From 8a87e257bb55135005a90b14546e9c4a28d13590 Mon Sep 17 00:00:00 2001 From: AlstonLi007 <148654191+AlstonLi007@users.noreply.github.com> Date: Thu, 9 Oct 2025 08:53:13 -0500 Subject: [PATCH] Consolidate Chinese texts and add financial tools --- ...1\223\343\200\213\345\216\237\346\226\207" | 94 - ...1\223\343\200\213\350\247\243\351\207\212" | 11 - ...0\216\344\271\210\345\212\236\343\200\213" | 13 - ...5\225\344\272\244\346\230\223\343\200\213" | 40 - ...1\200\351\231\220\346\200\247\343\200\213" | 14 - ...2\204\344\275\277\347\224\250\343\200\213" | 9 - ...1\206\346\263\250\350\247\243\343\200\213" | 5 - ...0\215\345\217\230\345\274\217\343\200\213" | 12 - ...0\265\350\247\243\351\207\212\343\200\213" | 28 - ...4\227\350\277\220\345\212\250\343\200\213" | 18 - ...1\251\345\210\251\347\216\207\343\200\213" | 11 - ...3\223\346\211\221\345\255\246\343\200\213" | 1 - ...holes\346\250\241\345\236\213\343\200\213" | 5 - ...7\207\350\256\277\347\250\277\343\200\213" | 1058 --------- 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financial_programs/__init__.py create mode 100644 financial_programs/fixed_income.py create mode 100644 financial_programs/option_pricing.py create mode 100644 financial_programs/portfolio_analysis.py diff --git "a/001\343\200\212\344\275\233\346\263\225\347\262\276\351\253\223\344\270\216\346\257\224\345\272\223\344\271\213\351\201\223\343\200\213\345\216\237\346\226\207" "b/001\343\200\212\344\275\233\346\263\225\347\262\276\351\253\223\344\270\216\346\257\224\345\272\223\344\271\213\351\201\223\343\200\213\345\216\237\346\226\207" deleted file mode 100644 index b43e182..0000000 --- "a/001\343\200\212\344\275\233\346\263\225\347\262\276\351\253\223\344\270\216\346\257\224\345\272\223\344\271\213\351\201\223\343\200\213\345\216\237\346\226\207" +++ /dev/null @@ -1,94 +0,0 @@ -比库对世间的惠益：佛陀教导妙法，为世间与出世间指明繁荣之道，依此道而行者能获得世间与出世间的一切利益。正是比库们防止了佛陀教法的消亡，若非比库，或许佛法早已从世间隐没。令佛法久住是比库们对世间最大的贡献。 - - -人们亲近比库、聆听佛法开示，由此皈依三宝、受持五戒、增长慈悲、学习佛法、减弱愚痴、投入禅修，他们于此生和来世收获快乐。有些人证悟入流道果等出世间成就；有些亲近比库的信徒，认识到佛陀教法的意趣、出家加入僧团，证悟涅槃。 - - -许多人亲近比库后，听取规劝、戒除酗酒等恶习，提升了做人的品德；还有一些人跟随比库们学习，得到提升。已加入僧团或是希求加入僧团的人，应常省思持戒的功德，以及为自己和世间带来的惠益，如法如律地生活。 - - -成为优秀的比库：于此教法中，那些已经获得禅那（安止定）或更殊胜能力的比库们，被认为是优秀的比库。现今有此能力的比库虽然不常见，但也不能一概而论的说，世上没有这样的比库了。 - - -结合现今的情况，如果比库不违犯守护出家身份的重要戒条，尽力持守所有的戒律，破戒后悔过改正，履行所有义务，致力于学习、教授和开示佛法，以及念诵护卫和禅修等比库之修行，努力降低贪婪、傲慢等烦恼，提升慈悲等功德；如此，即使他没有固定的住处和施主、没有亲戚和财物，只是过游方行脚的生活，依然可称为优秀的比库。 - - -当知不应以地位、学历和财产来衡量比库的高尚，比库的高尚在于戒德、定德、慧德等品质。比库不应为了获得供养而取悦信徒，不应为了获取资具而参与不如法的活动，只应踏踏实实地修行。也许他会缺衣少用，也许走到哪里都会遇到无礼之人，也许因少有人供养，而很长一段时间生活陷入困窘；若此时他能够如法如律地行持，他会因这些障碍而提升。 - - -就算比库身处非常困难的环境，若他以非法方式索求资具、破坏诸如非时食等戒条，他也不算是优秀的比库。想要成为一名优秀的比库，身、心必须准备好面对各种考验。娇贵的身体对修行是巨大的障碍，身体越娇贵需求越多。那些爱护身体的人，想方设法为身体提供所需，供给不足时就不得不通过非法途径获取。 - - -想避免这种障碍，我们成为优秀的比库必须准备好忍受酷暑、雨露和任何天气的考验，吃不饱时可以依靠任何粗食生存，能忍受任何难吃的钵食，能以任何种类的饮食维生，乃至忍受蚊蝇瘟疫。 - - -印度教行者靠运动提升身体机能，巴利圣典中虽未记载释子沙门会锻炼身体，但释子沙门通过锻炼保持健康并不是坏事。即使不锻炼，走路、外出托钵、履行义务等活动，也会在很大程度上帮助调节身体。 - - -为提高身体的适应能力，行者应练习在硬面上坐卧，培养于户外逗留、宿眠的能力，应适应饮用白水取代夜分药，饮食知节量，即使在允许的时段内也不要吃零食。以茶、咖啡等糖饮作为夜分药的习惯，对身体是有害的。如今比库们习惯喝夜分药，古代的比库并没有这种习惯，他们用冷水解渴。 - - -比库的义务里清楚说明需常备饮用水，在《律藏·大品·大犍度》的“义务”部分，没有提到应向客僧供夜分药以取代水。此点在以下的《律藏》义注中也有清楚说明：“客僧若饮完供给他的水，供水的比库应该询问是否再需要一杯。”这里表明比库应以水解渴，而非茶饮、咖啡等夜分药。缅甸比库也没有饮用夜分药的习惯，客僧都是喝白水的。 - - -心的调御，即是去除杂染与贪欲、培育少欲知足等僧格或品行。通过学习和实践比库必备的僧格或品行，可以令心调御。对名闻利养的渴望，是成为优秀比库的障碍。一位比库若要圆满自己的出家生命，应习惯于满足任何所得到的袈裟等必需品。 - - -学习并念诵沙利子大长老的教诫，会对比库助益颇多：“无论美食或粗食，比库不应完全吃到饱腹；而应时时省思，饮食知量。”“食用比实际所需少四或五口的米饭，随后饮水；对于心向涅槃的比库，这样的生活足够安适。”“只要袈裟如法而得，如律覆体，足可御寒；对于心向涅槃的比库，此袈裟足够安适。”“于坐卧处盘腿而坐，只要不令膝盖打湿；对于心向涅槃的比库，这样的僧舍足够安适。” - - -若比库无法调御自心，即会陷入贪婪，无论得到多少资具都不满意。“我穿这些旧袈裟太丢人了，我这样怎么出门？我怎么能吃这些食物？若有人来这间破旧的住处让我情何以堪！我让访客坐在哪儿？我没有收入来源，要是病死该怎么办？如果我不得不出门该怎么办？……”心未调御的比库，会因如是之匮乏而懊恼，身体因此憔悴黯然甚至病倒；懊悔之后不久，便开始逐步用非法手段获取资具。 - - -若比库心已调伏，他不会为了四资具短缺而懊恼；无论当下状况如何，他都会知足，并依此而生存。他省思自身戒德等善行，生活充满喜悦。生活在丛林中的隐士，依靠水果和绿色植物生存，食物无盐无糖、未经烹饪，他们仍然健康长寿，全赖调伏之心所生起的喜悦。比库的心被调伏之后，所需越少越惬意。 - - -我们的菩萨，过去有一世曾是德米亚王子，住在丛林里修行。他的父王来探望他，看到菩萨的住处和食物，很震惊地问：“你吃这样的食物，独居山林，为何色身如此明净？” - - -菩萨以如下偈颂回答父亲：“大王，我睡于铺在地面的树叶上，以独自睡眠令色身明净。我没有皇家卫兵佩剑守护在侧，以独自安然睡眠令色身明净。”“大王，我不懊恼过去，不憧憬未来，活在当下，以此令色身明净。因为期望未来、懊悔过去，身体会如砍倒的竹竿一般，在烈日下枯萎。” - - -意识到这些过患，无论资具如何匮乏，比库也绝不应贪着，而应省思修行的殊胜、守护戒律。佛陀曾说：“愚人身心未调御，出家对于他们是艰难的；他们不能忍耐，无法持久，出家后被诸多困难吓退。”“比库若不停止逐欲之心，他又能坚持修行几天呢？他始终会被不善心干扰，最终放弃修持沙门法，得不到任何提升。” - - -破戒的过患：比库护戒应不亚于保护生命。破戒者佯装具德比库、混在清净比库的队伍里，乍现律仪相，伪装具德者而受到恭敬，他也受用佛陀只开许具德者使用的资具、接受具德比库的礼敬，参加戒律甘马，这些是非常严重的过失。“如同不握好古沙草会割伤手，沙门执持邪行会趣向地狱。”——《法句·地狱品》 - - -佛陀在《火堆喻经》中提到，即使一个人双腿被牢固的绳索捆绑、由两位壮汉相对拉拽直到肉散骨断，或是以刀剑刺穿其胸膛，此人所受之苦不及破戒比库接受信徒礼敬所受果报之苦。佛陀进一步教导，即使身体被滚烫燃烧的铁片包裹，其苦不及破戒之人穿着信施袈裟所受果报之苦； - - -即使口被火红的铁钳撬开、再吞下滚烫的铁球，其苦不及破戒之人食用信施食物所受果报之苦；即使坐卧在滚烫的铁椅和铁床上，其苦不及破戒之人使用信施床椅所受果报之苦；即使被头朝下脚朝上地浸没在融化的铁水中，其苦也不及破戒之人住在信施建造的寺院所受果报之苦。《火堆喻经》是关于已从沙门法堕落而仍乍现沙门相的犯戒者，应受果报的开示。 - - -《清净之道》所提及的破戒过患应当牢记：“虽受礼敬乐，破戒有何乐？彼因此受苦，过于引绳锯。”“受信众合掌，无戒有何乐？彼因此受苦，过于利刀刺。”“不自调御者，受用衣何乐？久受地狱苦，火焰铁板触。”“无戒受美食，毒如哈罗哈，因此于长夜，吞咽热铁丸。”“无戒用床座，虽苦思为乐，热铁椅与床，恼苦无穷极。”“信施寺中住，破戒有何乐？因此彼当住，热红大铁釜。” - - -“世间导师呵：破戒如粪土，具恶有疑行，有漏而内腐。”“不御非沙门，但穿沙门服，善根自掘害，此生实卑恶。”“如欲庄严者，厌离粪与尸，寂静具戒者，弃彼命何如？”“不离诸怖畏，却离诸证乐，紧闭入天门，登临地狱道。”“破戒者破戒，具足诸罪恶，悲愍者所愍，舍彼复谁属？”“哪怕比库只破微小戒但不忏悔，仍以破戒而住，此人死后将投生为沙门鬼，身着热火袈裟，捧燃烧之钵。” - - -《相应部·因缘品·勒叉那相应》中，也记载在迦叶佛教法期，有些比库、比库尼、沙马内拉、沙马内莉由于恶行投生为悲惨的亚卡（夜叉），哀嚎着忍受燃烧之钵和袈裟的折磨，这一幕被路经灵鹫山的勒叉那尊者看到。事实的确如此，当知比库以非法行是极其危险的。 - - -比库的助缘：佛陀曾于行脚期间开示《火堆喻经》。听闻后，有六十位比库心生怖畏而吐血，又六十位比库还俗，离开时说：“终生做一名优秀的比库难，还是回家做居士更好”，又六十位比库听后断除烦恼体证阿拉汉。 - - -此经迅速在比库之间传播，许多比库听闻后还俗离去，说：“此教法中能够完全守戒简直太难！”于是，有十名、二十名、五十名、百名、千名的比库相继还俗离去，曾经满是比库的寺院如今空空如也。 - - -佛陀行脚后回到祇园精舍，休息两周后与阿难尊者一起巡视各地寺院，发现寺院荒芜、比库人数骤减、个个愁眉苦脸；佛陀问阿难，早前他游方回来时还满是比库的寺院，而今为何如此寥落呢？ - - -佛陀听完阿难尊者回复缘由，随后说道：“正如有许多港口可以入海，在我的教法里有许多方法可令比库满足。”于是，召集众比库宣说《小弹指经》：“诸比库！若比库修习慈心乃至一弹指顷，诸比库，此比库可说是未缺乏禅那而过活，奉行大师之教法而过活，维护大师之教诫而过活，他未享用民众所施之食而空过。更不用说经常修习慈心的人了！” - - -经中提到，戒等等素质圆满的比库受施者，才能为施主们带来大的功德利益。但是，比库们即使每天修习慈心禅哪怕一弹指顷，也是在遵从佛陀的教导、可以如法受用信施。慈心是高贵的美德，戒德不够，应以慈心来弥补。即使受供的比库戒德不圆满，若他充满慈心，供养者还是能累积大功德。既然能令布施者得到大利益，遍满慈心的比库受用食物并非无益。修习慈心的比库值得被礼敬和供养。 - - -“比库修习慈心乃至弹指顷，他可成为信施食物的主人、无负债者、继承者而受用此食。”该经义注中提到，比库修习慈心之后，能以主人般受用信施食物，不再是“借受用”，已转为“嗣受用”。始终保持戒律清净是非常难的，因此所有的比库们都应该修习慈心，每天至少修习片刻。 - - -慈心也是比库抚慰自心的方法之一。祝愿顶礼的信众“快乐平安”也是一种慈爱的形式。比库养成如此祝福的习惯，是为了去除因自己戒律不清净时，被礼敬而生的不善。（这一点大部分比库只是按照传统去做，却不知其因。） - - -《弹指经》有多部，这些经都是为了对应《火堆喻经》而开示的，经中囊括了所有形式的禅修。因此，当知不论比库修习何种禅修所缘，他都可以如法受用信施资具，接受礼敬。以佛随念来礼敬佛是一种禅修业处；以法随念来礼敬法是一种禅修业处；以僧随念来礼敬僧是一种禅修业处；很多比库每日皈依三宝，也是一种禅修业处。如此行持的比库有资格受用信施资具；而且此礼敬本身也对比库有大利益，亦成抚慰之因，所以比库应每日礼敬三宝！——摘自《教海觉舟》 diff --git "a/002\343\200\212\344\275\233\346\263\225\347\262\276\351\253\223\344\270\216\346\257\224\345\272\223\344\271\213\351\201\223\343\200\213\350\247\243\351\207\212" "b/002\343\200\212\344\275\233\346\263\225\347\262\276\351\253\223\344\270\216\346\257\224\345\272\223\344\271\213\351\201\223\343\200\213\350\247\243\351\207\212" deleted file mode 100644 index 12a77b9..0000000 --- "a/002\343\200\212\344\275\233\346\263\225\347\262\276\351\253\223\344\270\216\346\257\224\345\272\223\344\271\213\351\201\223\343\200\213\350\247\243\351\207\212" +++ /dev/null @@ -1,11 +0,0 @@ -比库的作用与贡献：佛陀教导了佛法，并指出了生活中的正确道路。比库是佛法的保护者，他们使佛法得以流传至今。 - -比库的影响：当人们接近比库并听取佛法，他们会受益于戒律、慈悲、智慧等，并在此生和来世中都会受益。 - -优秀的比库：真正优秀的比库不仅是遵循外在的戒律，而且是在内心中对佛法的真实实践，具有深厚的慈悲和智慧。 - -破戒的严重后果：破戒的比库可能会受到严重的果报或报应。比库应该始终维持他们的道德和修行标准，避免因破戒而受到的后果。 - -慈心的修习：慈心是比库修行的一个重要组成部分，它可以使比库对信众产生正面的影响，也可以帮助他们在面对困境时保持平和的心态。 - -心的调御与修行：为了真正地实践佛法，比库需要调节和训练他们的心，以达到真正的慈悲、智慧和清净。 diff --git "a/003\343\200\212\345\210\270\345\225\206\345\200\222\351\227\255\345\220\216\346\200\216\344\271\210\345\212\236\343\200\213" "b/003\343\200\212\345\210\270\345\225\206\345\200\222\351\227\255\345\220\216\346\200\216\344\271\210\345\212\236\343\200\213" deleted file mode 100644 index bf68f2b..0000000 --- "a/003\343\200\212\345\210\270\345\225\206\345\200\222\351\227\255\345\220\216\346\200\216\344\271\210\345\212\236\343\200\213" +++ /dev/null @@ -1,13 +0,0 @@ -投资者保护基金：许多国家或地区都有类似于美国的证券投资者保护公司（Securities Investor Protection Corporation, SIPC）这样的机构，用以保护投资者免受券商破产的影响。如果券商是这类机构的成员，客户的账户通常会受到一定限额的保护。例如，SIPC可以保护每位投资者高达50万美元的证券和现金，其中现金的保护限额为25万美元。 - -隔离客户资金：合规的券商应当将客户资金和公司自己的资金分开存放，即使券商破产，客户的资金也应当是安全的。这些资金应当被隔离在受信任的银行账户中，并且在券商财务出现问题时不能被用来偿还券商的债务。 - -转移账户：在许多情况下，当一个券商面临倒闭的情况时，监管机构会寻找另一家券商接管客户账户，从而客户的资产可以无缝转移，减少对投资者的影响。 - -破产程序：如果无法转移账户，券商会进入破产程序，破产清算人将按照法律规定和优先级别分配剩余资产。 - -索赔程序：客户可能需要在特定的期限内向破产清算人或保护基金提出索赔，以证明其账户余额和投资持仓。 - -监管机构介入：在券商倒闭的情况下，金融监管机构会介入以确保法律法规得到遵守，同时调查倒闭原因，并采取措施保护投资者利益。 - -客户能否全额收回资金取决于多种因素，包括券商的财务状况、客户资金是否被正确隔离、以及有无其他未履行的交易或债务。在任何情况下，作为客户，了解您的券商的监管状态、投资保护规则以及您作为投资者的权利是非常重要的。如果您的券商确实遇到了问题，您应当尽快联系当地的金融监管机构或投资者保护机构了解具体的索赔程序和步骤。 diff --git "a/004\343\200\212\347\234\213\346\263\225\345\222\214\351\243\216\351\231\251\347\232\204\350\267\237\345\215\225\344\272\244\346\230\223\343\200\213" "b/004\343\200\212\347\234\213\346\263\225\345\222\214\351\243\216\351\231\251\347\232\204\350\267\237\345\215\225\344\272\244\346\230\223\343\200\213" deleted file mode 100644 index 2974bfc..0000000 --- "a/004\343\200\212\347\234\213\346\263\225\345\222\214\351\243\216\351\231\251\347\232\204\350\267\237\345\215\225\344\272\244\346\230\223\343\200\213" +++ /dev/null @@ -1,40 +0,0 @@ -对跟单系统的详细评估需要从多个角度来考虑，包括技术性能、用户体验、风险管理、透明度和监管等方面。以下是一个详细的评估框架： - -技术性能 - -1. 执行速度：评估跟单指令从生成到执行的时间延迟。快速的执行对于避免滑点（成交价格与期望价格的差异）非常重要。 -2. 系统稳定性：系统是否稳定运行，没有频繁的中断或错误。 -3. 兼容性和集成：系统是否能与多种交易平台和工具无缝集成。 - -用户体验 - -1. 界面直观性：用户界面是否清晰易懂，新用户是否容易上手。 -2. 自定义选项：用户在跟单时是否可以设置自己的参数，如资金分配、止损水平等。 -3. 多样性和选择：提供多少交易者可供跟随，这些交易者的交易风格和表现历史如何。 - -风险管理 - -1. 风险控制工具：平台是否提供有效的风险控制工具，如止损订单、资金管理限制等。 -2. 跟单策略的风险评估：是否有系统来评估和显示每个可跟随交易者的风险水平。 - -透明度 - -1. 交易者历史表现：是否能够访问交易者的详细历史表现记录，包括盈亏、风险水平和交易策略。 -2. 费用和成本：平台的费用结构是否清晰透明，用户是否能轻易理解他们需要支付的费用。 - -监管和合规性 - -1. 监管地位：该平台是否受到认可的金融监管机构的监管。 -2. 资金安全：用户的资金是否存放在受监管的银行账户中，是否有合适的资金隔离措施。 - -社区和支持 - -1. 用户社区：是否存在一个活跃的用户社区，用于交流和分享经验。 -2. 客户支持：客户支持的可用性和响应速度，是否提供多语言支持。 - -性能和历史记录 - -1. 历史表现：评估平台上交易者的历史表现记录，但需记住过去的业绩不预示未来表现。 -2. 成功案例：是否有明确的成功案例，用户在使用该系统后的实际盈亏情况。 - -通过对这些方面进行综合评估，可以更全面地了解一个跟单系统的优势和潜在风险。重要的是，即使在使用跟单系统时，用户也应保持警惕，了解市场动态，并准备好应对可能出现的亏损。 diff --git "a/005\343\200\212\346\212\200\346\234\257\345\210\206\346\236\220\345\234\250\344\270\215\345\220\214\345\270\202\345\234\272\347\216\257\345\242\203\344\270\255\347\232\204\345\272\224\347\224\250\344\270\216\345\261\200\351\231\220\346\200\247\343\200\213" "b/005\343\200\212\346\212\200\346\234\257\345\210\206\346\236\220\345\234\250\344\270\215\345\220\214\345\270\202\345\234\272\347\216\257\345\242\203\344\270\255\347\232\204\345\272\224\347\224\250\344\270\216\345\261\200\351\231\220\346\200\247\343\200\213" deleted file mode 100644 index d350931..0000000 --- "a/005\343\200\212\346\212\200\346\234\257\345\210\206\346\236\220\345\234\250\344\270\215\345\220\214\345\270\202\345\234\272\347\216\257\345\242\203\344\270\255\347\232\204\345\272\224\347\224\250\344\270\216\345\261\200\351\231\220\346\200\247\343\200\213" +++ /dev/null @@ -1,14 +0,0 @@ -技术分析的角度： - -跳出技术分析看技术分析：意味着在应用技术分析时，需要从更广阔的视角考虑，不仅仅局限于图表和指标。要将技术分析放入整体市场环境的上下文中去理解。 -根据市场类型调整策略： - -趋势市场（如明显的上涨或下跌）：技术分析相对更有效，因为存在清晰的市场方向，使得技术指标能够提供更准确的交易信号。 -震荡市场（价格波动无明显趋势）：技术分析的有效性降低，因为缺乏清晰的方向性，使得预测变得困难。 -投资持有时间的考虑： - -上涨趋势中：长期持有可能更有利，因为趋势的持续可能带来更多利润。 -震荡市场中：短期持有可能更安全，因为长期持有可能会面临更大的价格波动和不确定性。 -技术分析的定位： - -技术分析应被视为一个跟踪当前趋势的工具，而不是一个预测未来市场走势的工具。它有助于分析和理解当前市场状态，但对于未来的预测需要更多信息和其他类型的分析。 diff --git "a/006\343\200\212\347\216\260\344\273\243\344\272\262\345\257\206\347\247\260\350\260\223\347\232\204\344\275\277\347\224\250\343\200\213" "b/006\343\200\212\347\216\260\344\273\243\344\272\262\345\257\206\347\247\260\350\260\223\347\232\204\344\275\277\347\224\250\343\200\213" deleted file mode 100644 index b1510f9..0000000 --- "a/006\343\200\212\347\216\260\344\273\243\344\272\262\345\257\206\347\247\260\350\260\223\347\232\204\344\275\277\347\224\250\343\200\213" +++ /dev/null @@ -1,9 +0,0 @@ -社交关系：王啸与嘉雯之间的关系可能较为亲密，或者他们在一个较为非正式的环境中交流。直接使用名字而不是带有正式性的“小姐”，显示了一种更随意的互动方式。 - -社会语境的变化：王啸的话反映了语言的社会文化含义随时间的演变。在当代，直接用名字称呼可能被认为更加平等和友好，而“小姐”则可能因为多重含义而变得不那么常用。 - -避免误解：正如您提到的，“小姐”在某些情境下可能会被误解或带有负面含义。王啸选择用名字来称呼可能是为了避免这种误解或负面的社会现实暗示。 - -文本风格：通过这种对话，作者可能在展现角色的个性或是塑造轻松幽默的对话风格，也可能是在提示故事的背景设定与时代环境。 - -原文“那我就直接叫你嘉雯，现在都不流行叫人小姐。”王啸打趣道。” diff --git "a/007\343\200\212\345\215\207\345\256\230\345\217\221\350\264\242\346\255\273\350\200\201\345\251\206\346\263\250\350\247\243\343\200\213" "b/007\343\200\212\345\215\207\345\256\230\345\217\221\350\264\242\346\255\273\350\200\201\345\251\206\346\263\250\350\247\243\343\200\213" deleted file mode 100644 index ab69514..0000000 --- "a/007\343\200\212\345\215\207\345\256\230\345\217\221\350\264\242\346\255\273\350\200\201\345\251\206\346\263\250\350\247\243\343\200\213" +++ /dev/null @@ -1,5 +0,0 @@ -"升官发财死老婆"是一个典型的中国俗语，含有讽刺和黑色幽默的成分。这句话的字面意思是“在一个人升官和发财的过程中，他的妻子会死去”，但实际上它通常不被理解为字面意义。这句俗语主要用来批评那些在追求权力和财富过程中忽视或牺牲个人关系的人。 - -它反映了一种观念，即在某些情况下，个人的职业成功和财富积累可能会对他们的私人生活，尤其是婚姻关系产生负面影响。在极端情况下，这种追求可能导致家庭关系的破裂或家庭成员的不幸。 - -总的来说，这个俗语是一个提醒，强调在追求事业和财富的同时，也应该注意保持生活的平衡，关注和维护重要的人际关系。 diff --git "a/008\343\200\212\345\205\270\345\236\213\347\276\244\345\222\214\345\207\240\344\275\225\344\270\215\345\217\230\345\274\217\343\200\213" "b/008\343\200\212\345\205\270\345\236\213\347\276\244\345\222\214\345\207\240\344\275\225\344\270\215\345\217\230\345\274\217\343\200\213" deleted file mode 100644 index 8ca1f39..0000000 --- "a/008\343\200\212\345\205\270\345\236\213\347\276\244\345\222\214\345\207\240\344\275\225\344\270\215\345\217\230\345\274\217\343\200\213" +++ /dev/null @@ -1,12 +0,0 @@ -"典型群和几何不变式" 或 "Classical Groups and Geometric Invariants" 的原理涉及数学中的抽象代数和几何学。让我们分别了解一下这两个概念的基本原理。 - -典型群 (Classical Groups): 这些是数学中的基本群体，主要包括以下几种： - -广义线性群 (General Linear Group, GL(n, R)): 包含所有n阶可逆矩阵，这些矩阵在实数或复数域上进行操作。广义线性群的操作是矩阵乘法。 -正交群 (Orthogonal Group, O(n)): 包含所有保持欧几里得空间中距离不变的n阶矩阵。这些矩阵与其转置矩阵相乘等于单位矩阵。 -辛群 (Symplectic Group, Sp(n)): 这个群体的元素是保持辛结构不变的线性变换。 -几何不变式 (Geometric Invariants): 这些是在几何变换（如旋转、平移、缩放）下保持不变的属性。它们在研究几何形状和它们的性质时非常重要。几何不变式的例子包括： - -面积和体积: 在合适的几何变换下，这些度量保持不变。 -曲率: 在曲线或曲面上的点的局部弯曲度，是一种重要的不变量。 -在典型群和几何不变式的研究中，一个关键的方面是理解这些群如何通过它们的作用来保持某些几何结构或不变式。例如，正交群的元素保持空间中的角度和距离不变，这是研究欧几里得几何的基础。这些概念在理论物理、机器学习、数学物理和许多其他领域都有广泛的应用。 diff --git "a/009\343\200\212n\351\230\266\345\217\257\351\200\206\347\237\251\351\230\265\350\247\243\351\207\212\343\200\213" "b/009\343\200\212n\351\230\266\345\217\257\351\200\206\347\237\251\351\230\265\350\247\243\351\207\212\343\200\213" deleted file mode 100644 index fe8b48e..0000000 --- "a/009\343\200\212n\351\230\266\345\217\257\351\200\206\347\237\251\351\230\265\350\247\243\351\207\212\343\200\213" +++ /dev/null @@ -1,28 +0,0 @@ -在数学中，特别是在线性代数中，一个n阶可逆矩阵是指一个n×n的矩阵，它满足以下条件： - -1. 方阵：这个矩阵是方形的，意味着它的行数和列数相同，都是n。 - -2. 可逆性：存在另一个n×n的矩阵，称为其逆矩阵，与原矩阵相乘时，结果是一个单位矩阵。单位矩阵是一个主对角线上的元素全为1，其余元素全为0的方阵。 - - - 如果一个矩阵 A 是可逆的，那么存在一个矩阵 B 使得 AB = BA = I，其中 I 是单位矩阵。 - - 这个矩阵 B 被称为 A 的逆矩阵，通常记作 A^{-1}。 - -3. 行列式非零：一个n阶矩阵是可逆的当且仅当其行列式（一个从矩阵计算得到的标量值）不为零。 - -4. 线性独立的行或列：矩阵的所有行（或列）都是线性独立的，这意味着没有一行（或列）可以表示为其他行（或列）的线性组合。 - -可逆矩阵在数学和应用科学中非常重要，因为它们提供了线性方程组解的存在和唯一性的条件，并且在变换、系统理论和许多其他领域中都有广泛的应用。 - -将n阶可逆矩阵应用到金融领域，可以通过多种方式，包括风险管理、资产组合优化、定价模型等。以下是一些具体的应用示例： - -1. 资产组合优化：在构建投资组合时，投资者希望最大化回报的同时控制风险。通过使用矩阵，可以计算资产之间的协方差，这有助于理解不同资产价格变化的相关性。在这个框架下，可以使用可逆矩阵来解决优化问题，找到风险和回报之间的最佳权衡。 - -2. 风险管理：金融机构使用可逆矩阵来量化和管理风险。例如，在计算Value at Risk (VaR) 或其他风险度量时，可逆矩阵用于模拟不同资产组合的风险敞口。 - -3. 定价模型：在金融工程中，复杂的定价模型（如Black-Scholes模型）常用于衍生品定价。这些模型中，可逆矩阵有助于解决线性方程组，这些方程组用于模拟金融市场中的各种因素。 - -4. 因子分析：在评估证券性能时，因子模型（如Fama-French三因子模型）用于解释不同资产收益的变动。可逆矩阵在这些模型中用于从历史数据中提取关键因子，并帮助投资者理解市场动态。 - -5. 算法交易：在算法交易中，可逆矩阵用于构建复杂的交易算法和策略。这些策略通过分析历史数据和市场行为，自动执行交易决策。 - -在金融中应用矩阵和线性代数不仅仅是处理数字和方程，更多的是关于理解和解释市场行为，以及在此基础上做出有效的投资和风险管理决策。 diff --git "a/009\343\200\212\345\270\203\346\234\227\350\277\220\345\212\250\343\200\213" "b/009\343\200\212\345\270\203\346\234\227\350\277\220\345\212\250\343\200\213" deleted file mode 100644 index 743031e..0000000 --- "a/009\343\200\212\345\270\203\346\234\227\350\277\220\345\212\250\343\200\213" +++ /dev/null @@ -1,18 +0,0 @@ -布朗运动（Brownian motion）是一种随机运动，由悬浮在流体（如空气或液体）中的微小粒子所展现。这个名字来自于19世纪的生物学家罗伯特·布朗，他首次观察并记录了花粉在水中的这种运动。 - -在二维空间中，布朗运动的轨迹可以用一个粒子在x和y坐标上的位置变化来表示。每个方向上的移动都是随机的，粒子在每个时刻都可以向任何方向移动一小步。这些随机步伐可以由温度、粒子大小、流体粘度等因素影响。 - -从图中的左侧可以看到，粒子的路径非常杂乱无章，没有明显的方向或模式，这是布朗运动的典型特征。每个转折点代表粒子的方向发生了随机变化，整个路径构成了一个复杂的、连续的轨迹。 - -布朗运动是热力学和统计物理学中的一个重要现象，因为它提供了原子和分子运动理论的直观证据。在金融领域，布朗运动模型也被用来描述资产价格的随机变化，这是许多金融数学模型的基础，如股票价格的随机漫步模型。在这些模型中，价格变化被假设为连续时间随机漫步，它们的变化率（即“回报”）遵循布朗运动。 - - -时域上的布朗运动的y轴是什么. - - -在时域上的布朗运动图中，y轴通常代表某个变量随时间变化的值。具体来说，这个变量可能是： - -粒子在某一固定方向上的位移，例如在水平或垂直轴向上的位置变化。 -物理量的大小，如粒子速度、加速度或其它可以随时间变化的物理属性。 -金融中的资产价格变动，如果这个图表示的是金融模型中的布朗运动，y轴可以代表资产价格的变化或回报率。 -对于上传的图的右侧部分（假设它描述的是一维布朗运动），y轴显示的可能是从起始点开始的累计变化，而x轴则代表时间。这种图通常用于显示随机过程中某个变量随时间的演变，如随机漫步或股票价格在某段时间内的变动。 diff --git "a/010\343\200\212\346\227\240\351\243\216\351\231\251\345\210\251\347\216\207\343\200\213" "b/010\343\200\212\346\227\240\351\243\216\351\231\251\345\210\251\347\216\207\343\200\213" deleted file mode 100644 index 60ac1ae..0000000 --- "a/010\343\200\212\346\227\240\351\243\216\351\231\251\345\210\251\347\216\207\343\200\213" +++ /dev/null @@ -1,11 +0,0 @@ -无风险利率（Risk-Free Interest Rate）是指在理论上没有违约风险的投资的回报率。换句话说，这是投资者投资于绝对安全的资产所能获得的收益率。在实际中，虽然没有绝对无风险的投资，但某些资产被视为近似无风险，例如一些政府债券。 - -政府债券作为基准：经常将稳定国家（如美国、德国等）发行的短期国债视为无风险资产。这是因为假设这些国家不会违约，因此，这些债券的收益率常被用作无风险利率的代理。 - -在金融模型中的应用：无风险利率在许多金融模型和计算中扮演重要角色，例如在资本资产定价模型（CAPM）中，它用于确定资产的预期回报率。此外，它也是计算投资组合的夏普比率（一个衡量风险调整回报的指标）的关键因素。 - -经济指标：无风险利率还被视为一个重要的经济指标，反映了市场对经济环境和货币政策的预期。例如，较低的无风险利率通常表明中央银行正在实施宽松货币政策，以刺激经济。 - -与市场风险的关系：无风险利率为投资者提供了一个基准，用于衡量承担额外风险的相对吸引力。投资者寻求超过无风险利率的回报来补偿他们承担的更高风险。 - -总体而言，无风险利率是理解和评估金融市场中风险和回报之间关系的一个基本概念。 diff --git "a/011\343\200\212\346\213\223\346\211\221\345\255\246\343\200\213" "b/011\343\200\212\346\213\223\346\211\221\345\255\246\343\200\213" deleted file mode 100644 index 8b13789..0000000 --- "a/011\343\200\212\346\213\223\346\211\221\345\255\246\343\200\213" +++ /dev/null @@ -1 +0,0 @@ - diff --git "a/012\343\200\212Black-Scholes\346\250\241\345\236\213\343\200\213" "b/012\343\200\212Black-Scholes\346\250\241\345\236\213\343\200\213" deleted file mode 100644 index 97f6cca..0000000 --- "a/012\343\200\212Black-Scholes\346\250\241\345\236\213\343\200\213" +++ /dev/null @@ -1,5 +0,0 @@ -Black-Scholes模型是一个用于金融市场中的期权定价的数学模型。这个模型由Fischer Black和Myron Scholes在1973年提出，并且后来Robert Merton对其进行了发展。这个模型的核心是一个偏微分方程，用于计算欧式期权的理论价格。欧式期权是一种标准类型的期权，它只能在到期日那一天行使。 - -Black-Scholes模型的重要性在于它提供了一个理论框架来理解期权价格如何受到各种因素的影响，如标的资产的价格、行权价格、到期时间、无风险利率和资产价格波动性（通常用标准差衡量）。这个模型假设资产价格遵循几何布朗运动，并且市场是无摩擦的（即没有交易成本和限制）。 - -Black-Scholes模型对金融领域产生了深远的影响，尤其是在风险管理和衍生品定价方面。它的一个主要局限性是它基于一些理想化的假设，例如恒定的波动率和对数正态分布的资产价格变化。实际市场中的复杂性往往要求对这个模型进行调整或使用更复杂的模型。 diff --git "a/013\343\200\212Steven Dux \344\272\244\346\230\223\351\207\207\350\256\277\347\250\277\343\200\213" "b/013\343\200\212Steven Dux \344\272\244\346\230\223\351\207\207\350\256\277\347\250\277\343\200\213" deleted file mode 100644 index 14f2b77..0000000 --- "a/013\343\200\212Steven Dux \344\272\244\346\230\223\351\207\207\350\256\277\347\250\277\343\200\213" +++ /dev/null @@ -1,1058 +0,0 @@ -0:00 -First Trade was very lucky I think I made 10,000 in one trade really yeah I -0:05 -think I with $25,000 yeah and and the next few weeks -0:11 -instantly 50% down and this is all your first year of trading or how long dides -0:16 -it take for you to eventually become profitable 6 months 6 months yeah 6 months uh I think the fastest approach -0:23 -to trading is to look at other people's mistakes because what whatever mistakes they made I might run into it later -0:30 -um everybody know that I made 6 million on the on the first day I made three M 3.5 million on the following day and I -0:37 -made a 9 or 3 million on the following day after the 3.5 million so that week total I made 17 million I think oh my -0:44 -God I don't ever focus on how much money that was generated by trading I want to -0:50 -perfect the system okay make sure it hits the maximum performance of all the patterns that I track once I reach 85% -0:58 -I'm creating trading hi have you ever wondered how much money a retail Trader can make in a single trading day in this -1:05 -episode we have a very special guest The Man of Mystery Stephen ducks ducks is a -1:11 -verified Trader and he holds a record for the highest p&l in a single trading day in 2022 making over $6 million -1:20 -trading dwac in one day I personally have a lot of respect for ducks he's -1:26 -very young but he has matured as a Trader and master the Arts of trading penny stocks using psychology and -1:33 -statistics and extreme discipline in this video you're going to learn Steven's approach to trading smoke cap -1:40 -stocks using Trader psychology Steven's various methods of tracking statistics -1:46 -how to recognize patterns and capture High profitability trades and how to avoid over trading make sure to hit the -1:54 -like button and join me today for a very insightful conversation with Steven ducks -2:01 -[Music] welcome to the humble Traders podcast -2:07 -Stephen hello you are a really famous Trader on Twitter and YouTube and you -2:14 -are really famously known for that I think was the dwac where you make six -2:19 -was it $6 million in one day yeah right so I think a lot of people know you for that and of course a lot of other -2:26 -profits you've had over the years if we could tell audience how this year treating you so far and how are you -2:31 -adjusting to the market this year is not as good as 2021 -2:39 -2022 the beginning of the year was okay uh since ever -2:45 -since uh May and June I mean the later this year is not very active yeah and uh -2:52 -this year's Market has been uh has been okay uh profitable and -3:00 -not making as aggressive as money as uh compared to -3:05 -2021 uh still up in the seven figures um and the lower seven figures okay not -3:14 -crazy high approaching eight figures um -3:19 -but volume has gone down about 90% 80% compared to 2021 and 2022 the market is -3:26 -become much more competitive compared to the last two years especially on the -3:33 -short side um as we know that shorting -3:39 -has 90% or or has much higher winning percentage compared to buying so -3:44 -majority of the money are H or held by shorts Setters and so if Shorts Setters -3:49 -are trying to Pile in into a ticker and there's not many Longs in there so there -3:55 -uh first short Setter cover and second short Setter cover above that so it will cause a massive parabolic uh as we saw -4:01 -in like top mhm so from my understanding is you're predominantly a short seller -4:07 -right okay I do want to ask you a little bit later on about like specific short strategies you're doing and how you're -4:13 -using your statistics to track those High odds as you call it um but that's take a step back how did you get into -4:19 -trading in the first place and how many years have you been trading now I got into trading when I was 19 so the the -4:27 -freshman year of college how did I get into trading you in school yes uh I -4:33 -don't have a very good family history but uh okay uh so at that time my mom -4:38 -and dad are going through divorce um so I was just trying to solve some of the -4:44 -financial pressure from my from my mom's side and uh I used my uh tuitions as my -4:52 -base money to trade which is about which is 25,000 yeah -4:58 -so um first of all I I think at the very beginning I lost half of it and then -5:04 -then I borrow some money from my friends started again you have rich friends not rich friends but I had to pay interest -5:11 -on that money so so okay so um but uh and they started again uh that's where I -5:18 -went from I think 27,000 to 900,000 first year then uh second year was 2.7 -5:26 -million third was I mean goes up from there so so you were trading with your -5:31 -tuition money and then eventually once you start making money is that how you paid for your school for the rest of the -5:37 -college or did you drop out of college I mean still in school and pay for the tuition of whatever the money I made -5:43 -from Trading okay and what was your major uh engineering oh I was going to -5:48 -guess either like mathematics or engineering uh chemical engineering -5:54 -chemical okay yeah so what what did you aspire to be at the time when you were still going through school -6:01 -uh I mean I like engineering I like very statistic based so a major and I chose -6:09 -engineering and the reason why I went to engineering I want to more Focus down into -6:14 -nanotechnology nanot technology yeah okay uh at that time we're focused on nanot tubes I think but uh then um I -6:23 -shift my focus more into trading afterwards so okay so how did you I -6:28 -understand you were trying to make some money to help out with a family so why Trad in stocks and how did you discover -6:35 -stock trading in the first place okay so yeah so um well first of all 25,000 is -6:41 -not a lot of money first of all as an international students we don't I mean -6:48 -our commun communication skills are not very good compared to the the natives -6:54 -people in here oh like in terms of English in ter yeah in terms of English so trying to do the the talk businesses -7:01 -or like real estate you have to communicate with other people so that's you know a big I say shortage for for -7:08 -some people like us and we also came in as a F1 student so you can't really have -7:15 -a job but only in campus you only can have a job in campus okay yeah I remember and -7:22 -you're making about like $6 an hour or $7 an hour so that's not efficient um -7:28 -and with 20 5,000 I look through pretty much all of the uh industry and the only -7:34 -one you can make money is trading to um uh using small amount of capital to -7:43 -get over 1,000% or 10,000% return that's where I looked into it and I see a lot -7:50 -of potential into it but I also see a lot of risk so just let need to take a bit I I I was also international student -7:58 -in the state I went to school school in Florida uhhuh so at the time I was I -8:03 -discovered trading around the last year so senior year but I didn't actually trade because I didn't have the money -8:09 -but I was like trying to save up from like my $7 an hour like on campus job but that -8:16 -helped me save us so that brought back some good memories yeah yeah I mean yeah -8:21 -similar similar to boat so you found out about trading stocks mhm did you start -8:27 -with like with day trading right away or did you invest or you know people do like a dividend investing or swing -8:33 -trading or did you just dive into the wild wild west of day trading not oh -8:39 -pretty much straightforward into day trading the first ticket I traded was ETF I think it was okay uvxy I mean it's -8:46 -ETF but uh that's the first trade made $20 but uh good -8:52 -job and uh I mean there's bunch of trading histories that have I think ad -8:58 -that straight pretty pretty much straightforward into day trading and uh the first trade was very lucky I think I -9:04 -made 10,000 in one trade really yeah I think I with $25,000 yeah oh okay I think I had a uh -9:14 -I think a $3,000 position okay so tiger went like 300% then I made 10,000 I -9:21 -think the trading could be that easy so oh okay and and the next few weeks -9:27 -instantly 50% down I mean TR on some stupid tickers and over trading were you -9:32 -following alerts at first or did you actually like try to learn strategies and trade I don't follow alerts and I I -9:42 -uh I I want to learn strategies because I look in this industry a little bit -9:47 -differently because I see well in trading industry if you if you make -9:52 -money somebody else is losing money right so zero some game yeah very simple -9:59 -concept yeah so um that means if you're following alerts a lot of people going -10:05 -into one directions that means the if 90% people in the trading industry are -10:10 -losing money yeah 10 10% are making money that means uh majority of the you know you -10:17 -have to go opposite of the what the majority go so I start going the opposite Sid of shorting alerts oh so -10:24 -you start out a contrarian from like very early on when people are like pumping what those alerts you were -10:29 -shorting them I'm shorting them yeah oh you fig that I was super early yeah I mean very beginning of my career I -10:35 -started making like 20% 30% again I mean then you start not that start not work -10:41 -doesn't well you start to not work as well because okay um my size is getting -10:47 -bigger and there's not many people chasing alerts anymore and the stock becomes very liquid so it's hard to get -10:52 -out uh but uh that's where my first I would say 50,000 40,000 oh -11:00 -so you started trading pretty big size almost right away then right cuz you mentioned you were taking $3,000 3,000 -11:07 -shares $3,000 worth of positions yeah okay I guess you were trading with a 25 -11:13 -$27,000 account to avoid PDT yeah and how often were you trading since you -11:18 -didn't have the Restriction of PDT were you still trading every day not trading every day okay um but when there's a -11:26 -play I'm in there so it's still overtrading but uh I think I was making about four -11:33 -to five trades a week and did you dive into full-time trading or were you still -11:38 -I guess you were you managing the classwork and trading on the site yes yes pretty much TR how did you find the -11:45 -schedule then I mean not I mean look at the phone during class I mean other other than the exam but you know just -11:52 -look at the phone during the class uh using TDM trade and not anything oh okay -11:58 -and how did that work out trading on the phone does not work very very well okay -12:03 -slow and uh first of all it's slow second it's I mean take a while to put -12:09 -in limit orders and limit orders yeah yeah so it's not quick at all it was -12:17 -sometimes you miss I miss couple thousand dollars just just trying to get out at one point and 10 second later you -12:23 -know we're 10% down and this is all your first year of trading or how long did it -12:28 -take for you to eventually become profitable 6 months 6 months yeah 6 -12:34 -months mhm that's really really fast uh yes because uh I look at so I -12:42 -think the fastest approach to trading is to look at other people's mistakes because what whatever mistakes they made -12:48 -I might run into it later defitely so I look through Gran's entire trading -12:54 -record yeah and I think was uh on the Tim side of the student they have their -13:01 -record on U on profit I think was a very early stage of trading and I was also looking -13:09 -at uh investor underground and other people you know people on Twitter they talk about their trading and poster -13:15 -profits I I don't typically look at their wins I only look at losses and I want to be able to even though they -13:22 -don't post the entry and exit chart but I want to be able to guess where where they short it is I see where where they -13:29 -got uh where they exited or uh maybe they made a huge M mistake they -13:35 -continued to add and eventually got BL out the position so all those mistakes -13:40 -are very valuable experience for me so that's when I become very uh profitable -13:45 -because I actively avoiding those mistakes yeah you you you're really young but you're also really wise a lot -13:53 -of people who start out trading they want to see like the flashy pnls a big profit but you were looking the opposite -13:59 -you're looking at people's losses and looking at learning from their mistakes yeah um and also I know that there's -14:08 -three base factors first of all is human mistakes that's number one you have to fix okay number two is um patterns come -14:15 -from psychology because if you're making money that means other people are making mistakes and you know how stock it -14:24 -really is it's really emotional driven yeah so psychology is very plays very -14:29 -big part of uh in trading so understanding the people that's going -14:35 -the opposite directions or um I mean they're behind the computer clicking the -14:41 -Button making mistakes so you have to understand their psychology first and third you have to use your statistics -14:47 -Theory to back up the psychology side um then with those three combined then it's -14:54 -instantly profitable so but it take it take a while take a while to get those -15:00 -three thing lined up together how long do that take you 6 months really you you -15:06 -everything clicked just like that in six months yeah oh wow so what kind of Statistics I know you mentioned that -15:13 -earlier in the beginning how what what were you tracking to realize okay I need to focus on this one strategy or these -15:20 -two strategy what kind of specific criterias were you looking at first of all I mean when I went went in there -15:27 -it's it's a there's a lot of stuff to track you can't you most people go in with okay -15:33 -well there's a lot of stuff I have no idea what to track right so you start narrow stuff down let's say we have a -15:41 -ticker that's 20 million market cap 3 million float uh very similar action put them -15:47 -together how much they traded uh to see there's any similar actions or similar -15:54 -Behavior or if it's going parabolic or start going M midday or Gap up in the pre market uh so pretty much you want to -16:03 -categorize very similar Market very similar Mark uh uh float um and the gap of -16:10 -percentages uh categorize them into one section try to find the conclusion of if -16:16 -volume changed what happened if flow changed what happened so you you kind of put a fixed criteria on All U pretty -16:23 -much everything and uh there's only one factor that's different I see so you -16:29 -will be able to kind of tell okay next time similar flow similar market cap if -16:35 -the volume is different I'm supposed to do this I see so you need a massive -16:40 -amount of Statistics to find uh I know I have I think at -16:46 -beginning I 25 sections okay with market cap between 0 to 10 million FL between 0 -16:52 -to one uh Gap up over 50% or market cap between 0 to to 20 or float between 1 to -17:01 -three see this time is different but with gap up percentage with 50% so you only have the flow difference I see and -17:09 -once you only have the flow difference uh with very similar volume throughout the day so you can kind of see what how -17:16 -much did the spiking percentage changed oh so that's one method of how to figure -17:23 -out what to track okay let me sum up that really quick cuz you just mentioned a lot of things I want to make sure -17:28 -audience understand your method ex the first method you mentioned really clearly so essentially you're trying to -17:35 -find the first method that say you narrow down let's say 10 stocks that you -17:40 -know are low flows they have similar volume and then you look at different categories like the volume pre-market -17:46 -volume you know percentage Spike after open and you look at what they have in common yeah and what's the outlier -17:53 -criteria whether it be super low float or super high volume that cost -17:59 -potentially have caused that one stock to Stand Out Among the most yes oh okay -18:04 -got it okay uh first criteria and second is you second way to be able to track uh -18:12 -statistics is you want to focus on volume specifically because people are -18:19 -behind computers trading the tickers right so every shares they trade means one shares and well of course there's -18:26 -alos and H found involved in there but you have to think there's one thing that -18:32 -the Hedge found that won't do is they take the entire the flow so basically -18:37 -they buy the entire flow okay and first of all they have they have to file to the SEC that's very that's you know not -18:45 -very convenient that's what they what they don't want to do and second you -18:50 -want to if you want to pump the stock you don't want to own the entire flow because eventually once you sell you're -18:57 -basically uh playing with yourself yeah there's no one else to sell to there's nobody else to sell you need the -19:02 -liquidity so you do not want to occupy the entire floor you want to retail to go in there yeah and pump the stock up -19:09 -and they sell into the retails and retails loses money so once you track enough multi- rers there's actually a -19:17 -very uh similar number that how much money can retail put into a ticker okay -19:25 -based on float or market cap based on market cap okay yeah so uh that's -19:31 -another way to track statistics based on how to really short into multi owners so -19:38 -in that case that say hypothetically speaking your second method just mentioned let's say based um I don't -19:45 -know 50 mil market cap retail can only let's say from that tracking retail can -19:51 -only get up to you know 10% of that market cap and then that's the ideal time to short uh yes yes but more more -20:01 -accurately uh do you want to be more accurate is you want to use the volume -20:06 -uh times the average traded price on that day if it meets the threshold of how much money that retail can pour into -20:13 -stock that means stock will go down next day uh because basically the stock has reached the maximum threshold that -20:19 -retail can push up to the maximum maximum percentage yeah yes oh interesting I never thought of that way -20:26 -or dollar amount there there's a lot of uh I can go uh so I I'll do three um -20:33 -there's another way to track statistics mean uh which I personally use which -20:38 -will be volume comparison is that you want to um so -20:46 -there's three different uh uh categories you want to do you want to track first -20:51 -of all is uh to be able to correctly track in resistance okay and lot of people see -20:58 -okay well there's a resistance that traded 50 million volume on a price of -21:05 -three and uh next time I want to short against with that $3 resistance right -21:12 -okay and so let's see for example let's say uh 50 million Vol that means five -21:19 -people let's say five people bought stock at three two mon later stock instantly dumped 90% everybody wants to -21:25 -get out because well if I get out I'll be down % what's the point of me selling right now since I'm already down 90% so -21:33 -the first reaction that when stock pushes back two three right everybody wants to wants to sell okay that's their -21:40 -instant reaction that's human psychology right there so and but here comes a problem because -21:48 -we're dealing with low floats so if the stock only have 3 million float and has 50 million volume in there and that -21:55 -doesn't mean that there's 5050 million resistance in there cuz there's only 3 milon volume 3 million flow sorry okay -22:03 -from previous let's say uh chart the resistance from like weeks ago yes -22:08 -doesn't have that much volume is what you're saying no doesn't it doesn't have the flow in there doesn't have 1550 -22:14 -million flow okay so if you want to let's say one one um every share is a -22:19 -back holder 15 million shares means 15 million back holder but if there's a 15 million shares only 3 million flow -22:26 -there's only 3 million back coders okay does that make sense that makes sense yeah so uh next time when you try to -22:33 -short into resistance that's the statistics you want to track because you are shorting a 50 million -22:41 -resistance but there's only 3 million backers in there okay so there's a very possible chance that stock can push -22:48 -through that resistance because there's only 3 million flow oh I see so a lot of -22:53 -people trying to just short based on how much volume uh that that's against the -22:58 -15 million that's a very interesting statistics to track -23:04 -and um it you can once you track that statistics you can help you avoid a lot -23:11 -of traps traps see so I think the first two method you mentioned helps you find -23:16 -a potential short entry the third one helps you avoid getting squeezed yes okay yeah oh thank you for sharing that -23:24 -there's uh there's many many many uh uh stuff that I I mean I came up in the last couple -23:31 -years what about you are you tracking any kinds of stats yourself make sure to share with other Traders down -23:38 -below is that do you think that's the reason why you pretty much stick with -23:43 -small caps cuz when it comes to large cap stocks there's a lot a lot less of these in inefficiencies right and a lot -23:51 -of the patterns the stats you track do they apply to other kinds of stocks no -23:56 -they don't uh the limitation is uh well except 2021 but the -24:04 -limitation is you cannot go beyond market cap that's above 300 million -24:09 -initial initial market cap so if the stock starts to spike starting with 300 million market cap then doesn't work -24:16 -okay but start less than 300 million let's say started around 100 million then goes all the way to couple billion -24:22 -it works oh so you're talking about let's say the first day of the run where the stock already started from yes oh so -24:30 -anything about 300 mil that doesn't count that still categorize a small cap right yes still categorize but you just -24:36 -won't trade it I just won't trade it oh so how you pick your stocks to trade is by volume and the market cap has to be -24:44 -below 300 mil yes oh okay and what kind of volume are you looking for when you are scanning for stocks to trade each -24:50 -morning uh really depends I mean volume highest the higher the higher the better -24:56 -okay uh I mean I do avoid first Green Day very crowded volume okay avoid that -25:03 -type of tickers uh but once they exhaust their volume then uh higher the volume -25:10 -the better yeah okay what about percentage gapper percentage um is there -25:15 -a point of like too high or like too low if it gaps above 200 I would say oh well -25:22 -it's probably more ridiculous when it's gaps above like 500% then it looks a -25:28 -little bit fishy to me um but the ideal range should be -25:34 -between 100 to 150 100 to 170 yeah percent -25:41 -percent oh okay like it has to have gapped up that much for you to be interested in trading them not -25:47 -interested but more comfortable trading okay I Gap up 500% I'm still interested -25:52 -in trading them I'm just want to be a little bit cautious on how to size in okay yeah so I I get that you know 100% -26:01 -gainers are very normal in 2020 and 21 but how what about in 2022 and 23 how -26:08 -are you selecting stocks then do you change your criteria there's still gappers that's above um 20 100% okay -26:17 -very few yeah very very uh we have let's see mmv that's one mhm when kep 200% -26:27 -then um yeah not many we had VC IG and all -26:33 -those biotechs that only gapped up like 80% so yeah above 100% is my highest -26:40 -winning percentage okay less than 70% if it doesn't have a resistance and -26:45 -on first screen day and it's a biotech yeah that's that's a noo for oh so you also don't want to trade try to avoid -26:52 -biotechs yeah yeah okay is there a reason why oh every time when I trade biotch I lose I mean it's and ATT track -26:59 -statistics on I still lose so I've been fighting biotch for many years now and -27:04 -uh it's sometimes you win sometimes you lose but by the end of the day you lose money right and and uh doesn't really -27:12 -matter we are going short we going along yeah biotches are very hard to predict they do not follow small cap stati -27:18 -statistics at all oh interesting so not only do you track those individual stocks or sectors or like the individual -27:25 -stock criteria you also track your own performance trading these stocks yeah I track everything yes okay how much the -27:32 -stock will drop to at what percentage to what scent I can get to that sometimes -27:38 -yeah that's how i' be able to bottom tick and top tick a ticket oh so what's like the a general formula you use to -27:45 -find the the top tick and the bottom tick and there's no general formula it's based on different patterns okay yeah -27:51 -every pattern has its own top tick and bottom tick tick uh point oh okay let's talk about your f favorite pattern do -27:58 -you have one right now uh favorite pattern probably this year it's first -28:03 -red day okay um highest they can drop other than IP other than IPO IPO will be -28:10 -a little bit different uh but not IPO multi owners the percentage that can -28:16 -drop market cap that's initially below 100 million flow below 5 million under -28:22 -10 million that work too uh the ne the average fading percentage for first red -28:30 -day is negative 26% average okay second day -28:35 -15% and the time typically drops to is 10:30 so once -28:42 -you once reaches okay 10:30 a.m. that's typically the lowest point oh after the -28:48 -first red day so typically you want to hold it overnight with a gap down next day hold on until 10:30 then you cover -28:54 -it yeah okay so these are ways that's like for this particular pattern the -29:00 -first red day that's how you find your exit yeah how do you find your entry now entry is the method that I talked about -29:08 -uh maximum volume on retail or maximum dollar being traded on the retails oh I -29:14 -see do is that your favorite pattern this year has that how how is that one pattern been performing for you this -29:20 -year it's still perform great it just the statistics keeps changing there's -29:26 -the that's flowing in the retail Market keeps changing yeah uh in -29:32 -2021 was 1 billion Inay mhm in I think like htz was something like that Herz -29:39 -yeah yeah I mean not Herz is a billion dollar cap so it's doesn't count that doesn't count but for lower cap the it's -29:47 -1 billion okay and for 2023 it's only 200 million so we can see that how much -29:53 -you dropped w a huge drop so we just talk about your favorite pattern what's your your biggest win ever on that -30:00 -specific pattern and your biggest loss we can cover that the first red day or I guess what -30:08 -the most memorable winner and the most memorable loser that You' ever had winner it's dwac dwac -30:19 -m um everybody know that I made 6 million on the on the first day I made -30:24 -three 3.5 million on the following day and that 9 3 million on the following day after the 3.5 million so that week -30:31 -total I made 17 million I think oh my God uh or from shorting that stock right -30:37 -or from shorting DW and there's another ticket I followed with it I forgot what's the name it was a sympathy play -30:43 -okay I went from I think went from uh 40 no it was around 52 I showed -30:50 -it around 48 covered at 28 so it's it was a sympathy play of dwac okay uh uh -30:58 -the most memorable loss yes I do remember one it was a biotech uh oh okay -31:04 -1 minut Flo 13 million flow uh I think it didm the uh maximum -31:11 -retail number okay and uh you squeezed above it typically I size in pretty big -31:17 -once it once uh it meets the retail number I see because that's high winning percentage Yeah that's when the com -31:24 -losses and the liquidity was not very great so so so and it took a long time -31:29 -to exit that's why okay I think the highest was a million dollar loss yeah 1 million okay now that's why you kind of -31:36 -crossed out biotech from your trading list forever Blacklist now yeah yeah Black List oh okay I mean up to dat has -31:43 -still I don't know because biotechs like they have they they do Gap very often -31:49 -they Gap 100% 200% sometimes and when when there is no play going on like you -31:56 -know in the last couple months and everybody has attempt to trade that and everybody tempting yeah everybody's -32:02 -getting squeezed so um um to be a very -32:07 -consistent profitable Trader yeah to be to stay alive in this industry you have -32:13 -to be super disciplined so yeah yeah I noticed that you don't trade every day -32:18 -like most Traders do how how often do you actually Place trades in a given month uh 3 to five or 3 to a week oh no -32:28 -not three to five in in the recent months three three trades to four trades -32:35 -a month okay yeah typically one trade a week oh wow sometimes not even a trade -32:41 -yeah do you believe in well do you practice what um is also a term that we -32:47 -recently learned from uh lens Bret Brin sorry keep on uh mispronouncing his name -32:53 -he's mentioned this term called exponential bet sizing basically do you size the same across -33:00 -all your different patterns or do you have certain ones like your favorite one that you would use more risk on oh yeah -33:06 -that's compound compound growth is um so uh I have all the patterns winning -33:14 -percentage down mhm some patterns has 70% some some some patterns has 80% 90% -33:21 -the higher the winning percentage is that means bigger size for me okay and how do you allocate that let's say -33:27 -the basic average is that's just use for a simple simple number a thousand so -33:33 -then that's say that's the average right let's say anything with 60% win rate you use an average of $1,000 risk and how -33:41 -would you use that for your um 90% win rate or your 80% win rate um patterns -33:48 -like what what number would it be 10x 10x oh okay yeah so if so average I'm -33:54 -using 100K 200k positions then and yeah the best it would be 2 million highest -34:01 -that size was 17 million was crazy 17 million shares traded not a$ 17 million -34:07 -position oh okay and how do you scale in because I understand once you're starting take taking these like massive -34:13 -sizes how do you scale into your position uh how do you scale in Parts by -34:20 -parts and has to be under 1% of the volume yeah yeah okay so let's say for -34:26 -example for a stock your max size will be let's say in this example 100,000 -34:32 -shares and you just divide it up into 10,000 share Lots or maybe 20,000 share Lots 50 50 yeah the bigger the positions -34:40 -maybe you have to break down a little bit more but yeah under $1 million it should be two okay two entries oh okay -34:48 -maybe three yeah do you think new Traders should learn about scaling as well or they should do one entry one -34:55 -exit one entry one exit oh it's the most efficient is one one enter and one exit -35:01 -one go oh okay so you never started with like you know let's say divide it into -35:07 -two halves and then just add and add and then two exits uh sometimes you will turn into -35:14 -add and add and add and blow up oh okay yeah but it happens a lot to -35:21 -a lot to Traders oh yeah well basically in that case they're not adding to Winners they're adding aaging down to a -35:27 -loser yeah a lot of people think that uh add into -35:32 -winners carut losses into losers I disagree with that you have to -35:40 -know exactly where you enter exactly where you want to exit and before you -35:46 -enter the trade you should know that how much you will will lose if you fail so -35:53 -we mentioned that about your most memorable loss so when you take these big losses is it usually from slippage -36:01 -or or was everything calculated beforehand everything calculated really okay I already know that million loss -36:08 -was coming oh okay because it's a biotech and you were sizing in that is -36:13 -your A+ setup yeah so you willing to risk a bit more yeah okay I see you just -36:19 -shared some really good tips for a lot of the new be Traders basically you recommend one entry in one exit out yeah -36:27 -yeah don't over complicate this uh maybe two maximum two but I recommend one in -36:34 -and one exit oh okay and we also talked about statistics and tracking do you -36:40 -think beginners should be tracking like you are or they should simplify things or how how would you recommend them to -36:46 -approach tracking well first of all for people that come to trading you love trading I love trading I love to win -36:53 -yeah people some people come in for trading that they want to make money so either way you want uh you want to win -37:01 -so you whatever do whatever that makes you want to win I can guarantee you that -37:07 -tracking statistics will make you win more so okay uh I recommend track as -37:14 -much as you can uh do the method that I recommend the first method which finding -37:20 -out the outliers okay um and to see what's the uh Factor that actually -37:27 -affect the stock push uh fading percentages or pushing percentages um then you will start -37:34 -finding your entry from there so I think a lot of beginners also suffer from -37:39 -struggle with overtrading and how do you think they should is there any way in which they can utilize -37:46 -tracking statistics and help them avoid you know overtrading these like random setups yes there there's one way I found -37:54 -out I was very helpful and they should be the golden tips uh for -38:00 -not making stupid mistakes on over trading okay well I to be honest I over -38:05 -trade uh I see I even over trade I sometimes you know hate myself over -38:11 -trades because you know nobody wants to make stupid mistakes and wasting money on on you know something that you -38:18 -shouldn't do everybody does I don't think there's as long as you're not an -38:24 -algo everybody make overtrading mistakes so uh first method which will be the -38:31 -most important one is you want to track well first of all find your pattern find -38:37 -out the statistics find out the average winning percentage act find out -38:44 -uh the average um profitable percentages so let's say this pattern average profit -38:51 -you can profit around 15% 20% okay find out the frequency how many times happens -38:57 -a year generate a sheet that using a fixed size so let's say every time when -39:03 -this pattern appears I'm going to size in $5,000 I'm going to make $1,000 on the -39:08 -trade uh this pattern happens 50 50 times a year 60 times a year you can -39:15 -generate a number MH uh how much you can make a year that's your expected return -39:21 -that's true expected return okay so every time when you sit in front of the computer in the morning every day look -39:26 -at that number first okay look at it first right this is how much I'm gonna make a year so I'm not gonna make a -39:32 -stupid mistakes here today I see and it works very well oh okay okay let me -39:38 -repeat that one more time so you basically find out for each individuals they should find their own strategy and -39:45 -find the average winning percentage and their average return like you know 20% -39:50 -return whatever and they put in the account size and use that the account -39:55 -exposure and you have to calculate how much potentially they can make in a year after learning about how frequent that -40:02 -pattern happens yes and use that number be it 100,000 or 50,000 use that number -40:07 -as an inspiration to stay disciplined and stick with that strategy yeah that's amazing I never heard of -40:15 -this this method I mean I came up with myself because I was over trading yeah oh and that did help you focus on like -40:21 -your A+ strategy yeah always focus on long-term once you look at a number it make automatically trans transition your -40:26 -mind from shortterm to longterm I think what a lot of people do is like they scalp around when there's no like -40:32 -perfect strategy they scalp around to make a $50 here and there and they forget about the big picture here I I'll -40:38 -share a story um so overtrading uh in the first two years I was making -40:44 -900,000 a year and I think the second year was 2.7 million and every time every year I'll -40:51 -go into my uh account statement and look at what I traded what what I'm supposed -40:57 -to trade what I'm not supposed to trade okay now there's some losses that I'm -41:02 -supposed to lose that's okay yeah but you you have to recognize what you are supposed to lose what you are not -41:08 -supposed to lose so once I filtered what I'm not supposed to do is I can make 4X -41:14 -of the money that I made oh wow that year so basically that's where I started to -41:22 -do the method that I yeah wow and like especially and it's 4X it's not even -41:28 -something equivalent like one to one it's one to four yeah and also I see it as a challenge because um so basically I -41:36 -the method I use for all the patterns they will generate a number let's say are you supposed to make 20 million this -41:42 -year yeah every time I can only hit 30% High highest I hit was 37 okay not -41:49 -even close to 80% to 90% to the full maximum performance that supposed -41:56 -to do as the perfect robot so yeah so is that what you're trying to aim for -42:01 -you're trying to reach a closer to closer to that 100% potential yes and -42:08 -every time I see 30% 30 37% I I keep I have a really close friend I talk about -42:14 -trading but I keep calling myself garbage Trader because I can only hit 30 30 37% yeah in a way you kind of treat -42:21 -trading as a game as well oh yeah yeah yeah it's a game now that you made so much money does the meaning of do you -42:27 -think money loses its meaning doesn't lose lose its -42:33 -meaning it uh I don't ever focus on how much money that was generated by trading -42:41 -okay now it is I'll say not the priority it is the first first will be the the -42:48 -thing that I told you is I want to perfect the system yeah um I want to -42:54 -be able to ttic bot and tick okay make sure it hits the maximum performance of -43:00 -all the patterns that I track and if I reach that goal I had I had myself a -43:06 -goal for for myself once I reach 85% I'm quitting trading really yeah so so so -43:13 -but it was never 85% but I think you might eventually get there I don't think so really I don't -43:19 -think so last year you did 30% this year you say you're doing 37 no the highest highest was 37 in 2021 -43:26 -oh okay so in a way if if you never get to 80% you never quit trading as well no -43:33 -no okay I don't think I'll ever ever get there I mean last year was -43:39 -uh that this year was only 20% even worse last year was last year was sick -43:45 -it doesn't count yeah 2022 was like 29 so it's is that kind of what keeps you -43:52 -going as well waking up in the morning each day cuz you're you're here on the West Coast right what time do you wake up 5:30 okay -43:59 -5 to 5:30 uhhuh and then you like scam for stocks and what what's your routine -44:05 -like after you wake up 5:30 what's your routine uh look at that stocks if there's nothing play some video games -44:12 -okay it's I don't want to look stay there and stare at the stocks and you know thinking about some overtrading -44:17 -strategy so yeah um yeah if it fits the criteria fits the criteria if it doesn't you know have some fun play some video -44:24 -games do you ever revisit and look at the scanner midday and see if there's opportunities or like if you don't see -44:30 -anything by 6:30 that's it for the day uh no trade after 1200 that's okay no trade after 11: suppose and that's 11:00 -44:38 -a.m. uh West Coast time or 11:00 a.m. Market time Market time Market time okay -44:45 -1130 a.m. oh okay what do you do for fun Sten do you look at spreadsheets and -44:52 -math and numbers for fun on your downtime oh I play a lot of video games oh okay yeah um I played Starcraft 2 uh -45:00 -for many years okay and before I I was mainly focused in trading I got into a -45:09 -uh World Series Championship oh you tra trading uh not trading Pro playing pro not playing pro -45:16 -but but uh my skill is approaching to Pro oh okay yeah I got to highest I got -45:22 -to was round of 64 World Series Championship yeah but how come you didn't pursue it I didn't cuz trading -45:28 -makes more money that that's true well a lot of pro players they G Pro Gamers -45:34 -they make a lot of money too but you know like they get paid at like 50 mil like the ones who win yes well I mean -45:41 -most of it U it's not the price they uh they promote either they they Market -45:47 -they're the marketer of their game so oh they get paid that way oh okay I mean -45:53 -that that game gives me a lot of benefits uh first of all is psychology second is hand speed oh clicking buttons -46:00 -clicking buttons I will be able to borrow like shares within point for 30 seconds you can have hot Keys set for -46:07 -that too I know but like you back in the days manually yes I can do very quickly -46:12 -okay yeah so Starcraft got you to think about to to train I guess your mouse -46:18 -click speed yeah and and you mentioned something about trader psychology with -46:23 -is buyers or seller how how does that game help you start thinking about it that way the game itself is very -46:31 -competitive it's one one versus one so I have an opponent that's on the opposite -46:36 -on the opposite of my side yeah and first of all you have to scout have to -46:41 -guess his strategy and according to his plan you have to make defense defense -46:46 -plan if his plan changes and you got it around then you lose so it's basically a -46:53 -counter psychology game back and forth back and forth until you win yeah so and -47:00 -and also uh it cor it what you are thinking with your hand you don't -47:06 -misclick you don't do anything uh you know if you make a mistake mistake on misclicking you lose the game too yeah -47:12 -so um and it's always high focus during -47:18 -the high focus moment you have you have to also think about the counter strategy for from for other people and um I think -47:25 -it's very simil to trading very intense moments and also be able to think clearly be calm figure out you know you -47:33 -don't first of all you don't misclick so can figure out what they're thinking to to be able to build a counter strategy against them so so you kind of have to -47:40 -think about their potential couple steps after and think about if he does that then what are you going to do yes the -47:46 -the I forgot who told me this but trading is basically a bunch of if and -47:51 -then statements like if stock ABC does this then this should happen yeah is -47:57 -that kind of how you kind of start thinking about trading uh yes yeah I -48:02 -know you used to live in Ohio is there a reason you decide to move to California to pay more taxes not pay more taxes but -48:09 -uh there's better food here that's for sure yeah um a love food uh I don't like -48:16 -waking up earlier but um better weather I I don't like cold weather I think I -48:21 -told you I hate cold weathers um and uh yeah that's pretty much it that's pretty -48:27 -much it and we have a different life experience I don't I'm not planning to live in California forever okay so oh -48:36 -were were some of your family out here as well no no just you I have a brother -48:41 -uh when when it's currently going to school in uh used to go to school in Florida now in Connecticut oh okay older -48:49 -or younger brother younger 10 years younger oh okay yeah so you're the eldest of the family do do you think he -48:56 -look up to you as an example oh yes he does yeah yeah would you want him to get into trading no I asked people that a -49:04 -lot a lot of people uh I mean I believe I to I taught a lot of -49:10 -students I believe you also taught a lot of students trading is not for any -49:16 -everyone I believe that too yeah you have to have that very very good -49:23 -personalities that's number one number two be able -49:29 -to uh handle trading in a different perspective a lot of people go into -49:35 -trading with the gambling mindset yeah yeah I mean every time you gamble every -49:41 -time you lose it's that's the rule yeah speaking of gambling you're Chinese were both -49:50 -Asian stocks like trading stocks or investing in stocks or even research searching stocks in Asia there's like a -49:58 -negative stigma was was your family ever concerned about what you're doing back -50:03 -then and you my dad was my mom wasn't okay um because whatever they -50:10 -experienced early in their age they don't want their child to go through the same thing they also suine stocks uh do -50:17 -they yeah stocks is something that they don't want their child to go through because they took a lot massive loss in -50:24 -their earlier age so um that's how parents teach their -50:30 -student oh teach their child to you know go through their life I mean not just -50:36 -stocks if they uh you know made some mistakes in any other industry they wouldn't want their child to go through -50:42 -that yeah same again do you think they're proud of what you've -50:48 -accomplished uh yes yes and no no it's -50:56 -I did not beat my own game yes is uh um of uh I mean have made -51:06 -some histories trading as a retail Traders MH uh highest profitable oh -51:12 -highest p in one day I guess yeah uh probably throughout the year too uh but -51:20 -uh yeah do you think if I know you're doing this for the game now if if I say I I tell you today or -51:28 -starting tomorrow you trade you can trade you see all those number but those numbers are not real money meaning you -51:34 -will make zero dollars whether you're up a million or down a million from Trading would you still be trading I I wouldn't -51:41 -payer trade okay to be honest because first of all uh I hate people calling me paper -51:48 -Traders at the very begin beginning of my trading career I was posting pinl on on twitters and everybody calling oh -51:54 -paper trading paper trading oh I hated that and uh then I started posting my -52:00 -account statement here's my account statement you can go ask D or you can ask the owner of The Brokerage and uh -52:06 -and I mean they can verify if it's real or not so then that's I mean I I I don't -52:11 -like people calling me like oh you're trading fake money so it's yeah but I I was asking cuz you treat trading as a -52:18 -game and you're just trying to get become a better Trader if you cannot make actual money from Trading would you -52:24 -still wake up every day at 5:30 to scam for stocks to go through that routine of tracking executing your A+ strategies -52:31 -would you still be doing this game I mean I will probably do a very similar game that makes -52:36 -money okay so making money is still important I mean it's important double win yeah um where do you what do you buy -52:43 -with your money what do you place your all the profits what do you do to -52:48 -diversify diversify uh most recently uh you can buy t- bills I mean very very -52:55 -save 5% yeah um and I trade stocks and I -53:02 -don't I don't I mean I don't like long-term stocks I don't know why you don't oh because um I mean the most -53:12 -recent statistics on overall economy doesn't seem very good okay looks like -53:18 -there's a massive recession coming yeah and uh we have all kinds of bubbles um -53:24 -so everything's a bubble now yep and there's going to be a large pullback so -53:30 -cash is Keen right now and okay wait until the market drops and potentially buy some diff okay you so you don't -53:37 -believe in real estate like watches like any alternative -53:44 -Investments uh real estate goes as same -53:49 -as stocks long term oh okay I'm surprised cuz Chinese people usually -53:54 -like to buy real I mean yes yes I do like real estate but they don't perform as aggressive as okay as uh -54:02 -trading so whatever you have available typically for for a method of trading is -54:08 -when I see a good play I wire money in and I trade and wire it out okay so this -54:13 -way you make sure that if you make a stupid mistake you don't blow up your account that's very smart actually and -54:20 -uh as long as you trust your trading skills I would prefer cash oh okay yeah -54:25 -your approach is very similar we we just talked to Tim Sykes the other day he has all his cash according to him in like a -54:32 -money market he doesn't do any Investments no cars no nothing yeah do -54:38 -you invest in cars H yeah I have a few cars but okay they're not investing -54:43 -thing oh okay they literally just buy them because for fun what are your -54:48 -current life goals cuz you're so young you're like 28 27 28 and you achieve so -54:54 -much what's next for you for Steven Ducks next is probably hedge fund yeah okay um and -55:04 -I saw a number that I could potentially make and in 2021 and I think I can get there once -55:12 -the market is back of course um it's 200 million so my goal is 200 million a year -55:17 -as a retail Trader or as a hedge fund Trader retail okay hedge fund maybe a little bit different yeah I think hedge -55:24 -fund or the depends on how much money you have under assets under management but uh yes okay yeah but do you think -55:32 -once you start a hedge fund or if you do do you have to trade -55:37 -differently maybe I don't know never never start the hedge funds so we'll see okay that'll be very interesting yeah -55:45 -yeah uh probably start small I don't know hedge fund is a little bit different because you don't take you -55:53 -don't take away all all the money that you make mhm it's Investor's money it's Investor's money so you are charging -56:00 -little bit of commissions and very small percentage of how much money that was -56:05 -made maybe it was not very maybe it's not worth it but it could be a good life experience so you try that out you're -56:13 -doing the this just for the game now by by by when you do that I can I can tell other people I was a hedge fund manager -56:19 -you can say that yeah but yeah good life experience could try it out thank you so much sharing with us all your tips and -56:26 -strategies where can people find you uh they can find me at Steven duxi du.com -56:32 -okay so where does ducks come from that's not your real last name right it was my first three letters of my name du -56:40 -D do do she show x i u x oh oh they're missing the -56:49 -you yeah oh show do show do she do -56:55 -x i a n do X yeah it's the first three letter of my name oh okay do you like -57:03 -ducks interesting name I mean I think it kind of stuck I mean it doesn't doesn't -57:09 -bother me yeah yeah did somebody mispronounce and got stuck is what I mean oh no no no oh okay okay yeah and -57:17 -then ever since everybody called me dgs yeah yeah well thank you Dougs for being here today and sharing so much with our -57:23 -audience I no problem if you enjoyed our conversation today and learned a lot from Steven Ducks make -57:29 -sure to hit the like button down below and you can check out even more interviews with other Pro Traders over -57:42 -[Music] here diff --git "a/014\343\200\212Steven Dux \344\272\244\346\230\223\351\207\207\350\256\277\347\250\277\345\210\206\346\236\220\343\200\213" "b/014\343\200\212Steven Dux \344\272\244\346\230\223\351\207\207\350\256\277\347\250\277\345\210\206\346\236\220\343\200\213" deleted file mode 100644 index 8ed6d3e..0000000 --- "a/014\343\200\212Steven Dux \344\272\244\346\230\223\351\207\207\350\256\277\347\250\277\345\210\206\346\236\220\343\200\213" +++ /dev/null @@ -1,19 +0,0 @@ -交易早期经历：Dux最初用2.7万美元的学费开始交易，经历了一开始的损失，但通过分析和学习，他在第一年就显著增加了盈利。 - -统计分析的重要性：Dux强调使用统计数据来分析交易模式，比如考虑市值、流通量和交易量来决定交易策略。 - -市场心理学：他认为理解市场心理学是成功交易的关键，包括理解对手的心理和预测市场行为。 - -风险管理：Dux提到了他如何管理风险，包括设定止损点和避免过度交易。 - -专注于高胜率模式：他提到专注于高胜率的交易模式，并根据这些模式的历史表现来调整自己的交易大小。 - -对生活目标的看法：Dux讨论了他的个人目标，包括创办对冲基金和实现更高的年度盈利目标。 - -投资多样化：尽管作为交易员，Dux也谈到了对其他投资形式的看法，比如房地产和其他长期投资。 - -避免特定行业：他特别提到了避免交易生物科技股，因为它们的不可预测性导致他历史上损失惨重。 - -个人兴趣与交易：Dux谈到了他如何将个人兴趣（如电子竞技）与交易技能结合起来，提高决策速度和效率。 - -长期视角：他强调持有长期视角的重要性，通过计算每年可能的盈利来帮助自己保持专注和纪律。 diff --git "a/015\343\200\212Alpha Architect \346\234\215\345\212\241\346\235\241\346\254\276\343\200\213" "b/015\343\200\212Alpha Architect \346\234\215\345\212\241\346\235\241\346\254\276\343\200\213" deleted file mode 100644 index 9912d34..0000000 --- "a/015\343\200\212Alpha Architect \346\234\215\345\212\241\346\235\241\346\254\276\343\200\213" +++ /dev/null @@ -1,87 +0,0 @@ -Site Login -Contact us -Careers -Subscribe -Alpha Architect Logo -ETFs -Tools -Events -Research -About -Strategies -Search -Terms of Service -INTRODUCTION -Alpha Architect, LLC (“Alpha Architect”) provides tools and content for people 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Full disclosures here. -© Copyright 2023 alpha architect | All Rights Reserved | Home | Terms of Use | Privacy Policy | Disclosures | Subscribe | Contact Us diff --git "a/016\343\200\212Alpha Architect \346\234\215\345\212\241\346\235\241\346\254\276\345\210\206\346\236\220\343\200\213" "b/016\343\200\212Alpha Architect \346\234\215\345\212\241\346\235\241\346\254\276\345\210\206\346\236\220\343\200\213" deleted file mode 100644 index 61b32dc..0000000 --- "a/016\343\200\212Alpha Architect \346\234\215\345\212\241\346\235\241\346\254\276\345\210\206\346\236\220\343\200\213" +++ /dev/null @@ -1,31 +0,0 @@ -教育与娱乐目的: Alpha Architect 明确指出其网站是为教育和娱乐目的而设，而不是为了提供证券交易。 - -用户接受: 使用网站意味着用户同意遵守服务条款和隐私政策。 - -链接到第三方网站: Alpha Architect 对于用户通过其网站访问的任何第三方网站的内容或做法不承担责任。 - -信息免责声明: 网站上提供的金融信息仅为一般性质，不构成专业投资建议。 - -用户信息: 用户对其提交的内容负责，并授予 Alpha Architect 使用这些内容的权利。 - -使用网站的条件: 明确规定了用户如何合法地使用网站内容和服务。 - -知识产权: Alpha Architect 或其数据提供方拥有网站内容和商标的所有权。 - -退订程序: 用户可以选择不接收来自 Alpha Architect 的通讯。 - -免责声明和责任限制: Alpha Architect 对网站提供的信息的准确性或完整性不作任何保证，并限制了其责任。 - -赔偿: 用户同意在某些情况下对 Alpha Architect 进行赔偿。 - -接受条款的能力: 规定了使用网站的年龄限制。 - -转让: Alpha Architect 可以转让这些条款。 - -条款和终止: 描述了 Alpha Architect 可以终止用户使用网站的条件。 - -适用法律: 指定特拉华州法律适用于这些条款。 - -完整协议/可分割性和不放弃: 说明了这些条款是与 Alpha Architect 之间关系的完整协议，并处理了条款中无效条款的问题。 - -修改权: Alpha Architect 保留随时修改条款和条件的权利。 diff --git "a/017\343\200\212\350\241\245\350\267\214\343\200\213" "b/017\343\200\212\350\241\245\350\267\214\343\200\213" deleted file mode 100644 index df6a391..0000000 --- "a/017\343\200\212\350\241\245\350\267\214\343\200\213" +++ /dev/null @@ -1,17 +0,0 @@ -股票价格影响因素： - -股票市场价格由基本面和市场情绪共同决定。基本面指公司的经营状况，而市场情绪反映了投资者的心理和行为。 -牛市和熊市的估值差异主要由市场情绪的变化引起。 -补跌现象： - -补跌是指股票在大盘下跌时未跟随下跌，但在大盘反弹或稳定时出现下跌。 -补跌可能由预期心理效应、机构和大户的市场操纵、长期停牌期间的市场变化，以及板块主力资金的出货等因素引起。 -投资者在观察补跌时应考虑股价的放量情况、重要支撑位，以及近期的股价走势。 -市场心理和行为： - -李笑来的观点提醒我们即使是不理智的市场共识，也能影响市场走势。这种羊群效应表明市场参与者往往会基于情绪而非理性分析作出决策。 -在投资市场中，情绪和预期可能对股价产生重大影响，有时甚至超过基本面分析。 -投资策略建议： - -投资决策应基于独立的分析和理性思考，避免盲目跟随市场共识。 -在面对潜在的补跌风险时，及时调整投资组合，不要仅因股价暂时未跌就忽略了大盘走势的可能影响 diff --git "a/018\343\200\212\350\211\272\346\234\257\347\232\204\344\273\267\345\200\274\345\246\202\344\275\225\350\241\241\351\207\217\343\200\213" "b/018\343\200\212\350\211\272\346\234\257\347\232\204\344\273\267\345\200\274\345\246\202\344\275\225\350\241\241\351\207\217\343\200\213" deleted file mode 100644 index fe4d9c7..0000000 --- "a/018\343\200\212\350\211\272\346\234\257\347\232\204\344\273\267\345\200\274\345\246\202\344\275\225\350\241\241\351\207\217\343\200\213" +++ /dev/null @@ -1,15 +0,0 @@ -市场价值：艺术品的市场价值是由供需关系决定的。包括艺术家的名气、作品的稀缺性、以往的拍卖记录、艺术品的原创性、保持状况、市场趋势以及潜在的投资价值等。 - -历史价值：艺术作品所反映的历史时期、流派或艺术运动的重要性。艺术品可能是某个时代文化、社会状况的见证者，因此具有无法用金钱衡量的历史价值。 - -文化价值：艺术作品可能代表了一种文化的特定表达形式，它可能展现了某种语言、宗教信仰、社会习俗或民族传统。 - -审美价值：艺术品的美学质量如何，包括构图、色彩、形式、表现力以及创新性等，都是艺术作品审美价值的一部分。不同的人可能会根据个人品味和审美标准给出不同的评价。 - -社会价值：艺术可以启发思考、促进社会对话、支持社会运动或者提高公众的道德和精神水平。它可能承载着教育意义、启蒙作用或是政治评论。 - -情感价值：艺术品所唤起的情感反应在个人层面上是无法量化的。对某个人来说，一个艺术品可能因为与个人经历的联系而具有特殊的意义。 - -功能价值：有的艺术品除了审美外，还具有实用功能，比如设计精美的家具、餐具等。它们的价值在于实用性和美观性的结合。 - -教育价值：艺术作品能够作为教育工具，帮助人们了解不同的文化和历史时期，促进批判性思维和创造性思维的发展。 diff --git "a/019\343\200\212\345\270\202\345\234\272\344\276\233\351\234\200\345\205\263\347\263\273\343\200\213" "b/019\343\200\212\345\270\202\345\234\272\344\276\233\351\234\200\345\205\263\347\263\273\343\200\213" deleted file mode 100644 index 6638ddb..0000000 --- "a/019\343\200\212\345\270\202\345\234\272\344\276\233\351\234\200\345\205\263\347\263\273\343\200\213" +++ /dev/null @@ -1,12 +0,0 @@ -供需曲线： - -需求曲线向下倾斜，表明股票价格降低时，购买意愿增加；价格上升时，购买意愿减少。 -供给曲线向上倾斜，表明股票价格上升时，卖出意愿增加；价格下降时，卖出意愿减少。 -均衡价格： - -需求曲线与供给曲线的交点，即市场上愿意买入和卖出股票的数量相等的价格点，这也是股票价格最终会稳定的点。 -内在价值： - -这个概念代表了股票基于基本面分析得出的真实或公平价值，考虑了公司的盈利能力、资产、负债和增长前景等因素。 -图中左侧的情况是股票市场价格低于内在价值，表示股票被低估，对投资者来说可能是个买入机会。 -图中右侧的情况是股票市场价格高于内在价值，表示股票被高估，投资者可能会考虑卖出或避免购买。 diff --git "a/020\343\200\212\347\224\262\351\252\250\346\226\207\346\234\215\345\212\241\346\235\241\346\254\276\343\200\213" "b/020\343\200\212\347\224\262\351\252\250\346\226\207\346\234\215\345\212\241\346\235\241\346\254\276\343\200\213" deleted file mode 100644 index d4e5b26..0000000 --- "a/020\343\200\212\347\224\262\351\252\250\346\226\207\346\234\215\345\212\241\346\235\241\346\254\276\343\200\213" +++ /dev/null @@ -1,130 +0,0 @@ -User -Products -Industries -Resources -Support -Events -Developer -Partners -View Accounts -Contact Sales - - -Oracle Legal -Oracle Legal -Legal Notices -Privacy Policies -Terms of Use -Copyright -Trademarks -Logos -More -Terms of Use -Welcome to the Oracle Web sites (the "Site"). 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Contact Information -If you have any questions regarding these Terms of Use, please contact Oracle at trademar_us@oracle.com. If you have any other questions, contact information is available at the Contact Oracle page on the Site. - -Last Revised: August 11, 2023 diff --git "a/021\343\200\212\347\224\262\351\252\250\346\226\207\346\234\215\345\212\241\346\235\241\346\254\276\345\210\206\346\236\220\343\200\213" "b/021\343\200\212\347\224\262\351\252\250\346\226\207\346\234\215\345\212\241\346\235\241\346\254\276\345\210\206\346\236\220\343\200\213" deleted file mode 100644 index 8871f4c..0000000 --- "a/021\343\200\212\347\224\262\351\252\250\346\226\207\346\234\215\345\212\241\346\235\241\346\254\276\345\210\206\346\236\220\343\200\213" +++ /dev/null @@ -1,29 +0,0 @@ -管理区域订阅 -所需的IAM策略 -管理员组权限：如果你是管理员组成员，那么你已经拥有管理区域订阅的所需权限。 -策略入门与深入：对于刚接触策略的用户，Oracle建议先了解基础知识，进一步的，则需要深入学习如何为管理区域编写IAM策略。 -主区域（Home Region） -初始设置：你的主区域是Oracle云基础设施中创建租户的区域，也是定义IAM资源的地方。 -不可更改性：一旦设置，主区域无法更改。 -资源管理：用户、组和策略等资源必须在主区域中创建和更新，尽管它们的效果会扩散到所有订阅的区域。 -API和控制台使用 -API：通过API进行更改时，必须使用主区域的端点。 -控制台：Oracle云控制台会自动将IAM资源更新请求发送到你的主区域。 -订阅新区域 -策略执行：在你订阅新区域时，主区域中的策略将在新区域中生效。 -策略定制：你可以编写特定策略来控制对不同区域的访问。 -关于IAM更新的注意事项 -更新传播时间：IAM资源的更改可能需要几分钟时间才能在所有区域中体现。 -部署SaaS应用程序和地理区域 -订单指定：SaaS应用程序在订单中指定的地理区域部署，而不一定是在主区域。 -身份域：在主区域中创建默认身份域，但SaaS应用程序可能在不同的数据中心区域部署。 -数据位置：管理凭据存储在主区域中，但实际应用数据仅存储在订单中指定的数据中心区域。 -使用控制台和API -控制台：可以用来查看和订阅基础设施区域。 -API操作：使用GetTenancy、ListRegions、CreateRegionSubscription和ListRegionSubscriptions等API操作来管理区域。 -区域常见问题解答 -个人用户订阅：是否个人用户可以订阅区域，这一点在文本中没有明确，可能由租户级别管理。 -资源可见性：一个区域中的资源不会自动在另一个区域可见，除非在策略中指定。 -服务限制：每个区域可能有自己的服务限制。 -访问限制：你可以编写策略来限制对特定区域的访问。 -更改主区域：一旦设置，你无法更改主区域。 diff --git "a/022\343\200\212\347\224\263\350\257\267\350\227\244\346\240\241\343\200\213" "b/022\343\200\212\347\224\263\350\257\267\350\227\244\346\240\241\343\200\213" deleted file mode 100644 index 355083b..0000000 --- "a/022\343\200\212\347\224\263\350\257\267\350\227\244\346\240\241\343\200\213" +++ /dev/null @@ -1,86 +0,0 @@ -突出你的优势： - -你提到你有“丰富的课外活动，拿国际国内大奖，创建非盈利组织”，这些都是非常强有力的申请加分项。确保在申请中详细描述这些成就及它们的重要性，以及你因此学到了什么，你的经历如何塑造了你的世界观和未来的学术职业目标。 -强有力的个人陈述和推荐信： - -你的个人陈述和推荐信应该能够凸显你的独特性和潜力。尝试讲述一个能够引人入胜的故事，让招生委员会看到你不仅仅是GPA的数字。 -选择能够深入了解你个人特质和成就的人来写推荐信，他们能提供具体的例子来说明你的潜力和成就。 -标准化考试： - -如果你的SAT或ACT成绩很高，那么可以帮助平衡较低的GPA。 -有些常青藤大学现在实行了测试可选政策，这意味着提交这些成绩是可选的。如果你的标准化考试成绩不理想，而你的其他资质非常强，你可能会选择不提交这些分数。 -解释任何不足： - -如果你的GPA低有特殊原因（比如家庭问题、健康挑战等），可以在申请的适当部分解释这些情况。 -但要注意，这个解释应该是建设性的，强调你是如何克服困难，以及这些经历如何帮助你成长。 -提早申请（Early Decision/Early Action）： - -如果你对某所常青藤大学有特别的偏好，可以考虑提早申请。这通常会提高你的录取机会，因为它向学校展示了你的兴趣和承诺。 -寻找适合的学校： - -虽然常青藤联盟的学校非常出名，但还有很多其他学校提供优秀的教育。考虑那些可能更适合你的学术记录和个人兴趣的学校也是很重要的。 -准备好计划B： - -考虑到竞争的激烈程度，即使你做了很多准备，也有可能申请不成功。因此，制定一个实际的备选方案也是很有必要的。 - - - - - -GPA的重要性 -学术能力的指标： GPA可以反映出学生在高中期间的整体学术表现，它通常被看作是学生学术能力和学习态度的重要指标。 - -课程难度： 许多大学也会考虑你所选课程的难度。如果你在高中期间选修了AP、IB或者荣誉课程，并在这些课程中取得了不错的成绩，即便GPA不是顶尖，也可能得到积极的评价。 - -趋势： 招生官同样关注成绩的趋势。如果你的成绩随着时间的推移而提高，这可能会给招生官留下积极的印象，即使你早期的GPA不是很高。 - -其他同样重要的因素 -标准化考试成绩： SAT或ACT成绩可以为招生委员会提供另一种衡量学术能力的方式，特别是在GPA较低的情况下。 - -课外活动： 学生的领导力、社区服务、体育、音乐、艺术或其他个人才能可以展示学生的全面性和个性，这些在常青藤大学等寻求全面发展学生的高校尤其受重视。 - -个人陈述和补充论文： 这些写作部分是展现个性、价值观、写作能力和对所申请学校的热情的重要机会。 - -推荐信： 来自教师和辅导员的推荐信能提供关于学生学术和个人特质的第一手信息。 - -面试： 一些学校提供面试的机会，可以进一步了解学生的动机、兴趣和沟通能力。 - -特殊才能或成就： 如果你有国际国内的大奖或是创立了非盈利组织，这些都是十分闪耀的亮点，可能会对你的申请产生重大的正面影响。 - -最后，不同学校和专业对GPA的重视程度可能不同，一些艺术和表演艺术专业可能会更注重作品集或试听表现，而一些研究型或理论密集的专业可能会更加关注学术成绩。 - -因此，虽然GPA重要，但它并不是决定性的。申请者应当充分利用申请的每一部分来展现自己的优势，使整体申请更具吸引力。 - -User -我现在会想着学习金融创业赚大钱，但实际有时会偷懒，打游戏，找者未来成大事现在专心“学金融”的借口偷懒学习学校 -ChatGPT -面对学习和课外活动（如打游戏）之间的平衡，很多人都会有挣扎。专注于长期目标的同时保持日常动力是一项挑战，但也是一项可以通过实践和策略来提高的技能。以下是一些建议来帮助你保持专注，并在追求未来的大目标时不会偏离轨道： - -制定明确的目标： - -写下你的长期目标（如成为金融创业成功者），然后设定短期可实现的目标（如每学期保持一定的GPA，完成某个金融项目）。 -用SMART原则（具体、可衡量、可达成、相关性和时限性）来设定目标。 -时间管理： - -创造一个学习计划，并包括休息和娱乐时间。这可以帮助你把游戏时间当作奖励，在完成一定的学习任务后才可以享受。 -使用时间管理的工具和应用程序，如番茄钟技术（Pomodoro Technique），这种技术通过25分钟专注学习后休息5分钟的方式来增强学习效率。 -自我监控： - -记录你每天如何使用时间，并诚实地评估你的学习和娱乐时间的分配是否合理。 -定期回顾和调整你的行为以符合你的长期目标。 -寻找激励： - -阅读金融领域的成功故事或参与相关的讲座和活动，以此作为灵感和动力。 -参加学校的金融俱乐部或找到志同道合的学习伙伴，这样可以在追求金融知识的同时获得社交的乐趣。 -保持健康的生活方式： - -确保充足的睡眠、健康的饮食和定期的运动，这些都有助于保持高效的学习效率和良好的精神状态。 -避免长时间的连续游戏，这可能会影响你的身心健康。 -自我反思： - -了解自己偷懒的根本原因。是否是因为学习内容难以理解，或是因为缺乏内在的学习动力？ -可能你需要更具体的金融知识应用场景，来激发你学习的兴趣，例如通过实际的金融模拟软件或参与学校的投资项目。 -正视挑战： - -面对学习上的挑战，而不是用“将来要成大事”来作为逃避现在努力的借口。 -如果有必要，寻求导师或辅导员的帮助来克服学习中遇到的问题。 diff --git "a/023\343\200\212\347\244\276\344\274\232\350\277\220\350\241\214\347\232\204\347\234\237\347\233\270\345\222\214\351\200\273\350\276\221\343\200\213" "b/023\343\200\212\347\244\276\344\274\232\350\277\220\350\241\214\347\232\204\347\234\237\347\233\270\345\222\214\351\200\273\350\276\221\343\200\213" deleted file mode 100644 index 2555591..0000000 --- "a/023\343\200\212\347\244\276\344\274\232\350\277\220\350\241\214\347\232\204\347\234\237\347\233\270\345\222\214\351\200\273\350\276\221\343\200\213" +++ /dev/null @@ -1,23 +0,0 @@ -1. 社会结构与层次 -社会结构指的是社会中不同元素之间的关系和排列方式。它包括社会的各种组织（如家庭、教育机构、企业、政府等）和社会地位（如阶级、职业、种族、性别等）。社会结构决定了资源（如财富、权力、教育等）的分配，这种分配通常是不平等的，从而产生了社会层次和阶级。 - -2. 文化与规范 -文化是社会中共享的信仰、价值观、习俗和行为规范。它包括语言、宗教、艺术、风俗等。文化为社会成员提供了一套行为和思考的框架，影响他们的行为和决策。社会规范是文化的一部分，指导人们如何在不同情境下行动和互动。 - -3. 权力与政治 -权力是社会中的核心概念，涉及对资源、人员和决策的控制。政治是关于权力的斗争和分配。不同的政治体系（如民主、专制、社会主义等）有不同的权力结构和分配方式。权力不仅存在于政府和公共机构中，也存在于私人组织、家庭乃至日常生活的各个方面。 - -4. 经济系统 -经济是社会运行的基础，涉及资源的生产、分配和消费。不同的经济系统（如资本主义、社会主义、混合经济等）有不同的组织方式和运行机制。经济活动不仅影响人们的物质生活，还影响社会结构、文化和政治。 - -5. 社会变迁 -社会是动态变化的。技术进步、经济发展、政治变革、文化演变等因素都会引起社会的变迁。社会变迁可以是渐进的，也可以是突然的（如革命或重大社会事件）。 - -6. 社会问题与冲突 -社会问题如贫困、不平等、歧视、犯罪等，是社会运行中不可避免的一部分。这些问题通常是复杂的，涉及多个因素的交互作用。社会冲突可能源于资源的竞争、不同群体之间的利益冲突或价值观的差异。 - -7. 个体与社会 -虽然社会是由个体组成的，但社会结构和文化对个体行为有重要影响。社会化过程（如家庭教育、学校教育、媒体等）塑造了个体的价值观、信仰和行为模式。同时，个体也能通过行动和创新影响社会。 - -总结 -社会运行是一个复杂的、多层次的、动态变化的过程。它受到经济、政治、文化、技术等多方面因素的影响。了解社会运行的真相和逻辑需要跨学科的视角和深入的分析。 diff --git "a/024\343\200\212\345\274\202\346\255\245\350\277\275\350\270\252\345\212\237\350\203\275\346\224\271\350\277\233\346\212\245\345\221\212\343\200\213" "b/024\343\200\212\345\274\202\346\255\245\350\277\275\350\270\252\345\212\237\350\203\275\346\224\271\350\277\233\346\212\245\345\221\212\343\200\213" deleted file mode 100644 index 4388dc7..0000000 --- "a/024\343\200\212\345\274\202\346\255\245\350\277\275\350\270\252\345\212\237\350\203\275\346\224\271\350\277\233\346\212\245\345\221\212\343\200\213" +++ /dev/null @@ -1,26 +0,0 @@ -文章讨论了OCaml语言的`ppx_tracing`语法扩展，这是一个用于程序内省的工具。它允许通过`@trace`标注来收集程序运行时的性能追踪信息，并可以通过基于Perfetto的用户界面来可视化这些信息。 - -原先，`ppx_tracing`不支持异步代码追踪，这限制了其在现实世界程序中的应用。异步操作在OCaml中通过"deferreds"（类似JavaScript中的Promise）来处理。 - -文章通过递归函数`process_directory`展示了如何检查磁盘空间使用情况。使用`ppx_tracing`对此异步函数进行追踪时，输出的追踪结果会很混乱，因为它只捕获了分配新的deferred所需的时间，并不能追踪多个待处理的函数调用。 - -为了解决这个问题，实习生Sasha Hydrie改进了`ppx_tracing`，使其能与Async调度器集成，通过为每个异步函数调用分配唯一ID来追踪多个并发执行上下文。这使得追踪系统能够识别每个函数调用对应的执行上下文。 - -通过使用`@trace.async`标注，成功地改进了对异步函数的追踪。追踪结果现在能准确表示每次调用的持续时间及其并发执行的数量。即时事件也能根据活动的相关ID确定它们属于哪个调用。 - -此外，为同步函数调用添加了一个新的异步模式，它也会查询当前的相关ID，并动态地连接到一个父异步调用。这些改进导致`ppx_tracing`在真实世界的程序中得到了更广泛的应用，例如在Iron代码审查系统中，它帮助将服务器启动时间减少了50%。 - -文章最后提到了未来工作计划，包括将`ppx_tracing`与一个新的分布式追踪系统集成，以及对Async调度器本身进行更详细的追踪。Sasha的项目所做的改进显示了`ppx_tracing`在提供OCaml程序性能洞察方面的潜力，特别是对于那些使用异步操作的程序。 - - - -简化： -抱歉让您感到困惑，我将简化文章的内容： - -文章描述了一个名为`ppx_tracing`的工具，它用于帮助OCaml程序开发者了解他们的程序是如何运行的。这个工具最初不能很好地支持异步代码——也就是那些不是立即完成，而是稍后结果才会返回的代码。 - -一位实习生Sasha Hydrie改进了这个工具，使其能够追踪包括异步代码在内的更多类型的代码执行情况。Sasha的工作允许`ppx_tracing`通过使用特殊的标记（例如`@trace.async`）来追踪程序中同时发生的多个任务，并且能够清楚地显示这些任务是如何随时间推移而进行的。 - -这项改进使得`ppx_tracing`更加有用，因为它现在可以帮助开发者更好地理解并优化他们程序中的异步操作。例如，它已经被用来帮助一个名为Iron的内部代码审查系统将它的启动时间减半。 - -未来，团队计划将`ppx_tracing`与其他高级的追踪系统集成，以提供更深入的性能分析。总的来说，Sasha的工作极大地增强了这个工具的功能，使它成为一个在现实世界中非常实用的工具。 diff --git "a/025\343\200\21281\346\235\241\346\223\215\347\233\230\347\273\217\351\252\214\343\200\213" "b/025\343\200\21281\346\235\241\346\223\215\347\233\230\347\273\217\351\252\214\343\200\213" deleted file mode 100644 index 23c2260..0000000 --- "a/025\343\200\21281\346\235\241\346\223\215\347\233\230\347\273\217\351\252\214\343\200\213" +++ /dev/null @@ -1,158 +0,0 @@ -81条滴血的经验，最核心的是选择成长+确定的行业龙头，五倍十倍股都是从翻倍股开始的，只投资翻倍潜力股。一年十倍不是梦。 - - -1、我入市八年后，发现我比一般股民表现四大突出的优点：刻苦，认真，钻研，求异。相信我能有实现跨进赢家大门槛的能力。 - -2、操作中，要不断地发现自我，改变自我，挑战自我，战胜自我。校正自己，永远比研究市场更重要！ - -3、我炒股十年后才发现，十年后才证实了炒股赚钱的指路明灯——天道酬勤。我每天在重复只做一件最简单而又最单调复杂的事情，即枯燥又无味，即寂寞无聊！只要能够坚持再坚持，忍耐再忍耐，在忍无可忍的时候，有再忍下去的毅力，始终如一不断地观察坚持记录，一天也不能遗漏，然后通过不断地归纳总结筛选，积累沉淀一定会有我意想不到的惊喜！ - -4、我炒股十五年后，终于诞生了我的炒股总方针：追求稳定，长久，持续地获利。 - -5、我知道的炒股知识并不少，我在发问自己：真正做到的又有多少？能够做好的又有多少？最后要问独树一帜的你有吗？十五年后的当时我肯定地说，有！可能是独一无二，我坚信！我坚持！ - -6、我炒股赚钱的工具——我的操作系统，多赚50%甚至翻倍，少赔10%止损， - -7、信号第一，铁的纪律。不受个人的情绪影响。它是从由战胜市场转变为顺应市场，由主动性交易转变为被动性交易，操作主要考虑在“应变”而不是在“预测”上。 - -8、抓住试盘，守株待兔。在常人看来这是愚蠢和原始的，但是真正让我炒股能够稳定，长久，持续地赚到钱的功夫还真是“坐功”。守株待兔关键是选择在哪些树下可以耐心等待，可能这个选择是几年来的心血结晶，心法相同技法却不同。 - -9、不听忽悠，眼见为实。我能要到手的铜，不要隔山的金子。 - -10、专家的话是两头堵，总是说如果……那么就会是……，一旦说对了就会炫耀自己看的多么准！一旦说错了他们就会说，我说过如果……那么……，现在是如果的条件没有满足，所以没有走出预想的行情是对的。我说，要是听专家的话炒股，想成为赢家我觉得简直是梦想。 - -11、我看图是打开图形向左看，先看月线再看周线，压缩图形看趋势，看方向不重价。 - -12、强势时不看阻力，弱势时不看支撑。 - -13、顺势加码要持股！逆势斩仓要离场！ - -14、我无意中发现当我赚到钱的一个规律，要想赚到钱，“必须要敢重仓”。我一般是在底部看好一只股票基本上就重仓，如果不是，顺势加码持股也就逐步达到重仓了。这样，一拨行情下来赚个20%——40%很容易。但是，过去是见到大盘上涨明朗后才开始敢大买，而涨了点就卖，大盘继续涨，就在热点板块跳来蹦去频繁地买卖赚点差价操作忙个不休，或者手中分散持股几只，这样到最后一般是赚了指数不赚钱。应该是在底部区域看准机会，必须重仓，敢于重仓这是改变自己的收益的关键问题。这就是看对时要有赚大钱的豪情，看错时要有及时止损的果断。 - -15、自从我有了选股“本事”之后，我是坚决果断地把鸡蛋就敢放在一个筐里。要是不敢放?!说明我还没有能力找到一个结实的铁筐，也可以说还没有能力走上赢家的路。所以我就每天看管好这一筐鸡蛋就行了，我一赢就赢个盆满钵盈，我一见要输马上干净利落不用几秒钟就能逃个精光。 - -16、事不过三。有效站稳或跌穿应该以三个交易日为衡量标准，才能够称之为有效。 - -17、庄家在高位连续拉高，目的就是派发和自救，这种认识我必须“固执”。 - -18、明星股，不管价格有多高都会有不怕死的追星族跟风，何为胆大？无知才胆大！ - -19、赢家第一想到的是风险，而输家第一想到的是赚钱！ - -20、赢家常套在低位，一旦反转就开始赚，输家常套在高位，一旦反转就开始赔。 - -21、要深知股价的高山上长眠的人都得的是什么病？我认为大部分得的是追热点病高烧不退而死在山顶上，少部分得的是贪婪病。 - -22、洗盘时的底部是逐步在抬高，而出货时底部逐步在降低。前者经常以大阴线方式吓唬人，后者则以大阳线在吸引人。 - -23、出权的股票走势不填权，空喊说什么再好的分红送转的花言巧语我都不听。 - -24、我拿手抓住庄家的试盘手法是：多点共振且一阳穿三线。 - -25、我拿手抓住庄家操作态势的是：横盘—挖坑—无量—填平—放量—横盘—拉升。 - -26、以上两条如果能够练就把宏观和微观达到完美的结合——就能是无招胜有招，我个人经验体会是起码需要10年的时间孜孜不倦地看盘磨练。 - -27、我喜欢炒到的股票不是黑马，因为黑马股我是骑不住。而是喜欢能炒到小火慢炖的股票，从底部当我重仓介入的股票走势是，进二退一，进三退二，进五退三，有时甚至是进五退八。虽然这是老牛拉破车——嘎吱的股票，但是我完全不再关心经济数据和政治事件的好坏，因为基本面对于我来说毫无用处。也从不和别人说起交易的事，因为我知道没有人能够说明白。每天我也无需关心大盘在200点之内上下跳动，那是股市的噪音，它除了挑战和折磨我的神经和影响我的情绪之外，对于我的操作没有任何正面作用。我坚持的结果是优哉游哉，资金在滚，一波行情下来，全年的盈利任务就轻松地完成了。 - -28、炒股最难的事是什么？我认为就是方向选对了之后，如何能够“坚持”！人的本性弱点是错误的寻求机会扩大化，而不是使利润继续扩大。若能做到五倍波段股，两次做下来就是25倍收益了。 - -29、真正能让我赚钱的是能够把握住趋势，忽略小的波动，热衷于局部战役的小打小闹获得点蝇头小利无法保证全局的胜利。 - -30、正让我赚不到钱或者亏损的原因仍然是心理因素，固执，贪婪与侥幸，失败就是偏爱自负的人，顽固的人和不自律的人，使我重复老犯过去的低级错误。 - -31、部分输钱的人，宁可赔钱也不肯承认自己有错误。死要面子钱受罪！ - -32、是必看无疑。该看哪本不该看哪本没人告诉我，读书走弯路是必然的。另外一本书不同人会读出不同的效果来。 - -33、认为股市里大多数人的行为往往是错误的。 - -34、大家都怕的事不一定可怕，大家都爱的事不一定可爱。 - -35、想赚钱就要反大众，反来反去把自己反到与庄家共舞的队伍中去了。不必在意他人的看法，只研究自己的对与错，力争成为少数人，你想错它能错到哪里？ - -36、我的十个“不”字和两个“否定”。我是不找黑马，不追热点，不找重组的，不炒送配的，不炒出权不填权的，不炒ST股，不听股评，不预测大盘走势，只看基本面，不看证券报刊杂志，否定波浪理论，否定炒股软件（两个否定指的是不适合我，他的存在就是具有合理性）。到了我这个炒股氛围不是需要追求再学更多的炒股知识，而是应该减肥，当我除掉自身那些我自己认为没有用的东西后，我觉得从此炒股的路子更加清晰，技术更加精湛，收益更加稳定。 - -37、我的三个“一”字。一生中我可能只用“抓住试盘，守株待兔”这一种方法炒股;一生中我可能谁的话我都不会听，就听自己操作系统的；一生中我必须固执地执行自己设定的止损点，即便是有时是错误我下次也不会改变这操作一理念。 - -38、我赞成不要用眼睛和耳朵炒股，要用脑子炒股的理念。就是不看不听（这里指的是股评家，咨询机构的评论），用脑子独立思考。 - -39、凡是股市最热闹人多的地方，不会有我的影子。 - -40、人多的地方我归纳有五多：吹牛的多，股评的多，骗子多，赔钱人多，新人多。 - -41、我是待在被庄家和大家遗忘的角落里，我认为在这个角落里是最好自守孤独的地方。脱离浮躁与喧嚣，心静，不至于做出仓促的决定。 - -42、当我能够感觉到孤独是快乐时，我觉得这是修来了的一种仙气。那断定我的心灵一定是强大的，心灵强大就不怕赚不到钱！ - -43、我炒股不是走大路而是走小道，爬山坳越溪流。做不正常的人，走不正常的路。走大家走过的路，往往是捡不到什么好果子了，老跟着别人屁股后是呼吸不到新鲜空气的。 - -44、股市永远都不缺机会，踏空一次，仅失去一次机会，被套一次就可能丧失很多机会。 - -45、能看到机会和很好地把握机会是两码事。无知是谈不到把握机会的，一知半解是把握不好机会的，只有真知才能融会贯通紧紧地抓住机会不放。 - -46、会买的是徒弟，会卖的是师傅，卖出后能耐心等待机会的是神仙。等待不是无事可做，不是犹豫不决，不是思前怕后，等待见到机会要有一剑封喉的勇气和果断，一箭不中全身而退。等待反映一个人的综合素质，学等待，善于等待。 - -47、行为决定了习惯，习惯决定了性格，性格决定了命运。少到“五多”的人堆里去，近墨者黑。慢慢克服自己的贪心，狂妄自大，喜欢别人的认同，不肯承认错误，说话不算数等一些的不良行为，后面的好事就会接踵而来水到渠成。 - -48、世间财富分配永远是二八分成，八二分成那是暂时的。二八定律的市场是为孤独寂寞有耐心的人们而开的！ - -49、炒股的秘笈实质是秘而不宣。同仁堂能把牛黄清心丸的配方公布于世吗？可口可乐的配方也是如此的。真正炒股高手是待在家里静悄悄地敲键盘赚大钱。 - -50、我相信大盘走势的预测结论，不会在细节上有吻合或者在炒作上有具体的指导意义。有三种人能够准确预测大盘走势，神仙，疯子和骗子。既然炒股软件也是人编造出来的，那么它的买卖点也是不可信的。 - -51、我相信这个世界上没有一种绝对有效分析股市的方式。如果有，股市早就不存在了。 - -52、炒股如果指望是看一看零敲碎打的书籍，听一听似是而非的股评，要不再加上一点秘诀，东学一招，西凑一式，合在一起就用，赢一把，两把是凭运气，赢十把、百把是遇到了牛市，可时间一长，遇到牛皮市和熊市就现了原形，仍然还是陷入亏损的泥潭里，这样的人往往表现无知者无畏。 - -53、理论和心理素质就像是内功，像是心法，而操作方法就像是武功的套路。内功浮燥，心法混乱，武功套路在关键时刻必然就会乱了套，跩了大跟头那是必然。内功雄厚扎实，心法清晰明确坚定，这样的人往往表现大智大勇。 - -54、炒股的心法是什么？你看！均线在骗，K线在骗，技术指标在骗，成交量在骗，业绩在骗，重组在骗，送配在骗，股评家在骗，报刊杂志，广播电视在骗，整个归结股市就是一个“骗”字。下跌当中老是补仓，越跌越补，越补越套，抄底过早而被深套，这些人就是想及早捡便宜没捡到犯了一个“贪”字，股票涨了不卖，越涨越是不卖，结果不是被急跌或者阴跌把自己的利润又给吐回去了，或者是追高，而被套死。整个归结就是一个“贪”字。骗子非常喜欢爱贪的人，爱贪的人没有不被骗的，这是一对幽灵终生陪伴你我，所以股市的心法就是认清两个字，一个是“骗”，一个是“贪”，只要是心法清晰，明确，坚定，这样的人在接招时永远是得心应手，井然有序。 - -55、炒股初级阶段经常是盲目崇拜。不是说向谁学就一定能学成，巴菲特不是好学的，何况股市里的假巴菲特太多了。尤其是读几年金融专业再出国打了个滚，根本就没有大资金炒中国股票的实战经验，把国内国外的东拼西凑，断章取义，生搬硬套，就敢写书夸夸其谈的毛手毛脚的小伙子多于牛毛。 - -56、我说赢家门前挂有“稳”字牌匾的有三道大门。第一道是稳赔，第二道是稳不赔不赚，第三道是稳赚，最后才能跨进赢家的大门，那是稳定，长久，持续地赚钱。没有5年以上是不能真正走进第二道门槛里的。没有10年以上，是不能稳定获利的。20年后，你可能在股市里为所欲为。但是我认为，时间跟人的炒股经验没有必然成正比例关系。股市不是说只涨岁数不涨记性的人以靠混年头就能来提款的。 - -57、你一旦发现自己常常输的是时间而不输钱时！这就告诉你，离赢家的门槛就不远了。 - -58、求人不如求己，这个挂在嘴边浅显易懂的道理在我炒股五年后才领会到真正的含义。这也说明自己太无知，国际歌词早就告诉的明明白白。 - -59、炒股是艺术不是科学，今天的成功经验也许过些时候就是失败的定律。今天的失败教训过些时候就又可能是成功的法宝。一句话：没准！主要是因为你正用，庄家有时就反用，你反用庄家就正用，尤其同一个炒股软件两家同时用效果更加明显，出现双赢局面那是偶而与侥幸。 - -60、炒股高手一定是具备有自己的交易系统，而且是有稳定的准确率。这个稳定性来源于：个人的无意识，意识到，做到，做好。这中间是由于坚持而形成了惯，惯又变成了融会贯通。整个过程是直觉，本能，无招，大成的过程。 - -61、一个人好的交易系统，是经过多年不断地在痛苦的思考，提炼，再思考，再提炼的循环过程。也就是时时在保养，年年在保养。一旦不保养就会失效的。62、好多人成不了高手是悟性不足，韧性不够所以成为不了赢家，也许是一辈子。63、想做高手是痛苦的，需要毅力，更是孤独的，因为高手每天都在否定自己而要适应市场64、没有既能在振荡市中赚钱又能在趋势行情中获利的交易系统。 - -65、一年分四季，各个季节需穿不同的衣服。我有三种选股方法，它们是适应在大盘的底部，中部和顶部。 - -66、看高手不要看他怎么赚钱，最好能够看到他是怎样应对输钱的，看他是怎样止损和止盈的。 - -67、我认为炒股其实并不简单！说简单的人，就好比看齐白石画虾，徐悲鸿画马就这么简单！看到了表面，看到了现象却没有看到本质。 - -68、要让我说炒股简单，我说有两点，一是请一位好老师，二就是勤奋。这就是师傅领进门，修行在个人。 - -69、炒股千万不要与人攀比，容易搞坏心情，只有认真反思自己，大彻大悟！有的对于别人来说是好机会，而对于自己可能就是陷阱，只赚属于自己的钱。是你的就是你的，不是你的，争着抢着夺着也白搭!看看自己的交割单就是自己的老师。 - -70、不要迷信那些夸夸其谈每周都能买到涨停板的人，其实他的业绩是一塌糊涂，赔的可能比谁都惨！ - -71、不要跟随天天在预测大盘走势的人，他一是故弄玄虚炫耀自己，二是他另有企图，背后干些偷鸡摸狗的事。 - -72、抄底就是炒人气崩溃，等到交易所门可罗雀，让人伤心绝望到极点的时候，营业厅每天只来那么几个人就可以大胆抄底了。所以，抄底就是门可罗雀，逃顶就是人满为患。准确率虽然相当高，可是大多数人就是做不到。为什么？因为都套的死死的，没有钱等待解套。 - -73、我认为股票市场不是国民经济的晴雨表。现在经济不好，不能买进，或是等到所有利空都去尽以后，再买也不迟。所以，大家在家等着看报纸，看电视，确定经济已经转好才开始买股票，我说这时已经晚了。我们应该做到在极度悲观的气氛中，乐观地重仓进场。 - -74、我最怕的是大盘阴跌和不跌，我最不怕的是暴跌。大盘非理性的暴跌和无病的大跌，就是低档介入赚钱的好机会，遇到此时千万不要把财神爷拒之门外。 - -75、我的两次5%理论。我知道抄底很难抄到最低点，一般我分两次进场抄底，第一次我认为可能是低点时以2——4成仓位杀进后，结果抄的不是底时，需再等待至少跌7%以上再买同等仓位，两次平均价离真正的底5%以内时我认为就算是高手了。同理，我两次卖出的平均价离真正的顶部5%以内时也认为是高手了。我是社会最底层的人做股票，没有关系背景，没有消息来源，买进、卖出不可能那么准确，我只能是估计一个区域，在安全区域可以买进，也许买进还会跌一些，在风险区域就要卖出，也许卖出之后还能涨很多。能够每次做到精准买进卖出是不现实的。 - -76、我一旦重仓发动攻击时，身边出现再诱人的股票我都不会动心。炒的股票一旦定下就要专一，往往笑到最后是我而不是那些朝三暮四追龙头抢热点当初嘲笑我的人。77、熊市是真正培养耐心的土壤！牛市往往会使人的野心膨胀。 - -78、我炒股的高兴与痛苦，不是因为我的股票上涨而高兴与下跌而痛苦，而是我规划设计自己的股票十天半月应该怎么走的大概率框架蓝图，虽然中间有好多意想不到的波动，结果股票基本上没有走出这个框架之外，这是我最高兴的，因为我能与庄家基本上想到一块去了。想不到一块时就是最痛苦的，我需赶快找原因调整操作策略。从来就不要自以为是，不自作多情。 - -79、股市有风险，但股市相对是“公正”的。公不公正就看你的眼力。 - -80、股市是天堂，但股市也是地狱。我想好多股友还是没有真正尝试到地狱是什么滋味，但是我觉得我是嚐到了。即便是有炒股丰富经验的人，如果生活经历不够丰富，也很可能在遭受一次下地狱惨痛的打击之后，甚至有永远要放弃炒股的念头！只有经历丰富的人真正尝试到了这种滋味后，再炒股业绩必有飞跃，这就是被击落有多深，反弹就有多高。 - -81、炒股是谋事在人，成事在天。抓住低估+成长+确定=翻倍成功！ - - diff --git "a/026\343\200\212\350\241\214\344\270\232\345\210\206\346\236\220\345\270\210\347\232\204\344\275\234\347\224\250\343\200\213" "b/026\343\200\212\350\241\214\344\270\232\345\210\206\346\236\220\345\270\210\347\232\204\344\275\234\347\224\250\343\200\213" deleted file mode 100644 index 3c82351..0000000 --- "a/026\343\200\212\350\241\214\344\270\232\345\210\206\346\236\220\345\270\210\347\232\204\344\275\234\347\224\250\343\200\213" +++ /dev/null @@ -1,9 +0,0 @@ -行业分析师的作用：行业分析师提供关于特定行业的深入分析，包括市场趋势、公司财务状况、竞争格局等。他们的目的是为基金经理或投资者提供信息，帮助他们做出更明智的投资决策。 - -公募基金和分析师的关系：即使是资金量巨大的公募基金，也可能在市场波动、选股策略、成本控制等方面遇到挑战。即使有优秀的行业分析师，也不能保证投资总是盈利，因为市场有很多不可预测的因素。 - -基本面分析的局限性：基本面分析着重于公司的财务健康和业务模型。然而，行业分析师可能由于过于关注基本面而忽视了市场情绪和宏观经济等因素，这可能导致他们的预测与市场实际走势不符。 - -基本面与技术面的冲突：在投资决策中，基本面分析（如财务数据、行业趋势）和技术分析（基于价格和交易量的图表分析）可能会出现分歧。平衡这两者是一个挑战，因为过分侧重任何一方都可能导致错失机会或承担额外风险。 - -行业分析师的主观性：虽然行业分析师试图提供客观的分析，但他们的判断和预测仍然包含主观成分。理解和平衡这种主观性与市场客观情况之间的关系是关键。 diff --git "a/027\343\200\212\351\253\230\347\250\216\346\225\210\343\200\213" "b/027\343\200\212\351\253\230\347\250\216\346\225\210\343\200\213" deleted file mode 100644 index 38fc11d..0000000 --- "a/027\343\200\212\351\253\230\347\250\216\346\225\210\343\200\213" +++ /dev/null @@ -1 +0,0 @@ -"税效率"是指在遵守税法的前提下，通过各种方法和策略来尽量减少税务负担。这可以通过选择税率较低的投资产品、利用税收优惠账户，或者合理安排资产和收入来实现。无论是个人还是企业，提高税效率都有助于保留更多的收入或资本，从而优化财务状况。 diff --git a/Chinese_Content.md b/Chinese_Content.md new file mode 100644 index 0000000..bdbd579 --- /dev/null +++ b/Chinese_Content.md @@ -0,0 +1,2044 @@ +# 001《佛法精髓与比库之道》原文 + +比库对世间的惠益：佛陀教导妙法，为世间与出世间指明繁荣之道，依此道而行者能获得世间与出世间的一切利益。正是比库们防止了佛陀教法的消亡，若非比库，或许佛法早已从世间隐没。令佛法久住是比库们对世间最大的贡献。 + + +人们亲近比库、聆听佛法开示，由此皈依三宝、受持五戒、增长慈悲、学习佛法、减弱愚痴、投入禅修，他们于此生和来世收获快乐。有些人证悟入流道果等出世间成就；有些亲近比库的信徒，认识到佛陀教法的意趣、出家加入僧团，证悟涅槃。 + + +许多人亲近比库后，听取规劝、戒除酗酒等恶习，提升了做人的品德；还有一些人跟随比库们学习，得到提升。已加入僧团或是希求加入僧团的人，应常省思持戒的功德，以及为自己和世间带来的惠益，如法如律地生活。 + + +成为优秀的比库：于此教法中，那些已经获得禅那（安止定）或更殊胜能力的比库们，被认为是优秀的比库。现今有此能力的比库虽然不常见，但也不能一概而论的说，世上没有这样的比库了。 + + +结合现今的情况，如果比库不违犯守护出家身份的重要戒条，尽力持守所有的戒律，破戒后悔过改正，履行所有义务，致力于学习、教授和开示佛法，以及念诵护卫和禅修等比库之修行，努力降低贪婪、傲慢等烦恼，提升慈悲等功德；如此，即使他没有固定的住处和施主、没有亲戚和财物，只是过游方行脚的生活，依然可称为优秀的比库。 + + +当知不应以地位、学历和财产来衡量比库的高尚，比库的高尚在于戒德、定德、慧德等品质。比库不应为了获得供养而取悦信徒，不应为了获取资具而参与不如法的活动，只应踏踏实实地修行。也许他会缺衣少用，也许走到哪里都会遇到无礼之人，也许因少有人供养，而很长一段时间生活陷入困窘；若此时他能够如法如律地行持，他会因这些障碍而提升。 + + +就算比库身处非常困难的环境，若他以非法方式索求资具、破坏诸如非时食等戒条，他也不算是优秀的比库。想要成为一名优秀的比库，身、心必须准备好面对各种考验。娇贵的身体对修行是巨大的障碍，身体越娇贵需求越多。那些爱护身体的人，想方设法为身体提供所需，供给不足时就不得不通过非法途径获取。 + + +想避免这种障碍，我们成为优秀的比库必须准备好忍受酷暑、雨露和任何天气的考验，吃不饱时可以依靠任何粗食生存，能忍受任何难吃的钵食，能以任何种类的饮食维生，乃至忍受蚊蝇瘟疫。 + + +印度教行者靠运动提升身体机能，巴利圣典中虽未记载释子沙门会锻炼身体，但释子沙门通过锻炼保持健康并不是坏事。即使不锻炼，走路、外出托钵、履行义务等活动，也会在很大程度上帮助调节身体。 + + +为提高身体的适应能力，行者应练习在硬面上坐卧，培养于户外逗留、宿眠的能力，应适应饮用白水取代夜分药，饮食知节量，即使在允许的时段内也不要吃零食。以茶、咖啡等糖饮作为夜分药的习惯，对身体是有害的。如今比库们习惯喝夜分药，古代的比库并没有这种习惯，他们用冷水解渴。 + + +比库的义务里清楚说明需常备饮用水，在《律藏·大品·大犍度》的“义务”部分，没有提到应向客僧供夜分药以取代水。此点在以下的《律藏》义注中也有清楚说明：“客僧若饮完供给他的水，供水的比库应该询问是否再需要一杯。”这里表明比库应以水解渴，而非茶饮、咖啡等夜分药。缅甸比库也没有饮用夜分药的习惯，客僧都是喝白水的。 + + +心的调御，即是去除杂染与贪欲、培育少欲知足等僧格或品行。通过学习和实践比库必备的僧格或品行，可以令心调御。对名闻利养的渴望，是成为优秀比库的障碍。一位比库若要圆满自己的出家生命，应习惯于满足任何所得到的袈裟等必需品。 + + +学习并念诵沙利子大长老的教诫，会对比库助益颇多：“无论美食或粗食，比库不应完全吃到饱腹；而应时时省思，饮食知量。”“食用比实际所需少四或五口的米饭，随后饮水；对于心向涅槃的比库，这样的生活足够安适。”“只要袈裟如法而得，如律覆体，足可御寒；对于心向涅槃的比库，此袈裟足够安适。”“于坐卧处盘腿而坐，只要不令膝盖打湿；对于心向涅槃的比库，这样的僧舍足够安适。” + + +若比库无法调御自心，即会陷入贪婪，无论得到多少资具都不满意。“我穿这些旧袈裟太丢人了，我这样怎么出门？我怎么能吃这些食物？若有人来这间破旧的住处让我情何以堪！我让访客坐在哪儿？我没有收入来源，要是病死该怎么办？如果我不得不出门该怎么办？……”心未调御的比库，会因如是之匮乏而懊恼，身体因此憔悴黯然甚至病倒；懊悔之后不久，便开始逐步用非法手段获取资具。 + + +若比库心已调伏，他不会为了四资具短缺而懊恼；无论当下状况如何，他都会知足，并依此而生存。他省思自身戒德等善行，生活充满喜悦。生活在丛林中的隐士，依靠水果和绿色植物生存，食物无盐无糖、未经烹饪，他们仍然健康长寿，全赖调伏之心所生起的喜悦。比库的心被调伏之后，所需越少越惬意。 + + +我们的菩萨，过去有一世曾是德米亚王子，住在丛林里修行。他的父王来探望他，看到菩萨的住处和食物，很震惊地问：“你吃这样的食物，独居山林，为何色身如此明净？” + + +菩萨以如下偈颂回答父亲：“大王，我睡于铺在地面的树叶上，以独自睡眠令色身明净。我没有皇家卫兵佩剑守护在侧，以独自安然睡眠令色身明净。”“大王，我不懊恼过去，不憧憬未来，活在当下，以此令色身明净。因为期望未来、懊悔过去，身体会如砍倒的竹竿一般，在烈日下枯萎。” + + +意识到这些过患，无论资具如何匮乏，比库也绝不应贪着，而应省思修行的殊胜、守护戒律。佛陀曾说：“愚人身心未调御，出家对于他们是艰难的；他们不能忍耐，无法持久，出家后被诸多困难吓退。”“比库若不停止逐欲之心，他又能坚持修行几天呢？他始终会被不善心干扰，最终放弃修持沙门法，得不到任何提升。” + + +破戒的过患：比库护戒应不亚于保护生命。破戒者佯装具德比库、混在清净比库的队伍里，乍现律仪相，伪装具德者而受到恭敬，他也受用佛陀只开许具德者使用的资具、接受具德比库的礼敬，参加戒律甘马，这些是非常严重的过失。“如同不握好古沙草会割伤手，沙门执持邪行会趣向地狱。”——《法句·地狱品》 + + +佛陀在《火堆喻经》中提到，即使一个人双腿被牢固的绳索捆绑、由两位壮汉相对拉拽直到肉散骨断，或是以刀剑刺穿其胸膛，此人所受之苦不及破戒比库接受信徒礼敬所受果报之苦。佛陀进一步教导，即使身体被滚烫燃烧的铁片包裹，其苦不及破戒之人穿着信施袈裟所受果报之苦； + + +即使口被火红的铁钳撬开、再吞下滚烫的铁球，其苦不及破戒之人食用信施食物所受果报之苦；即使坐卧在滚烫的铁椅和铁床上，其苦不及破戒之人使用信施床椅所受果报之苦；即使被头朝下脚朝上地浸没在融化的铁水中，其苦也不及破戒之人住在信施建造的寺院所受果报之苦。《火堆喻经》是关于已从沙门法堕落而仍乍现沙门相的犯戒者，应受果报的开示。 + + +《清净之道》所提及的破戒过患应当牢记：“虽受礼敬乐，破戒有何乐？彼因此受苦，过于引绳锯。”“受信众合掌，无戒有何乐？彼因此受苦，过于利刀刺。”“不自调御者，受用衣何乐？久受地狱苦，火焰铁板触。”“无戒受美食，毒如哈罗哈，因此于长夜，吞咽热铁丸。”“无戒用床座，虽苦思为乐，热铁椅与床，恼苦无穷极。”“信施寺中住，破戒有何乐？因此彼当住，热红大铁釜。” + + +“世间导师呵：破戒如粪土，具恶有疑行，有漏而内腐。”“不御非沙门，但穿沙门服，善根自掘害，此生实卑恶。”“如欲庄严者，厌离粪与尸，寂静具戒者，弃彼命何如？”“不离诸怖畏，却离诸证乐，紧闭入天门，登临地狱道。”“破戒者破戒，具足诸罪恶，悲愍者所愍，舍彼复谁属？”“哪怕比库只破微小戒但不忏悔，仍以破戒而住，此人死后将投生为沙门鬼，身着热火袈裟，捧燃烧之钵。” + + +《相应部·因缘品·勒叉那相应》中，也记载在迦叶佛教法期，有些比库、比库尼、沙马内拉、沙马内莉由于恶行投生为悲惨的亚卡（夜叉），哀嚎着忍受燃烧之钵和袈裟的折磨，这一幕被路经灵鹫山的勒叉那尊者看到。事实的确如此，当知比库以非法行是极其危险的。 + + +比库的助缘：佛陀曾于行脚期间开示《火堆喻经》。听闻后，有六十位比库心生怖畏而吐血，又六十位比库还俗，离开时说：“终生做一名优秀的比库难，还是回家做居士更好”，又六十位比库听后断除烦恼体证阿拉汉。 + + +此经迅速在比库之间传播，许多比库听闻后还俗离去，说：“此教法中能够完全守戒简直太难！”于是，有十名、二十名、五十名、百名、千名的比库相继还俗离去，曾经满是比库的寺院如今空空如也。 + + +佛陀行脚后回到祇园精舍，休息两周后与阿难尊者一起巡视各地寺院，发现寺院荒芜、比库人数骤减、个个愁眉苦脸；佛陀问阿难，早前他游方回来时还满是比库的寺院，而今为何如此寥落呢？ + + +佛陀听完阿难尊者回复缘由，随后说道：“正如有许多港口可以入海，在我的教法里有许多方法可令比库满足。”于是，召集众比库宣说《小弹指经》：“诸比库！若比库修习慈心乃至一弹指顷，诸比库，此比库可说是未缺乏禅那而过活，奉行大师之教法而过活，维护大师之教诫而过活，他未享用民众所施之食而空过。更不用说经常修习慈心的人了！” + + +经中提到，戒等等素质圆满的比库受施者，才能为施主们带来大的功德利益。但是，比库们即使每天修习慈心禅哪怕一弹指顷，也是在遵从佛陀的教导、可以如法受用信施。慈心是高贵的美德，戒德不够，应以慈心来弥补。即使受供的比库戒德不圆满，若他充满慈心，供养者还是能累积大功德。既然能令布施者得到大利益，遍满慈心的比库受用食物并非无益。修习慈心的比库值得被礼敬和供养。 + + +“比库修习慈心乃至弹指顷，他可成为信施食物的主人、无负债者、继承者而受用此食。”该经义注中提到，比库修习慈心之后，能以主人般受用信施食物，不再是“借受用”，已转为“嗣受用”。始终保持戒律清净是非常难的，因此所有的比库们都应该修习慈心，每天至少修习片刻。 + + +慈心也是比库抚慰自心的方法之一。祝愿顶礼的信众“快乐平安”也是一种慈爱的形式。比库养成如此祝福的习惯，是为了去除因自己戒律不清净时，被礼敬而生的不善。（这一点大部分比库只是按照传统去做，却不知其因。） + + +《弹指经》有多部，这些经都是为了对应《火堆喻经》而开示的，经中囊括了所有形式的禅修。因此，当知不论比库修习何种禅修所缘，他都可以如法受用信施资具，接受礼敬。以佛随念来礼敬佛是一种禅修业处；以法随念来礼敬法是一种禅修业处；以僧随念来礼敬僧是一种禅修业处；很多比库每日皈依三宝，也是一种禅修业处。如此行持的比库有资格受用信施资具；而且此礼敬本身也对比库有大利益，亦成抚慰之因，所以比库应每日礼敬三宝！——摘自《教海觉舟》 + +# 002《佛法精髓与比库之道》解释 + +比库的作用与贡献：佛陀教导了佛法，并指出了生活中的正确道路。比库是佛法的保护者，他们使佛法得以流传至今。 + +比库的影响：当人们接近比库并听取佛法，他们会受益于戒律、慈悲、智慧等，并在此生和来世中都会受益。 + +优秀的比库：真正优秀的比库不仅是遵循外在的戒律，而且是在内心中对佛法的真实实践，具有深厚的慈悲和智慧。 + +破戒的严重后果：破戒的比库可能会受到严重的果报或报应。比库应该始终维持他们的道德和修行标准，避免因破戒而受到的后果。 + +慈心的修习：慈心是比库修行的一个重要组成部分，它可以使比库对信众产生正面的影响，也可以帮助他们在面对困境时保持平和的心态。 + +心的调御与修行：为了真正地实践佛法，比库需要调节和训练他们的心，以达到真正的慈悲、智慧和清净。 + +# 003《券商倒闭后怎么办》 + +投资者保护基金：许多国家或地区都有类似于美国的证券投资者保护公司（Securities Investor Protection Corporation, SIPC）这样的机构，用以保护投资者免受券商破产的影响。如果券商是这类机构的成员，客户的账户通常会受到一定限额的保护。例如，SIPC可以保护每位投资者高达50万美元的证券和现金，其中现金的保护限额为25万美元。 + +隔离客户资金：合规的券商应当将客户资金和公司自己的资金分开存放，即使券商破产，客户的资金也应当是安全的。这些资金应当被隔离在受信任的银行账户中，并且在券商财务出现问题时不能被用来偿还券商的债务。 + +转移账户：在许多情况下，当一个券商面临倒闭的情况时，监管机构会寻找另一家券商接管客户账户，从而客户的资产可以无缝转移，减少对投资者的影响。 + +破产程序：如果无法转移账户，券商会进入破产程序，破产清算人将按照法律规定和优先级别分配剩余资产。 + +索赔程序：客户可能需要在特定的期限内向破产清算人或保护基金提出索赔，以证明其账户余额和投资持仓。 + +监管机构介入：在券商倒闭的情况下，金融监管机构会介入以确保法律法规得到遵守，同时调查倒闭原因，并采取措施保护投资者利益。 + +客户能否全额收回资金取决于多种因素，包括券商的财务状况、客户资金是否被正确隔离、以及有无其他未履行的交易或债务。在任何情况下，作为客户，了解您的券商的监管状态、投资保护规则以及您作为投资者的权利是非常重要的。如果您的券商确实遇到了问题，您应当尽快联系当地的金融监管机构或投资者保护机构了解具体的索赔程序和步骤。 + +# 004《看法和风险的跟单交易》 + +对跟单系统的详细评估需要从多个角度来考虑，包括技术性能、用户体验、风险管理、透明度和监管等方面。以下是一个详细的评估框架： + +技术性能 + +1. 执行速度：评估跟单指令从生成到执行的时间延迟。快速的执行对于避免滑点（成交价格与期望价格的差异）非常重要。 +2. 系统稳定性：系统是否稳定运行，没有频繁的中断或错误。 +3. 兼容性和集成：系统是否能与多种交易平台和工具无缝集成。 + +用户体验 + +1. 界面直观性：用户界面是否清晰易懂，新用户是否容易上手。 +2. 自定义选项：用户在跟单时是否可以设置自己的参数，如资金分配、止损水平等。 +3. 多样性和选择：提供多少交易者可供跟随，这些交易者的交易风格和表现历史如何。 + +风险管理 + +1. 风险控制工具：平台是否提供有效的风险控制工具，如止损订单、资金管理限制等。 +2. 跟单策略的风险评估：是否有系统来评估和显示每个可跟随交易者的风险水平。 + +透明度 + +1. 交易者历史表现：是否能够访问交易者的详细历史表现记录，包括盈亏、风险水平和交易策略。 +2. 费用和成本：平台的费用结构是否清晰透明，用户是否能轻易理解他们需要支付的费用。 + +监管和合规性 + +1. 监管地位：该平台是否受到认可的金融监管机构的监管。 +2. 资金安全：用户的资金是否存放在受监管的银行账户中，是否有合适的资金隔离措施。 + +社区和支持 + +1. 用户社区：是否存在一个活跃的用户社区，用于交流和分享经验。 +2. 客户支持：客户支持的可用性和响应速度，是否提供多语言支持。 + +性能和历史记录 + +1. 历史表现：评估平台上交易者的历史表现记录，但需记住过去的业绩不预示未来表现。 +2. 成功案例：是否有明确的成功案例，用户在使用该系统后的实际盈亏情况。 + +通过对这些方面进行综合评估，可以更全面地了解一个跟单系统的优势和潜在风险。重要的是，即使在使用跟单系统时，用户也应保持警惕，了解市场动态，并准备好应对可能出现的亏损。 + +# 005《技术分析在不同市场环境中的应用与局限性》 + +技术分析的角度： + +跳出技术分析看技术分析：意味着在应用技术分析时，需要从更广阔的视角考虑，不仅仅局限于图表和指标。要将技术分析放入整体市场环境的上下文中去理解。 +根据市场类型调整策略： + +趋势市场（如明显的上涨或下跌）：技术分析相对更有效，因为存在清晰的市场方向，使得技术指标能够提供更准确的交易信号。 +震荡市场（价格波动无明显趋势）：技术分析的有效性降低，因为缺乏清晰的方向性，使得预测变得困难。 +投资持有时间的考虑： + +上涨趋势中：长期持有可能更有利，因为趋势的持续可能带来更多利润。 +震荡市场中：短期持有可能更安全，因为长期持有可能会面临更大的价格波动和不确定性。 +技术分析的定位： + +技术分析应被视为一个跟踪当前趋势的工具，而不是一个预测未来市场走势的工具。它有助于分析和理解当前市场状态，但对于未来的预测需要更多信息和其他类型的分析。 + +# 006《现代亲密称谓的使用》 + +社交关系：王啸与嘉雯之间的关系可能较为亲密，或者他们在一个较为非正式的环境中交流。直接使用名字而不是带有正式性的“小姐”，显示了一种更随意的互动方式。 + +社会语境的变化：王啸的话反映了语言的社会文化含义随时间的演变。在当代，直接用名字称呼可能被认为更加平等和友好，而“小姐”则可能因为多重含义而变得不那么常用。 + +避免误解：正如您提到的，“小姐”在某些情境下可能会被误解或带有负面含义。王啸选择用名字来称呼可能是为了避免这种误解或负面的社会现实暗示。 + +文本风格：通过这种对话，作者可能在展现角色的个性或是塑造轻松幽默的对话风格，也可能是在提示故事的背景设定与时代环境。 + +原文“那我就直接叫你嘉雯，现在都不流行叫人小姐。”王啸打趣道。” + +# 007《升官发财死老婆注解》 + +"升官发财死老婆"是一个典型的中国俗语，含有讽刺和黑色幽默的成分。这句话的字面意思是“在一个人升官和发财的过程中，他的妻子会死去”，但实际上它通常不被理解为字面意义。这句俗语主要用来批评那些在追求权力和财富过程中忽视或牺牲个人关系的人。 + +它反映了一种观念，即在某些情况下，个人的职业成功和财富积累可能会对他们的私人生活，尤其是婚姻关系产生负面影响。在极端情况下，这种追求可能导致家庭关系的破裂或家庭成员的不幸。 + +总的来说，这个俗语是一个提醒，强调在追求事业和财富的同时，也应该注意保持生活的平衡，关注和维护重要的人际关系。 + +# 008《典型群和几何不变式》 + +"典型群和几何不变式" 或 "Classical Groups and Geometric Invariants" 的原理涉及数学中的抽象代数和几何学。让我们分别了解一下这两个概念的基本原理。 + +典型群 (Classical Groups): 这些是数学中的基本群体，主要包括以下几种： + +广义线性群 (General Linear Group, GL(n, R)): 包含所有n阶可逆矩阵，这些矩阵在实数或复数域上进行操作。广义线性群的操作是矩阵乘法。 +正交群 (Orthogonal Group, O(n)): 包含所有保持欧几里得空间中距离不变的n阶矩阵。这些矩阵与其转置矩阵相乘等于单位矩阵。 +辛群 (Symplectic Group, Sp(n)): 这个群体的元素是保持辛结构不变的线性变换。 +几何不变式 (Geometric Invariants): 这些是在几何变换（如旋转、平移、缩放）下保持不变的属性。它们在研究几何形状和它们的性质时非常重要。几何不变式的例子包括： + +面积和体积: 在合适的几何变换下，这些度量保持不变。 +曲率: 在曲线或曲面上的点的局部弯曲度，是一种重要的不变量。 +在典型群和几何不变式的研究中，一个关键的方面是理解这些群如何通过它们的作用来保持某些几何结构或不变式。例如，正交群的元素保持空间中的角度和距离不变，这是研究欧几里得几何的基础。这些概念在理论物理、机器学习、数学物理和许多其他领域都有广泛的应用。 + +# 009《n阶可逆矩阵解释》 + +在数学中，特别是在线性代数中，一个n阶可逆矩阵是指一个n×n的矩阵，它满足以下条件： + +1. 方阵：这个矩阵是方形的，意味着它的行数和列数相同，都是n。 + +2. 可逆性：存在另一个n×n的矩阵，称为其逆矩阵，与原矩阵相乘时，结果是一个单位矩阵。单位矩阵是一个主对角线上的元素全为1，其余元素全为0的方阵。 + + - 如果一个矩阵 A 是可逆的，那么存在一个矩阵 B 使得 AB = BA = I，其中 I 是单位矩阵。 + - 这个矩阵 B 被称为 A 的逆矩阵，通常记作 A^{-1}。 + +3. 行列式非零：一个n阶矩阵是可逆的当且仅当其行列式（一个从矩阵计算得到的标量值）不为零。 + +4. 线性独立的行或列：矩阵的所有行（或列）都是线性独立的，这意味着没有一行（或列）可以表示为其他行（或列）的线性组合。 + +可逆矩阵在数学和应用科学中非常重要，因为它们提供了线性方程组解的存在和唯一性的条件，并且在变换、系统理论和许多其他领域中都有广泛的应用。 + +将n阶可逆矩阵应用到金融领域，可以通过多种方式，包括风险管理、资产组合优化、定价模型等。以下是一些具体的应用示例： + +1. 资产组合优化：在构建投资组合时，投资者希望最大化回报的同时控制风险。通过使用矩阵，可以计算资产之间的协方差，这有助于理解不同资产价格变化的相关性。在这个框架下，可以使用可逆矩阵来解决优化问题，找到风险和回报之间的最佳权衡。 + +2. 风险管理：金融机构使用可逆矩阵来量化和管理风险。例如，在计算Value at Risk (VaR) 或其他风险度量时，可逆矩阵用于模拟不同资产组合的风险敞口。 + +3. 定价模型：在金融工程中，复杂的定价模型（如Black-Scholes模型）常用于衍生品定价。这些模型中，可逆矩阵有助于解决线性方程组，这些方程组用于模拟金融市场中的各种因素。 + +4. 因子分析：在评估证券性能时，因子模型（如Fama-French三因子模型）用于解释不同资产收益的变动。可逆矩阵在这些模型中用于从历史数据中提取关键因子，并帮助投资者理解市场动态。 + +5. 算法交易：在算法交易中，可逆矩阵用于构建复杂的交易算法和策略。这些策略通过分析历史数据和市场行为，自动执行交易决策。 + +在金融中应用矩阵和线性代数不仅仅是处理数字和方程，更多的是关于理解和解释市场行为，以及在此基础上做出有效的投资和风险管理决策。 + +# 009《布朗运动》 + +布朗运动（Brownian motion）是一种随机运动，由悬浮在流体（如空气或液体）中的微小粒子所展现。这个名字来自于19世纪的生物学家罗伯特·布朗，他首次观察并记录了花粉在水中的这种运动。 + +在二维空间中，布朗运动的轨迹可以用一个粒子在x和y坐标上的位置变化来表示。每个方向上的移动都是随机的，粒子在每个时刻都可以向任何方向移动一小步。这些随机步伐可以由温度、粒子大小、流体粘度等因素影响。 + +从图中的左侧可以看到，粒子的路径非常杂乱无章，没有明显的方向或模式，这是布朗运动的典型特征。每个转折点代表粒子的方向发生了随机变化，整个路径构成了一个复杂的、连续的轨迹。 + +布朗运动是热力学和统计物理学中的一个重要现象，因为它提供了原子和分子运动理论的直观证据。在金融领域，布朗运动模型也被用来描述资产价格的随机变化，这是许多金融数学模型的基础，如股票价格的随机漫步模型。在这些模型中，价格变化被假设为连续时间随机漫步，它们的变化率（即“回报”）遵循布朗运动。 + + +时域上的布朗运动的y轴是什么. + + +在时域上的布朗运动图中，y轴通常代表某个变量随时间变化的值。具体来说，这个变量可能是： + +粒子在某一固定方向上的位移，例如在水平或垂直轴向上的位置变化。 +物理量的大小，如粒子速度、加速度或其它可以随时间变化的物理属性。 +金融中的资产价格变动，如果这个图表示的是金融模型中的布朗运动，y轴可以代表资产价格的变化或回报率。 +对于上传的图的右侧部分（假设它描述的是一维布朗运动），y轴显示的可能是从起始点开始的累计变化，而x轴则代表时间。这种图通常用于显示随机过程中某个变量随时间的演变，如随机漫步或股票价格在某段时间内的变动。 + +# 010《无风险利率》 + +无风险利率（Risk-Free Interest Rate）是指在理论上没有违约风险的投资的回报率。换句话说，这是投资者投资于绝对安全的资产所能获得的收益率。在实际中，虽然没有绝对无风险的投资，但某些资产被视为近似无风险，例如一些政府债券。 + +政府债券作为基准：经常将稳定国家（如美国、德国等）发行的短期国债视为无风险资产。这是因为假设这些国家不会违约，因此，这些债券的收益率常被用作无风险利率的代理。 + +在金融模型中的应用：无风险利率在许多金融模型和计算中扮演重要角色，例如在资本资产定价模型（CAPM）中，它用于确定资产的预期回报率。此外，它也是计算投资组合的夏普比率（一个衡量风险调整回报的指标）的关键因素。 + +经济指标：无风险利率还被视为一个重要的经济指标，反映了市场对经济环境和货币政策的预期。例如，较低的无风险利率通常表明中央银行正在实施宽松货币政策，以刺激经济。 + +与市场风险的关系：无风险利率为投资者提供了一个基准，用于衡量承担额外风险的相对吸引力。投资者寻求超过无风险利率的回报来补偿他们承担的更高风险。 + +总体而言，无风险利率是理解和评估金融市场中风险和回报之间关系的一个基本概念。 + +# 011《拓扑学》 + + + +# 012《Black-Scholes模型》 + +Black-Scholes模型是一个用于金融市场中的期权定价的数学模型。这个模型由Fischer Black和Myron Scholes在1973年提出，并且后来Robert Merton对其进行了发展。这个模型的核心是一个偏微分方程，用于计算欧式期权的理论价格。欧式期权是一种标准类型的期权，它只能在到期日那一天行使。 + +Black-Scholes模型的重要性在于它提供了一个理论框架来理解期权价格如何受到各种因素的影响，如标的资产的价格、行权价格、到期时间、无风险利率和资产价格波动性（通常用标准差衡量）。这个模型假设资产价格遵循几何布朗运动，并且市场是无摩擦的（即没有交易成本和限制）。 + +Black-Scholes模型对金融领域产生了深远的影响，尤其是在风险管理和衍生品定价方面。它的一个主要局限性是它基于一些理想化的假设，例如恒定的波动率和对数正态分布的资产价格变化。实际市场中的复杂性往往要求对这个模型进行调整或使用更复杂的模型。 + +# 013《Steven Dux 交易采访稿》 + +0:00 +First Trade was very lucky I think I made 10,000 in one trade really yeah I +0:05 +think I with $25,000 yeah and and the next few weeks +0:11 +instantly 50% down and this is all your first year of trading or how long dides +0:16 +it take for you to eventually become profitable 6 months 6 months yeah 6 months uh I think the fastest approach +0:23 +to trading is to look at other people's mistakes because what whatever mistakes they made I might run into it later +0:30 +um everybody know that I made 6 million on the on the first day I made three M 3.5 million on the following day and I +0:37 +made a 9 or 3 million on the following day after the 3.5 million so that week total I made 17 million I think oh my +0:44 +God I don't ever focus on how much money that was generated by trading I want to +0:50 +perfect the system okay make sure it hits the maximum performance of all the patterns that I track once I reach 85% +0:58 +I'm creating trading hi have you ever wondered how much money a retail Trader can make in a single trading day in this +1:05 +episode we have a very special guest The Man of Mystery Stephen ducks ducks is a +1:11 +verified Trader and he holds a record for the highest p&l in a single trading day in 2022 making over $6 million +1:20 +trading dwac in one day I personally have a lot of respect for ducks he's +1:26 +very young but he has matured as a Trader and master the Arts of trading penny stocks using psychology and +1:33 +statistics and extreme discipline in this video you're going to learn Steven's approach to trading smoke cap +1:40 +stocks using Trader psychology Steven's various methods of tracking statistics +1:46 +how to recognize patterns and capture High profitability trades and how to avoid over trading make sure to hit the +1:54 +like button and join me today for a very insightful conversation with Steven ducks +2:01 +[Music] welcome to the humble Traders podcast +2:07 +Stephen hello you are a really famous Trader on Twitter and YouTube and you +2:14 +are really famously known for that I think was the dwac where you make six +2:19 +was it $6 million in one day yeah right so I think a lot of people know you for that and of course a lot of other +2:26 +profits you've had over the years if we could tell audience how this year treating you so far and how are you +2:31 +adjusting to the market this year is not as good as 2021 +2:39 +2022 the beginning of the year was okay uh since ever +2:45 +since uh May and June I mean the later this year is not very active yeah and uh +2:52 +this year's Market has been uh has been okay uh profitable and +3:00 +not making as aggressive as money as uh compared to +3:05 +2021 uh still up in the seven figures um and the lower seven figures okay not +3:14 +crazy high approaching eight figures um +3:19 +but volume has gone down about 90% 80% compared to 2021 and 2022 the market is +3:26 +become much more competitive compared to the last two years especially on the +3:33 +short side um as we know that shorting +3:39 +has 90% or or has much higher winning percentage compared to buying so +3:44 +majority of the money are H or held by shorts Setters and so if Shorts Setters +3:49 +are trying to Pile in into a ticker and there's not many Longs in there so there +3:55 +uh first short Setter cover and second short Setter cover above that so it will cause a massive parabolic uh as we saw +4:01 +in like top mhm so from my understanding is you're predominantly a short seller +4:07 +right okay I do want to ask you a little bit later on about like specific short strategies you're doing and how you're +4:13 +using your statistics to track those High odds as you call it um but that's take a step back how did you get into +4:19 +trading in the first place and how many years have you been trading now I got into trading when I was 19 so the the +4:27 +freshman year of college how did I get into trading you in school yes uh I +4:33 +don't have a very good family history but uh okay uh so at that time my mom +4:38 +and dad are going through divorce um so I was just trying to solve some of the +4:44 +financial pressure from my from my mom's side and uh I used my uh tuitions as my +4:52 +base money to trade which is about which is 25,000 yeah +4:58 +so um first of all I I think at the very beginning I lost half of it and then +5:04 +then I borrow some money from my friends started again you have rich friends not rich friends but I had to pay interest +5:11 +on that money so so okay so um but uh and they started again uh that's where I +5:18 +went from I think 27,000 to 900,000 first year then uh second year was 2.7 +5:26 +million third was I mean goes up from there so so you were trading with your +5:31 +tuition money and then eventually once you start making money is that how you paid for your school for the rest of the +5:37 +college or did you drop out of college I mean still in school and pay for the tuition of whatever the money I made +5:43 +from Trading okay and what was your major uh engineering oh I was going to +5:48 +guess either like mathematics or engineering uh chemical engineering +5:54 +chemical okay yeah so what what did you aspire to be at the time when you were still going through school +6:01 +uh I mean I like engineering I like very statistic based so a major and I chose +6:09 +engineering and the reason why I went to engineering I want to more Focus down into +6:14 +nanotechnology nanot technology yeah okay uh at that time we're focused on nanot tubes I think but uh then um I +6:23 +shift my focus more into trading afterwards so okay so how did you I +6:28 +understand you were trying to make some money to help out with a family so why Trad in stocks and how did you discover +6:35 +stock trading in the first place okay so yeah so um well first of all 25,000 is +6:41 +not a lot of money first of all as an international students we don't I mean +6:48 +our commun communication skills are not very good compared to the the natives +6:54 +people in here oh like in terms of English in ter yeah in terms of English so trying to do the the talk businesses +7:01 +or like real estate you have to communicate with other people so that's you know a big I say shortage for for +7:08 +some people like us and we also came in as a F1 student so you can't really have +7:15 +a job but only in campus you only can have a job in campus okay yeah I remember and +7:22 +you're making about like $6 an hour or $7 an hour so that's not efficient um +7:28 +and with 20 5,000 I look through pretty much all of the uh industry and the only +7:34 +one you can make money is trading to um uh using small amount of capital to +7:43 +get over 1,000% or 10,000% return that's where I looked into it and I see a lot +7:50 +of potential into it but I also see a lot of risk so just let need to take a bit I I I was also international student +7:58 +in the state I went to school school in Florida uhhuh so at the time I was I +8:03 +discovered trading around the last year so senior year but I didn't actually trade because I didn't have the money +8:09 +but I was like trying to save up from like my $7 an hour like on campus job but that +8:16 +helped me save us so that brought back some good memories yeah yeah I mean yeah +8:21 +similar similar to boat so you found out about trading stocks mhm did you start +8:27 +with like with day trading right away or did you invest or you know people do like a dividend investing or swing +8:33 +trading or did you just dive into the wild wild west of day trading not oh +8:39 +pretty much straightforward into day trading the first ticket I traded was ETF I think it was okay uvxy I mean it's +8:46 +ETF but uh that's the first trade made $20 but uh good +8:52 +job and uh I mean there's bunch of trading histories that have I think ad +8:58 +that straight pretty pretty much straightforward into day trading and uh the first trade was very lucky I think I +9:04 +made 10,000 in one trade really yeah I think I with $25,000 yeah oh okay I think I had a uh +9:14 +I think a $3,000 position okay so tiger went like 300% then I made 10,000 I +9:21 +think the trading could be that easy so oh okay and and the next few weeks +9:27 +instantly 50% down I mean TR on some stupid tickers and over trading were you +9:32 +following alerts at first or did you actually like try to learn strategies and trade I don't follow alerts and I I +9:42 +uh I I want to learn strategies because I look in this industry a little bit +9:47 +differently because I see well in trading industry if you if you make +9:52 +money somebody else is losing money right so zero some game yeah very simple +9:59 +concept yeah so um that means if you're following alerts a lot of people going +10:05 +into one directions that means the if 90% people in the trading industry are +10:10 +losing money yeah 10 10% are making money that means uh majority of the you know you +10:17 +have to go opposite of the what the majority go so I start going the opposite Sid of shorting alerts oh so +10:24 +you start out a contrarian from like very early on when people are like pumping what those alerts you were +10:29 +shorting them I'm shorting them yeah oh you fig that I was super early yeah I mean very beginning of my career I +10:35 +started making like 20% 30% again I mean then you start not that start not work +10:41 +doesn't well you start to not work as well because okay um my size is getting +10:47 +bigger and there's not many people chasing alerts anymore and the stock becomes very liquid so it's hard to get +10:52 +out uh but uh that's where my first I would say 50,000 40,000 oh +11:00 +so you started trading pretty big size almost right away then right cuz you mentioned you were taking $3,000 3,000 +11:07 +shares $3,000 worth of positions yeah okay I guess you were trading with a 25 +11:13 +$27,000 account to avoid PDT yeah and how often were you trading since you +11:18 +didn't have the Restriction of PDT were you still trading every day not trading every day okay um but when there's a +11:26 +play I'm in there so it's still overtrading but uh I think I was making about four +11:33 +to five trades a week and did you dive into full-time trading or were you still +11:38 +I guess you were you managing the classwork and trading on the site yes yes pretty much TR how did you find the +11:45 +schedule then I mean not I mean look at the phone during class I mean other other than the exam but you know just +11:52 +look at the phone during the class uh using TDM trade and not anything oh okay +11:58 +and how did that work out trading on the phone does not work very very well okay +12:03 +slow and uh first of all it's slow second it's I mean take a while to put +12:09 +in limit orders and limit orders yeah yeah so it's not quick at all it was +12:17 +sometimes you miss I miss couple thousand dollars just just trying to get out at one point and 10 second later you +12:23 +know we're 10% down and this is all your first year of trading or how long did it +12:28 +take for you to eventually become profitable 6 months 6 months yeah 6 +12:34 +months mhm that's really really fast uh yes because uh I look at so I +12:42 +think the fastest approach to trading is to look at other people's mistakes because what whatever mistakes they made +12:48 +I might run into it later defitely so I look through Gran's entire trading +12:54 +record yeah and I think was uh on the Tim side of the student they have their +13:01 +record on U on profit I think was a very early stage of trading and I was also looking +13:09 +at uh investor underground and other people you know people on Twitter they talk about their trading and poster +13:15 +profits I I don't typically look at their wins I only look at losses and I want to be able to even though they +13:22 +don't post the entry and exit chart but I want to be able to guess where where they short it is I see where where they +13:29 +got uh where they exited or uh maybe they made a huge M mistake they +13:35 +continued to add and eventually got BL out the position so all those mistakes +13:40 +are very valuable experience for me so that's when I become very uh profitable +13:45 +because I actively avoiding those mistakes yeah you you you're really young but you're also really wise a lot +13:53 +of people who start out trading they want to see like the flashy pnls a big profit but you were looking the opposite +13:59 +you're looking at people's losses and looking at learning from their mistakes yeah um and also I know that there's +14:08 +three base factors first of all is human mistakes that's number one you have to fix okay number two is um patterns come +14:15 +from psychology because if you're making money that means other people are making mistakes and you know how stock it +14:24 +really is it's really emotional driven yeah so psychology is very plays very +14:29 +big part of uh in trading so understanding the people that's going +14:35 +the opposite directions or um I mean they're behind the computer clicking the +14:41 +Button making mistakes so you have to understand their psychology first and third you have to use your statistics +14:47 +Theory to back up the psychology side um then with those three combined then it's +14:54 +instantly profitable so but it take it take a while take a while to get those +15:00 +three thing lined up together how long do that take you 6 months really you you +15:06 +everything clicked just like that in six months yeah oh wow so what kind of Statistics I know you mentioned that +15:13 +earlier in the beginning how what what were you tracking to realize okay I need to focus on this one strategy or these +15:20 +two strategy what kind of specific criterias were you looking at first of all I mean when I went went in there +15:27 +it's it's a there's a lot of stuff to track you can't you most people go in with okay +15:33 +well there's a lot of stuff I have no idea what to track right so you start narrow stuff down let's say we have a +15:41 +ticker that's 20 million market cap 3 million float uh very similar action put them +15:47 +together how much they traded uh to see there's any similar actions or similar +15:54 +Behavior or if it's going parabolic or start going M midday or Gap up in the pre market uh so pretty much you want to +16:03 +categorize very similar Market very similar Mark uh uh float um and the gap of +16:10 +percentages uh categorize them into one section try to find the conclusion of if +16:16 +volume changed what happened if flow changed what happened so you you kind of put a fixed criteria on All U pretty +16:23 +much everything and uh there's only one factor that's different I see so you +16:29 +will be able to kind of tell okay next time similar flow similar market cap if +16:35 +the volume is different I'm supposed to do this I see so you need a massive +16:40 +amount of Statistics to find uh I know I have I think at +16:46 +beginning I 25 sections okay with market cap between 0 to 10 million FL between 0 +16:52 +to one uh Gap up over 50% or market cap between 0 to to 20 or float between 1 to +17:01 +three see this time is different but with gap up percentage with 50% so you only have the flow difference I see and +17:09 +once you only have the flow difference uh with very similar volume throughout the day so you can kind of see what how +17:16 +much did the spiking percentage changed oh so that's one method of how to figure +17:23 +out what to track okay let me sum up that really quick cuz you just mentioned a lot of things I want to make sure +17:28 +audience understand your method ex the first method you mentioned really clearly so essentially you're trying to +17:35 +find the first method that say you narrow down let's say 10 stocks that you +17:40 +know are low flows they have similar volume and then you look at different categories like the volume pre-market +17:46 +volume you know percentage Spike after open and you look at what they have in common yeah and what's the outlier +17:53 +criteria whether it be super low float or super high volume that cost +17:59 +potentially have caused that one stock to Stand Out Among the most yes oh okay +18:04 +got it okay uh first criteria and second is you second way to be able to track uh +18:12 +statistics is you want to focus on volume specifically because people are +18:19 +behind computers trading the tickers right so every shares they trade means one shares and well of course there's +18:26 +alos and H found involved in there but you have to think there's one thing that +18:32 +the Hedge found that won't do is they take the entire the flow so basically +18:37 +they buy the entire flow okay and first of all they have they have to file to the SEC that's very that's you know not +18:45 +very convenient that's what they what they don't want to do and second you +18:50 +want to if you want to pump the stock you don't want to own the entire flow because eventually once you sell you're +18:57 +basically uh playing with yourself yeah there's no one else to sell to there's nobody else to sell you need the +19:02 +liquidity so you do not want to occupy the entire floor you want to retail to go in there yeah and pump the stock up +19:09 +and they sell into the retails and retails loses money so once you track enough multi- rers there's actually a +19:17 +very uh similar number that how much money can retail put into a ticker okay +19:25 +based on float or market cap based on market cap okay yeah so uh that's +19:31 +another way to track statistics based on how to really short into multi owners so +19:38 +in that case that say hypothetically speaking your second method just mentioned let's say based um I don't +19:45 +know 50 mil market cap retail can only let's say from that tracking retail can +19:51 +only get up to you know 10% of that market cap and then that's the ideal time to short uh yes yes but more more +20:01 +accurately uh do you want to be more accurate is you want to use the volume +20:06 +uh times the average traded price on that day if it meets the threshold of how much money that retail can pour into +20:13 +stock that means stock will go down next day uh because basically the stock has reached the maximum threshold that +20:19 +retail can push up to the maximum maximum percentage yeah yes oh interesting I never thought of that way +20:26 +or dollar amount there there's a lot of uh I can go uh so I I'll do three um +20:33 +there's another way to track statistics mean uh which I personally use which +20:38 +will be volume comparison is that you want to um so +20:46 +there's three different uh uh categories you want to do you want to track first +20:51 +of all is uh to be able to correctly track in resistance okay and lot of people see +20:58 +okay well there's a resistance that traded 50 million volume on a price of +21:05 +three and uh next time I want to short against with that $3 resistance right +21:12 +okay and so let's see for example let's say uh 50 million Vol that means five +21:19 +people let's say five people bought stock at three two mon later stock instantly dumped 90% everybody wants to +21:25 +get out because well if I get out I'll be down % what's the point of me selling right now since I'm already down 90% so +21:33 +the first reaction that when stock pushes back two three right everybody wants to wants to sell okay that's their +21:40 +instant reaction that's human psychology right there so and but here comes a problem because +21:48 +we're dealing with low floats so if the stock only have 3 million float and has 50 million volume in there and that +21:55 +doesn't mean that there's 5050 million resistance in there cuz there's only 3 milon volume 3 million flow sorry okay +22:03 +from previous let's say uh chart the resistance from like weeks ago yes +22:08 +doesn't have that much volume is what you're saying no doesn't it doesn't have the flow in there doesn't have 1550 +22:14 +million flow okay so if you want to let's say one one um every share is a +22:19 +back holder 15 million shares means 15 million back holder but if there's a 15 million shares only 3 million flow +22:26 +there's only 3 million back coders okay does that make sense that makes sense yeah so uh next time when you try to +22:33 +short into resistance that's the statistics you want to track because you are shorting a 50 million +22:41 +resistance but there's only 3 million backers in there okay so there's a very possible chance that stock can push +22:48 +through that resistance because there's only 3 million flow oh I see so a lot of +22:53 +people trying to just short based on how much volume uh that that's against the +22:58 +15 million that's a very interesting statistics to track +23:04 +and um it you can once you track that statistics you can help you avoid a lot +23:11 +of traps traps see so I think the first two method you mentioned helps you find +23:16 +a potential short entry the third one helps you avoid getting squeezed yes okay yeah oh thank you for sharing that +23:24 +there's uh there's many many many uh uh stuff that I I mean I came up in the last couple +23:31 +years what about you are you tracking any kinds of stats yourself make sure to share with other Traders down +23:38 +below is that do you think that's the reason why you pretty much stick with +23:43 +small caps cuz when it comes to large cap stocks there's a lot a lot less of these in inefficiencies right and a lot +23:51 +of the patterns the stats you track do they apply to other kinds of stocks no +23:56 +they don't uh the limitation is uh well except 2021 but the +24:04 +limitation is you cannot go beyond market cap that's above 300 million +24:09 +initial initial market cap so if the stock starts to spike starting with 300 million market cap then doesn't work +24:16 +okay but start less than 300 million let's say started around 100 million then goes all the way to couple billion +24:22 +it works oh so you're talking about let's say the first day of the run where the stock already started from yes oh so +24:30 +anything about 300 mil that doesn't count that still categorize a small cap right yes still categorize but you just +24:36 +won't trade it I just won't trade it oh so how you pick your stocks to trade is by volume and the market cap has to be +24:44 +below 300 mil yes oh okay and what kind of volume are you looking for when you are scanning for stocks to trade each +24:50 +morning uh really depends I mean volume highest the higher the higher the better +24:56 +okay uh I mean I do avoid first Green Day very crowded volume okay avoid that +25:03 +type of tickers uh but once they exhaust their volume then uh higher the volume +25:10 +the better yeah okay what about percentage gapper percentage um is there +25:15 +a point of like too high or like too low if it gaps above 200 I would say oh well +25:22 +it's probably more ridiculous when it's gaps above like 500% then it looks a +25:28 +little bit fishy to me um but the ideal range should be +25:34 +between 100 to 150 100 to 170 yeah percent +25:41 +percent oh okay like it has to have gapped up that much for you to be interested in trading them not +25:47 +interested but more comfortable trading okay I Gap up 500% I'm still interested +25:52 +in trading them I'm just want to be a little bit cautious on how to size in okay yeah so I I get that you know 100% +26:01 +gainers are very normal in 2020 and 21 but how what about in 2022 and 23 how +26:08 +are you selecting stocks then do you change your criteria there's still gappers that's above um 20 100% okay +26:17 +very few yeah very very uh we have let's see mmv that's one mhm when kep 200% +26:27 +then um yeah not many we had VC IG and all +26:33 +those biotechs that only gapped up like 80% so yeah above 100% is my highest +26:40 +winning percentage okay less than 70% if it doesn't have a resistance and +26:45 +on first screen day and it's a biotech yeah that's that's a noo for oh so you also don't want to trade try to avoid +26:52 +biotechs yeah yeah okay is there a reason why oh every time when I trade biotch I lose I mean it's and ATT track +26:59 +statistics on I still lose so I've been fighting biotch for many years now and +27:04 +uh it's sometimes you win sometimes you lose but by the end of the day you lose money right and and uh doesn't really +27:12 +matter we are going short we going along yeah biotches are very hard to predict they do not follow small cap stati +27:18 +statistics at all oh interesting so not only do you track those individual stocks or sectors or like the individual +27:25 +stock criteria you also track your own performance trading these stocks yeah I track everything yes okay how much the +27:32 +stock will drop to at what percentage to what scent I can get to that sometimes +27:38 +yeah that's how i' be able to bottom tick and top tick a ticket oh so what's like the a general formula you use to +27:45 +find the the top tick and the bottom tick and there's no general formula it's based on different patterns okay yeah +27:51 +every pattern has its own top tick and bottom tick tick uh point oh okay let's talk about your f favorite pattern do +27:58 +you have one right now uh favorite pattern probably this year it's first +28:03 +red day okay um highest they can drop other than IP other than IPO IPO will be +28:10 +a little bit different uh but not IPO multi owners the percentage that can +28:16 +drop market cap that's initially below 100 million flow below 5 million under +28:22 +10 million that work too uh the ne the average fading percentage for first red +28:30 +day is negative 26% average okay second day +28:35 +15% and the time typically drops to is 10:30 so once +28:42 +you once reaches okay 10:30 a.m. that's typically the lowest point oh after the +28:48 +first red day so typically you want to hold it overnight with a gap down next day hold on until 10:30 then you cover +28:54 +it yeah okay so these are ways that's like for this particular pattern the +29:00 +first red day that's how you find your exit yeah how do you find your entry now entry is the method that I talked about +29:08 +uh maximum volume on retail or maximum dollar being traded on the retails oh I +29:14 +see do is that your favorite pattern this year has that how how is that one pattern been performing for you this +29:20 +year it's still perform great it just the statistics keeps changing there's +29:26 +the that's flowing in the retail Market keeps changing yeah uh in +29:32 +2021 was 1 billion Inay mhm in I think like htz was something like that Herz +29:39 +yeah yeah I mean not Herz is a billion dollar cap so it's doesn't count that doesn't count but for lower cap the it's +29:47 +1 billion okay and for 2023 it's only 200 million so we can see that how much +29:53 +you dropped w a huge drop so we just talk about your favorite pattern what's your your biggest win ever on that +30:00 +specific pattern and your biggest loss we can cover that the first red day or I guess what +30:08 +the most memorable winner and the most memorable loser that You' ever had winner it's dwac dwac +30:19 +m um everybody know that I made 6 million on the on the first day I made +30:24 +three 3.5 million on the following day and that 9 3 million on the following day after the 3.5 million so that week +30:31 +total I made 17 million I think oh my God uh or from shorting that stock right +30:37 +or from shorting DW and there's another ticket I followed with it I forgot what's the name it was a sympathy play +30:43 +okay I went from I think went from uh 40 no it was around 52 I showed +30:50 +it around 48 covered at 28 so it's it was a sympathy play of dwac okay uh uh +30:58 +the most memorable loss yes I do remember one it was a biotech uh oh okay +31:04 +1 minut Flo 13 million flow uh I think it didm the uh maximum +31:11 +retail number okay and uh you squeezed above it typically I size in pretty big +31:17 +once it once uh it meets the retail number I see because that's high winning percentage Yeah that's when the com +31:24 +losses and the liquidity was not very great so so so and it took a long time +31:29 +to exit that's why okay I think the highest was a million dollar loss yeah 1 million okay now that's why you kind of +31:36 +crossed out biotech from your trading list forever Blacklist now yeah yeah Black List oh okay I mean up to dat has +31:43 +still I don't know because biotechs like they have they they do Gap very often +31:49 +they Gap 100% 200% sometimes and when when there is no play going on like you +31:56 +know in the last couple months and everybody has attempt to trade that and everybody tempting yeah everybody's +32:02 +getting squeezed so um um to be a very +32:07 +consistent profitable Trader yeah to be to stay alive in this industry you have +32:13 +to be super disciplined so yeah yeah I noticed that you don't trade every day +32:18 +like most Traders do how how often do you actually Place trades in a given month uh 3 to five or 3 to a week oh no +32:28 +not three to five in in the recent months three three trades to four trades +32:35 +a month okay yeah typically one trade a week oh wow sometimes not even a trade +32:41 +yeah do you believe in well do you practice what um is also a term that we +32:47 +recently learned from uh lens Bret Brin sorry keep on uh mispronouncing his name +32:53 +he's mentioned this term called exponential bet sizing basically do you size the same across +33:00 +all your different patterns or do you have certain ones like your favorite one that you would use more risk on oh yeah +33:06 +that's compound compound growth is um so uh I have all the patterns winning +33:14 +percentage down mhm some patterns has 70% some some some patterns has 80% 90% +33:21 +the higher the winning percentage is that means bigger size for me okay and how do you allocate that let's say +33:27 +the basic average is that's just use for a simple simple number a thousand so +33:33 +then that's say that's the average right let's say anything with 60% win rate you use an average of $1,000 risk and how +33:41 +would you use that for your um 90% win rate or your 80% win rate um patterns +33:48 +like what what number would it be 10x 10x oh okay yeah so if so average I'm +33:54 +using 100K 200k positions then and yeah the best it would be 2 million highest +34:01 +that size was 17 million was crazy 17 million shares traded not a$ 17 million +34:07 +position oh okay and how do you scale in because I understand once you're starting take taking these like massive +34:13 +sizes how do you scale into your position uh how do you scale in Parts by +34:20 +parts and has to be under 1% of the volume yeah yeah okay so let's say for +34:26 +example for a stock your max size will be let's say in this example 100,000 +34:32 +shares and you just divide it up into 10,000 share Lots or maybe 20,000 share Lots 50 50 yeah the bigger the positions +34:40 +maybe you have to break down a little bit more but yeah under $1 million it should be two okay two entries oh okay +34:48 +maybe three yeah do you think new Traders should learn about scaling as well or they should do one entry one +34:55 +exit one entry one exit oh it's the most efficient is one one enter and one exit +35:01 +one go oh okay so you never started with like you know let's say divide it into +35:07 +two halves and then just add and add and then two exits uh sometimes you will turn into +35:14 +add and add and add and blow up oh okay yeah but it happens a lot to +35:21 +a lot to Traders oh yeah well basically in that case they're not adding to Winners they're adding aaging down to a +35:27 +loser yeah a lot of people think that uh add into +35:32 +winners carut losses into losers I disagree with that you have to +35:40 +know exactly where you enter exactly where you want to exit and before you +35:46 +enter the trade you should know that how much you will will lose if you fail so +35:53 +we mentioned that about your most memorable loss so when you take these big losses is it usually from slippage +36:01 +or or was everything calculated beforehand everything calculated really okay I already know that million loss +36:08 +was coming oh okay because it's a biotech and you were sizing in that is +36:13 +your A+ setup yeah so you willing to risk a bit more yeah okay I see you just +36:19 +shared some really good tips for a lot of the new be Traders basically you recommend one entry in one exit out yeah +36:27 +yeah don't over complicate this uh maybe two maximum two but I recommend one in +36:34 +and one exit oh okay and we also talked about statistics and tracking do you +36:40 +think beginners should be tracking like you are or they should simplify things or how how would you recommend them to +36:46 +approach tracking well first of all for people that come to trading you love trading I love trading I love to win +36:53 +yeah people some people come in for trading that they want to make money so either way you want uh you want to win +37:01 +so you whatever do whatever that makes you want to win I can guarantee you that +37:07 +tracking statistics will make you win more so okay uh I recommend track as +37:14 +much as you can uh do the method that I recommend the first method which finding +37:20 +out the outliers okay um and to see what's the uh Factor that actually +37:27 +affect the stock push uh fading percentages or pushing percentages um then you will start +37:34 +finding your entry from there so I think a lot of beginners also suffer from +37:39 +struggle with overtrading and how do you think they should is there any way in which they can utilize +37:46 +tracking statistics and help them avoid you know overtrading these like random setups yes there there's one way I found +37:54 +out I was very helpful and they should be the golden tips uh for +38:00 +not making stupid mistakes on over trading okay well I to be honest I over +38:05 +trade uh I see I even over trade I sometimes you know hate myself over +38:11 +trades because you know nobody wants to make stupid mistakes and wasting money on on you know something that you +38:18 +shouldn't do everybody does I don't think there's as long as you're not an +38:24 +algo everybody make overtrading mistakes so uh first method which will be the +38:31 +most important one is you want to track well first of all find your pattern find +38:37 +out the statistics find out the average winning percentage act find out +38:44 +uh the average um profitable percentages so let's say this pattern average profit +38:51 +you can profit around 15% 20% okay find out the frequency how many times happens +38:57 +a year generate a sheet that using a fixed size so let's say every time when +39:03 +this pattern appears I'm going to size in $5,000 I'm going to make $1,000 on the +39:08 +trade uh this pattern happens 50 50 times a year 60 times a year you can +39:15 +generate a number MH uh how much you can make a year that's your expected return +39:21 +that's true expected return okay so every time when you sit in front of the computer in the morning every day look +39:26 +at that number first okay look at it first right this is how much I'm gonna make a year so I'm not gonna make a +39:32 +stupid mistakes here today I see and it works very well oh okay okay let me +39:38 +repeat that one more time so you basically find out for each individuals they should find their own strategy and +39:45 +find the average winning percentage and their average return like you know 20% +39:50 +return whatever and they put in the account size and use that the account +39:55 +exposure and you have to calculate how much potentially they can make in a year after learning about how frequent that +40:02 +pattern happens yes and use that number be it 100,000 or 50,000 use that number +40:07 +as an inspiration to stay disciplined and stick with that strategy yeah that's amazing I never heard of +40:15 +this this method I mean I came up with myself because I was over trading yeah oh and that did help you focus on like +40:21 +your A+ strategy yeah always focus on long-term once you look at a number it make automatically trans transition your +40:26 +mind from shortterm to longterm I think what a lot of people do is like they scalp around when there's no like +40:32 +perfect strategy they scalp around to make a $50 here and there and they forget about the big picture here I I'll +40:38 +share a story um so overtrading uh in the first two years I was making +40:44 +900,000 a year and I think the second year was 2.7 million and every time every year I'll +40:51 +go into my uh account statement and look at what I traded what what I'm supposed +40:57 +to trade what I'm not supposed to trade okay now there's some losses that I'm +41:02 +supposed to lose that's okay yeah but you you have to recognize what you are supposed to lose what you are not +41:08 +supposed to lose so once I filtered what I'm not supposed to do is I can make 4X +41:14 +of the money that I made oh wow that year so basically that's where I started to +41:22 +do the method that I yeah wow and like especially and it's 4X it's not even +41:28 +something equivalent like one to one it's one to four yeah and also I see it as a challenge because um so basically I +41:36 +the method I use for all the patterns they will generate a number let's say are you supposed to make 20 million this +41:42 +year yeah every time I can only hit 30% High highest I hit was 37 okay not +41:49 +even close to 80% to 90% to the full maximum performance that supposed +41:56 +to do as the perfect robot so yeah so is that what you're trying to aim for +42:01 +you're trying to reach a closer to closer to that 100% potential yes and +42:08 +every time I see 30% 30 37% I I keep I have a really close friend I talk about +42:14 +trading but I keep calling myself garbage Trader because I can only hit 30 30 37% yeah in a way you kind of treat +42:21 +trading as a game as well oh yeah yeah yeah it's a game now that you made so much money does the meaning of do you +42:27 +think money loses its meaning doesn't lose lose its +42:33 +meaning it uh I don't ever focus on how much money that was generated by trading +42:41 +okay now it is I'll say not the priority it is the first first will be the the +42:48 +thing that I told you is I want to perfect the system yeah um I want to +42:54 +be able to ttic bot and tick okay make sure it hits the maximum performance of +43:00 +all the patterns that I track and if I reach that goal I had I had myself a +43:06 +goal for for myself once I reach 85% I'm quitting trading really yeah so so so +43:13 +but it was never 85% but I think you might eventually get there I don't think so really I don't +43:19 +think so last year you did 30% this year you say you're doing 37 no the highest highest was 37 in 2021 +43:26 +oh okay so in a way if if you never get to 80% you never quit trading as well no +43:33 +no okay I don't think I'll ever ever get there I mean last year was +43:39 +uh that this year was only 20% even worse last year was last year was sick +43:45 +it doesn't count yeah 2022 was like 29 so it's is that kind of what keeps you +43:52 +going as well waking up in the morning each day cuz you're you're here on the West Coast right what time do you wake up 5:30 okay +43:59 +5 to 5:30 uhhuh and then you like scam for stocks and what what's your routine +44:05 +like after you wake up 5:30 what's your routine uh look at that stocks if there's nothing play some video games +44:12 +okay it's I don't want to look stay there and stare at the stocks and you know thinking about some overtrading +44:17 +strategy so yeah um yeah if it fits the criteria fits the criteria if it doesn't you know have some fun play some video +44:24 +games do you ever revisit and look at the scanner midday and see if there's opportunities or like if you don't see +44:30 +anything by 6:30 that's it for the day uh no trade after 1200 that's okay no trade after 11: suppose and that's 11:00 +44:38 +a.m. uh West Coast time or 11:00 a.m. Market time Market time Market time okay +44:45 +1130 a.m. oh okay what do you do for fun Sten do you look at spreadsheets and +44:52 +math and numbers for fun on your downtime oh I play a lot of video games oh okay yeah um I played Starcraft 2 uh +45:00 +for many years okay and before I I was mainly focused in trading I got into a +45:09 +uh World Series Championship oh you tra trading uh not trading Pro playing pro not playing pro +45:16 +but but uh my skill is approaching to Pro oh okay yeah I got to highest I got +45:22 +to was round of 64 World Series Championship yeah but how come you didn't pursue it I didn't cuz trading +45:28 +makes more money that that's true well a lot of pro players they G Pro Gamers +45:34 +they make a lot of money too but you know like they get paid at like 50 mil like the ones who win yes well I mean +45:41 +most of it U it's not the price they uh they promote either they they Market +45:47 +they're the marketer of their game so oh they get paid that way oh okay I mean +45:53 +that that game gives me a lot of benefits uh first of all is psychology second is hand speed oh clicking buttons +46:00 +clicking buttons I will be able to borrow like shares within point for 30 seconds you can have hot Keys set for +46:07 +that too I know but like you back in the days manually yes I can do very quickly +46:12 +okay yeah so Starcraft got you to think about to to train I guess your mouse +46:18 +click speed yeah and and you mentioned something about trader psychology with +46:23 +is buyers or seller how how does that game help you start thinking about it that way the game itself is very +46:31 +competitive it's one one versus one so I have an opponent that's on the opposite +46:36 +on the opposite of my side yeah and first of all you have to scout have to +46:41 +guess his strategy and according to his plan you have to make defense defense +46:46 +plan if his plan changes and you got it around then you lose so it's basically a +46:53 +counter psychology game back and forth back and forth until you win yeah so and +47:00 +and also uh it cor it what you are thinking with your hand you don't +47:06 +misclick you don't do anything uh you know if you make a mistake mistake on misclicking you lose the game too yeah +47:12 +so um and it's always high focus during +47:18 +the high focus moment you have you have to also think about the counter strategy for from for other people and um I think +47:25 +it's very simil to trading very intense moments and also be able to think clearly be calm figure out you know you +47:33 +don't first of all you don't misclick so can figure out what they're thinking to to be able to build a counter strategy against them so so you kind of have to +47:40 +think about their potential couple steps after and think about if he does that then what are you going to do yes the +47:46 +the I forgot who told me this but trading is basically a bunch of if and +47:51 +then statements like if stock ABC does this then this should happen yeah is +47:57 +that kind of how you kind of start thinking about trading uh yes yeah I +48:02 +know you used to live in Ohio is there a reason you decide to move to California to pay more taxes not pay more taxes but +48:09 +uh there's better food here that's for sure yeah um a love food uh I don't like +48:16 +waking up earlier but um better weather I I don't like cold weather I think I +48:21 +told you I hate cold weathers um and uh yeah that's pretty much it that's pretty +48:27 +much it and we have a different life experience I don't I'm not planning to live in California forever okay so oh +48:36 +were were some of your family out here as well no no just you I have a brother +48:41 +uh when when it's currently going to school in uh used to go to school in Florida now in Connecticut oh okay older +48:49 +or younger brother younger 10 years younger oh okay yeah so you're the eldest of the family do do you think he +48:56 +look up to you as an example oh yes he does yeah yeah would you want him to get into trading no I asked people that a +49:04 +lot a lot of people uh I mean I believe I to I taught a lot of +49:10 +students I believe you also taught a lot of students trading is not for any +49:16 +everyone I believe that too yeah you have to have that very very good +49:23 +personalities that's number one number two be able +49:29 +to uh handle trading in a different perspective a lot of people go into +49:35 +trading with the gambling mindset yeah yeah I mean every time you gamble every +49:41 +time you lose it's that's the rule yeah speaking of gambling you're Chinese were both +49:50 +Asian stocks like trading stocks or investing in stocks or even research searching stocks in Asia there's like a +49:58 +negative stigma was was your family ever concerned about what you're doing back +50:03 +then and you my dad was my mom wasn't okay um because whatever they +50:10 +experienced early in their age they don't want their child to go through the same thing they also suine stocks uh do +50:17 +they yeah stocks is something that they don't want their child to go through because they took a lot massive loss in +50:24 +their earlier age so um that's how parents teach their +50:30 +student oh teach their child to you know go through their life I mean not just +50:36 +stocks if they uh you know made some mistakes in any other industry they wouldn't want their child to go through +50:42 +that yeah same again do you think they're proud of what you've +50:48 +accomplished uh yes yes and no no it's +50:56 +I did not beat my own game yes is uh um of uh I mean have made +51:06 +some histories trading as a retail Traders MH uh highest profitable oh +51:12 +highest p in one day I guess yeah uh probably throughout the year too uh but +51:20 +uh yeah do you think if I know you're doing this for the game now if if I say I I tell you today or +51:28 +starting tomorrow you trade you can trade you see all those number but those numbers are not real money meaning you +51:34 +will make zero dollars whether you're up a million or down a million from Trading would you still be trading I I wouldn't +51:41 +payer trade okay to be honest because first of all uh I hate people calling me paper +51:48 +Traders at the very begin beginning of my trading career I was posting pinl on on twitters and everybody calling oh +51:54 +paper trading paper trading oh I hated that and uh then I started posting my +52:00 +account statement here's my account statement you can go ask D or you can ask the owner of The Brokerage and uh +52:06 +and I mean they can verify if it's real or not so then that's I mean I I I don't +52:11 +like people calling me like oh you're trading fake money so it's yeah but I I was asking cuz you treat trading as a +52:18 +game and you're just trying to get become a better Trader if you cannot make actual money from Trading would you +52:24 +still wake up every day at 5:30 to scam for stocks to go through that routine of tracking executing your A+ strategies +52:31 +would you still be doing this game I mean I will probably do a very similar game that makes +52:36 +money okay so making money is still important I mean it's important double win yeah um where do you what do you buy +52:43 +with your money what do you place your all the profits what do you do to +52:48 +diversify diversify uh most recently uh you can buy t- bills I mean very very +52:55 +save 5% yeah um and I trade stocks and I +53:02 +don't I don't I mean I don't like long-term stocks I don't know why you don't oh because um I mean the most +53:12 +recent statistics on overall economy doesn't seem very good okay looks like +53:18 +there's a massive recession coming yeah and uh we have all kinds of bubbles um +53:24 +so everything's a bubble now yep and there's going to be a large pullback so +53:30 +cash is Keen right now and okay wait until the market drops and potentially buy some diff okay you so you don't +53:37 +believe in real estate like watches like any alternative +53:44 +Investments uh real estate goes as same +53:49 +as stocks long term oh okay I'm surprised cuz Chinese people usually +53:54 +like to buy real I mean yes yes I do like real estate but they don't perform as aggressive as okay as uh +54:02 +trading so whatever you have available typically for for a method of trading is +54:08 +when I see a good play I wire money in and I trade and wire it out okay so this +54:13 +way you make sure that if you make a stupid mistake you don't blow up your account that's very smart actually and +54:20 +uh as long as you trust your trading skills I would prefer cash oh okay yeah +54:25 +your approach is very similar we we just talked to Tim Sykes the other day he has all his cash according to him in like a +54:32 +money market he doesn't do any Investments no cars no nothing yeah do +54:38 +you invest in cars H yeah I have a few cars but okay they're not investing +54:43 +thing oh okay they literally just buy them because for fun what are your +54:48 +current life goals cuz you're so young you're like 28 27 28 and you achieve so +54:54 +much what's next for you for Steven Ducks next is probably hedge fund yeah okay um and +55:04 +I saw a number that I could potentially make and in 2021 and I think I can get there once +55:12 +the market is back of course um it's 200 million so my goal is 200 million a year +55:17 +as a retail Trader or as a hedge fund Trader retail okay hedge fund maybe a little bit different yeah I think hedge +55:24 +fund or the depends on how much money you have under assets under management but uh yes okay yeah but do you think +55:32 +once you start a hedge fund or if you do do you have to trade +55:37 +differently maybe I don't know never never start the hedge funds so we'll see okay that'll be very interesting yeah +55:45 +yeah uh probably start small I don't know hedge fund is a little bit different because you don't take you +55:53 +don't take away all all the money that you make mhm it's Investor's money it's Investor's money so you are charging +56:00 +little bit of commissions and very small percentage of how much money that was +56:05 +made maybe it was not very maybe it's not worth it but it could be a good life experience so you try that out you're +56:13 +doing the this just for the game now by by by when you do that I can I can tell other people I was a hedge fund manager +56:19 +you can say that yeah but yeah good life experience could try it out thank you so much sharing with us all your tips and +56:26 +strategies where can people find you uh they can find me at Steven duxi du.com +56:32 +okay so where does ducks come from that's not your real last name right it was my first three letters of my name du +56:40 +D do do she show x i u x oh oh they're missing the +56:49 +you yeah oh show do show do she do +56:55 +x i a n do X yeah it's the first three letter of my name oh okay do you like +57:03 +ducks interesting name I mean I think it kind of stuck I mean it doesn't doesn't +57:09 +bother me yeah yeah did somebody mispronounce and got stuck is what I mean oh no no no oh okay okay yeah and +57:17 +then ever since everybody called me dgs yeah yeah well thank you Dougs for being here today and sharing so much with our +57:23 +audience I no problem if you enjoyed our conversation today and learned a lot from Steven Ducks make +57:29 +sure to hit the like button down below and you can check out even more interviews with other Pro Traders over +57:42 +[Music] here + +# 014《Steven Dux 交易采访稿分析》 + +交易早期经历：Dux最初用2.7万美元的学费开始交易，经历了一开始的损失，但通过分析和学习，他在第一年就显著增加了盈利。 + +统计分析的重要性：Dux强调使用统计数据来分析交易模式，比如考虑市值、流通量和交易量来决定交易策略。 + +市场心理学：他认为理解市场心理学是成功交易的关键，包括理解对手的心理和预测市场行为。 + +风险管理：Dux提到了他如何管理风险，包括设定止损点和避免过度交易。 + +专注于高胜率模式：他提到专注于高胜率的交易模式，并根据这些模式的历史表现来调整自己的交易大小。 + +对生活目标的看法：Dux讨论了他的个人目标，包括创办对冲基金和实现更高的年度盈利目标。 + +投资多样化：尽管作为交易员，Dux也谈到了对其他投资形式的看法，比如房地产和其他长期投资。 + +避免特定行业：他特别提到了避免交易生物科技股，因为它们的不可预测性导致他历史上损失惨重。 + +个人兴趣与交易：Dux谈到了他如何将个人兴趣（如电子竞技）与交易技能结合起来，提高决策速度和效率。 + +长期视角：他强调持有长期视角的重要性，通过计算每年可能的盈利来帮助自己保持专注和纪律。 + +# 015《Alpha Architect 服务条款》 + +Site Login +Contact us +Careers +Subscribe +Alpha Architect Logo +ETFs +Tools +Events +Research +About +Strategies +Search +Terms of Service +INTRODUCTION +Alpha Architect, LLC (“Alpha Architect”) provides tools and content for people interested in quantitative finance investing (on AlphaArchitect.com and subdomains, collectively known as the “Site”). 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You agree to submit to the personal and exclusive jurisdiction of the courts located within the county of Sussex Country, Delaware. + +ENTIRE AGREEMENT/SEVERABILITY +These Terms of Service, together with the Privacy Policy and any other legal notices published by Alpha Architect on the Site, shall constitute the entire agreement between you and Alpha Architect concerning the Site. If any provision of these Terms of Service is deemed invalid by a court of competent jurisdiction, the invalidity of such provision shall not affect the validity of the remaining provisions of these Terms of Service, which shall remain in full force and effect. + +NO WAIVER +No waiver of any provision of these Terms of Service shall be deemed a further or continuing waiver of such provision or any other provision, and Alpha Architect’s failure to assert any right under these Terms of Service shall not constitute a waiver of such right. YOU AND Alpha Architect AGREE THAT ANY CAUSE OF ACTION ARISING OUT OF OR RELATED TO THE SITE MUST COMMENCE WITHIN ONE (1) YEAR AFTER THE CAUSE OF ACTION ACCRUES. OTHERWISE, SUCH CAUSE OF ACTION IS PERMANENTLY BARRED. + +MODIFICATIONS +Alpha Architect reserves the right, in its sole discretion, at any time to modify, discontinue or terminate the Site, any portion thereof, or any content thereon without notice, or modify these Terms of Service. We will notify you about significant changes by sending you a notice to the primary email address specified in your account or by placing a prominent notice on the Site. If any modified terms and conditions are not acceptable to you, your sole remedy is to cease using the Site, and if applicable, cancel your Alpha Architect account. By continuing to access or use the Site after Alpha Architect makes any such revision, you agree to be bound by the revised Terms of Service. + +The Terms of Service were last revised on May 24, 2018. + +ARE YOU READY TO BECOME A BETTER INVESTOR? +CONTACT US +GET UPDATES NOW +I have read and agree to the Terms & Privacy Policy. Alpha Architect will use your information to provide blog updates and for email marketing. +Your email address +I have read and agree to the Terms & Privacy Policy. 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Full disclosures here. +© Copyright 2023 alpha architect | All Rights Reserved | Home | Terms of Use | Privacy Policy | Disclosures | Subscribe | Contact Us + +# 016《Alpha Architect 服务条款分析》 + +教育与娱乐目的: Alpha Architect 明确指出其网站是为教育和娱乐目的而设，而不是为了提供证券交易。 + +用户接受: 使用网站意味着用户同意遵守服务条款和隐私政策。 + +链接到第三方网站: Alpha Architect 对于用户通过其网站访问的任何第三方网站的内容或做法不承担责任。 + +信息免责声明: 网站上提供的金融信息仅为一般性质，不构成专业投资建议。 + +用户信息: 用户对其提交的内容负责，并授予 Alpha Architect 使用这些内容的权利。 + +使用网站的条件: 明确规定了用户如何合法地使用网站内容和服务。 + +知识产权: Alpha Architect 或其数据提供方拥有网站内容和商标的所有权。 + +退订程序: 用户可以选择不接收来自 Alpha Architect 的通讯。 + +免责声明和责任限制: Alpha Architect 对网站提供的信息的准确性或完整性不作任何保证，并限制了其责任。 + +赔偿: 用户同意在某些情况下对 Alpha Architect 进行赔偿。 + +接受条款的能力: 规定了使用网站的年龄限制。 + +转让: Alpha Architect 可以转让这些条款。 + +条款和终止: 描述了 Alpha Architect 可以终止用户使用网站的条件。 + +适用法律: 指定特拉华州法律适用于这些条款。 + +完整协议/可分割性和不放弃: 说明了这些条款是与 Alpha Architect 之间关系的完整协议，并处理了条款中无效条款的问题。 + +修改权: Alpha Architect 保留随时修改条款和条件的权利。 + +# 017《补跌》 + +股票价格影响因素： + +股票市场价格由基本面和市场情绪共同决定。基本面指公司的经营状况，而市场情绪反映了投资者的心理和行为。 +牛市和熊市的估值差异主要由市场情绪的变化引起。 +补跌现象： + +补跌是指股票在大盘下跌时未跟随下跌，但在大盘反弹或稳定时出现下跌。 +补跌可能由预期心理效应、机构和大户的市场操纵、长期停牌期间的市场变化，以及板块主力资金的出货等因素引起。 +投资者在观察补跌时应考虑股价的放量情况、重要支撑位，以及近期的股价走势。 +市场心理和行为： + +李笑来的观点提醒我们即使是不理智的市场共识，也能影响市场走势。这种羊群效应表明市场参与者往往会基于情绪而非理性分析作出决策。 +在投资市场中，情绪和预期可能对股价产生重大影响，有时甚至超过基本面分析。 +投资策略建议： + +投资决策应基于独立的分析和理性思考，避免盲目跟随市场共识。 +在面对潜在的补跌风险时，及时调整投资组合，不要仅因股价暂时未跌就忽略了大盘走势的可能影响 + +# 018《艺术的价值如何衡量》 + +市场价值：艺术品的市场价值是由供需关系决定的。包括艺术家的名气、作品的稀缺性、以往的拍卖记录、艺术品的原创性、保持状况、市场趋势以及潜在的投资价值等。 + +历史价值：艺术作品所反映的历史时期、流派或艺术运动的重要性。艺术品可能是某个时代文化、社会状况的见证者，因此具有无法用金钱衡量的历史价值。 + +文化价值：艺术作品可能代表了一种文化的特定表达形式，它可能展现了某种语言、宗教信仰、社会习俗或民族传统。 + +审美价值：艺术品的美学质量如何，包括构图、色彩、形式、表现力以及创新性等，都是艺术作品审美价值的一部分。不同的人可能会根据个人品味和审美标准给出不同的评价。 + +社会价值：艺术可以启发思考、促进社会对话、支持社会运动或者提高公众的道德和精神水平。它可能承载着教育意义、启蒙作用或是政治评论。 + +情感价值：艺术品所唤起的情感反应在个人层面上是无法量化的。对某个人来说，一个艺术品可能因为与个人经历的联系而具有特殊的意义。 + +功能价值：有的艺术品除了审美外，还具有实用功能，比如设计精美的家具、餐具等。它们的价值在于实用性和美观性的结合。 + +教育价值：艺术作品能够作为教育工具，帮助人们了解不同的文化和历史时期，促进批判性思维和创造性思维的发展。 + +# 019《市场供需关系》 + +供需曲线： + +需求曲线向下倾斜，表明股票价格降低时，购买意愿增加；价格上升时，购买意愿减少。 +供给曲线向上倾斜，表明股票价格上升时，卖出意愿增加；价格下降时，卖出意愿减少。 +均衡价格： + +需求曲线与供给曲线的交点，即市场上愿意买入和卖出股票的数量相等的价格点，这也是股票价格最终会稳定的点。 +内在价值： + +这个概念代表了股票基于基本面分析得出的真实或公平价值，考虑了公司的盈利能力、资产、负债和增长前景等因素。 +图中左侧的情况是股票市场价格低于内在价值，表示股票被低估，对投资者来说可能是个买入机会。 +图中右侧的情况是股票市场价格高于内在价值，表示股票被高估，投资者可能会考虑卖出或避免购买。 + +# 020《甲骨文服务条款》 + +User +Products +Industries +Resources +Support +Events +Developer +Partners +View Accounts +Contact Sales + + +Oracle Legal +Oracle Legal +Legal Notices +Privacy Policies +Terms of Use +Copyright +Trademarks +Logos +More +Terms of Use +Welcome to the Oracle Web sites (the "Site"). Through the Site, you have access to a variety of resources and content. These include: (a) software and software as a service offerings ("Software"); (b) Web pages, data, messages, text, images, photographs, graphics, audio and video such as podcasts and Webcasts, and documents such as press releases, white papers and product data sheets ("Materials"); and (c) forums, discussion groups, chat areas, bulletin boards, blogs, wikis, e-mail functions, and other services in connection with which you can upload, download, share, email, post, publish, transmit or otherwise access or make available Content (as defined below) ("Community Services"). Software, Materials, Community Services, and other information, content and services are collectively referred to as "Content." The following are terms of a legal agreement between you ("You" or "Your") and Oracle Corporation and its affiliated companies ("We" or "Oracle"). By accessing or using the Site or the Content provided on or through the Site, you agree to follow and be bound by the following terms and conditions concerning your access to and use of the Site and the Content provided on or through the Site ("Terms of Use") and our Privacy Policy. Oracle may revise the Terms of Use and Privacy Policy at any time without notice to you. The revised Terms of Use and Privacy Policy will be effective when posted. You can review the most current Terms of Use at https://www.oracle.com/legal/terms.html and Privacy Policy at http://www.oracle.com/legal/privacy/. + +1. 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You are responsible for maintaining the confidentiality of password(s) and account information, and you are responsible for all activities that occur through the use of your password(s) or account(s) or as a result of your access to the Site. You agree to notify Oracle immediately of any use of your password(s) or account(s) that you did not authorize or that is not authorized by these Terms of Use. + +8. No Unlawful or Prohibited Use +You agree not to use the Site, or Content provided on or through the Site, for any purpose that is unlawful or prohibited by these Terms of Use or the rules, guidelines or terms of use posted for a specific area of the Site or Content provided on or through the Site. + +9. 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ORACLE SHALL HAVE NO RESPONSIBILITY FOR ANY DAMAGE TO YOUR COMPUTER SYSTEM OR LOSS OF DATA THAT RESULTS FROM THE DOWNLOAD OR USE OF CONTENT. + +ORACLE RESERVES THE RIGHT TO MAKE CHANGES OR UPDATES TO, AND MONITOR THE USE OF, THE SITE AND CONTENT PROVIDED ON OR THROUGH THE SITE AT ANY TIME WITHOUT NOTICE. + +15. Limitation of Liability +IN NO EVENT SHALL ORACLE BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL OR CONSEQUENTIAL DAMAGES, OR DAMAGES FOR LOSS OF PROFITS, REVENUE, DATA OR DATA USE, INCURRED BY YOU OR ANY THIRD PARTY, WHETHER IN AN ACTION IN CONTRACT OR TORT, ARISING FROM YOUR ACCESS TO, OR USE OF, THE SITE OR ANY CONTENT PROVIDED ON OR THROUGH THE SITE. + +16. Exclusions and Limitations +SOME JURISDICTIONS DO NOT ALLOW THE DISCLAIMER OR EXCLUSION OF CERTAIN WARRANTIES OR THE DISCLAIMER, EXCLUSION OR LIMITATION OF CERTAIN LIABILITIES. TO THE EXTENT THAT THEY ARE HELD TO BE LEGALLY INVALID, DISCLAIMERS, EXCLUSIONS AND LIMITATIONS SET FORTH IN THESE TERMS OF USE, INCLUDING THOSE SET FORTH IN SECTIONS 14, 15 AND 16, DO NOT APPLY AND ALL OTHER TERMS SHALL REMAIN IN FULL FORCE AND EFFECT. + +17. Privacy Policy +Oracle is concerned about your privacy and has developed a policy to address privacy concerns. For more information, please see Oracle's Privacy Policy. Any personal information collected on this Site may be accessed and stored globally and will be treated in accordance with Oracle's Privacy Policy. You understand that Oracle collects, uses, processes, possesses, and otherwise stores your personal information and utilization data and may share such data with third party service providers for the purpose of improving or providing services subject to Oracle's Privacy Policy. + +18. 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You agree to comply with all export laws, restrictions and regulations of any United States or applicable agency or authority, and to not directly or indirectly provide or otherwise make available any services and products of Oracle in violation of any such restrictions, laws or regulations, including, without limitation, laws, restrictions or regulations pertaining to the development, design, manufacture or production of nuclear, chemical or biological weapons or missile technology. As applicable, you shall obtain and bear all expenses related to any necessary licenses, authorizations, and/or exemptions with respect to your own use of the services of Oracle outside the U.S. Neither the services or products of Oracle nor the underlying information or technology may be downloaded or otherwise provided or made available, either directly or indirectly, into any country subject to U.S. trade sanctions, (Supplement No. 1 to Part 740, Export Administration Regulations, Country Group E:1), to individuals or entities controlled by such countries, or to nationals or residents of such countries other than nationals who are lawfully admitted permanent residents of countries not subject to such sanctions. By agreeing to these Terms of Use, you agree to the foregoing and represent and warrant that you are not located in, under the control of, or a national or resident of any such country or on any such list. + +21. Forward-looking and Cautionary Statements +Statements set forth in the Site may constitute forward-looking and cautionary statements within the meaning of the Private Securities Litigation Reform Act of 1995 or other applicable laws. While these forward-looking statements represent our current judgment on what the future holds, they are subject to risks and uncertainties that could cause actual results to differ materially. You are cautioned not to place undue reliance on these forward-looking statements, which reflect our opinions only as of the date such statements are set forth in the Site. Please keep in mind that we are not obligating ourselves to revise or publicly release the results of any revision to these forward-looking statements in light of new information or future events. You should also review our most recent Form 10-K and Form 10-Q for a more complete discussion of these factors and other risks, particularly under the heading "Risk Factors." A copy of our press release and financial tables which include a GAAP to non-GAAP reconciliation can be viewed and downloaded on the Oracle Investor Relations website at Oracle.com/investor. + +22. Availability of Products +Information on the Site may reference or cross-reference Oracle products, programs, or services that might not be available in your location. Such references do not imply that Oracle plans to make such products, programs, or services available in your location. Please contact your local Oracle representative for more information. + +23. Waiver and Severability +The failure of Oracle to exercise or enforce any rights or provisions in these Terms of Use shall not constitute a waiver of such right or provision. If any part or provision of these Terms of Use is found to be unenforceable, such part or provision may be modified to make the Terms of Use as modified legal and enforceable. The balance of the Terms of Use shall not be affected. + +24. Applicable Laws +All matters relating to your access to, and use of, the Site and Content provided on or through or uploaded to the Site shall be governed by U.S. federal law or the laws of the State of California. Any legal action or proceeding relating to your access to, or use of, the Site or Content shall be instituted in a state or federal court in San Francisco or Santa Clara County, California. You and Oracle agree to submit to the jurisdiction of, and agree that venue is proper in, these courts in any such legal action or proceeding. + +25. No Integration +Some materials on the Site pertain to Oracle Health, Oracle Cerner and Cerner Enviza which are all wholly-owned subsidiaries of Oracle Corporation. Nothing on this website should be taken as indicating that any decisions regarding the integration of any EMEA Cerner and/or Enviza entities have been made where an integration has not already occurred. + +26. 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If you have any other questions, contact information is available at the Contact Oracle page on the Site. + +Last Revised: August 11, 2023 + +# 021《甲骨文服务条款分析》 + +管理区域订阅 +所需的IAM策略 +管理员组权限：如果你是管理员组成员，那么你已经拥有管理区域订阅的所需权限。 +策略入门与深入：对于刚接触策略的用户，Oracle建议先了解基础知识，进一步的，则需要深入学习如何为管理区域编写IAM策略。 +主区域（Home Region） +初始设置：你的主区域是Oracle云基础设施中创建租户的区域，也是定义IAM资源的地方。 +不可更改性：一旦设置，主区域无法更改。 +资源管理：用户、组和策略等资源必须在主区域中创建和更新，尽管它们的效果会扩散到所有订阅的区域。 +API和控制台使用 +API：通过API进行更改时，必须使用主区域的端点。 +控制台：Oracle云控制台会自动将IAM资源更新请求发送到你的主区域。 +订阅新区域 +策略执行：在你订阅新区域时，主区域中的策略将在新区域中生效。 +策略定制：你可以编写特定策略来控制对不同区域的访问。 +关于IAM更新的注意事项 +更新传播时间：IAM资源的更改可能需要几分钟时间才能在所有区域中体现。 +部署SaaS应用程序和地理区域 +订单指定：SaaS应用程序在订单中指定的地理区域部署，而不一定是在主区域。 +身份域：在主区域中创建默认身份域，但SaaS应用程序可能在不同的数据中心区域部署。 +数据位置：管理凭据存储在主区域中，但实际应用数据仅存储在订单中指定的数据中心区域。 +使用控制台和API +控制台：可以用来查看和订阅基础设施区域。 +API操作：使用GetTenancy、ListRegions、CreateRegionSubscription和ListRegionSubscriptions等API操作来管理区域。 +区域常见问题解答 +个人用户订阅：是否个人用户可以订阅区域，这一点在文本中没有明确，可能由租户级别管理。 +资源可见性：一个区域中的资源不会自动在另一个区域可见，除非在策略中指定。 +服务限制：每个区域可能有自己的服务限制。 +访问限制：你可以编写策略来限制对特定区域的访问。 +更改主区域：一旦设置，你无法更改主区域。 + +# 022《申请藤校》 + +突出你的优势： + +你提到你有“丰富的课外活动，拿国际国内大奖，创建非盈利组织”，这些都是非常强有力的申请加分项。确保在申请中详细描述这些成就及它们的重要性，以及你因此学到了什么，你的经历如何塑造了你的世界观和未来的学术职业目标。 +强有力的个人陈述和推荐信： + +你的个人陈述和推荐信应该能够凸显你的独特性和潜力。尝试讲述一个能够引人入胜的故事，让招生委员会看到你不仅仅是GPA的数字。 +选择能够深入了解你个人特质和成就的人来写推荐信，他们能提供具体的例子来说明你的潜力和成就。 +标准化考试： + +如果你的SAT或ACT成绩很高，那么可以帮助平衡较低的GPA。 +有些常青藤大学现在实行了测试可选政策，这意味着提交这些成绩是可选的。如果你的标准化考试成绩不理想，而你的其他资质非常强，你可能会选择不提交这些分数。 +解释任何不足： + +如果你的GPA低有特殊原因（比如家庭问题、健康挑战等），可以在申请的适当部分解释这些情况。 +但要注意，这个解释应该是建设性的，强调你是如何克服困难，以及这些经历如何帮助你成长。 +提早申请（Early Decision/Early Action）： + +如果你对某所常青藤大学有特别的偏好，可以考虑提早申请。这通常会提高你的录取机会，因为它向学校展示了你的兴趣和承诺。 +寻找适合的学校： + +虽然常青藤联盟的学校非常出名，但还有很多其他学校提供优秀的教育。考虑那些可能更适合你的学术记录和个人兴趣的学校也是很重要的。 +准备好计划B： + +考虑到竞争的激烈程度，即使你做了很多准备，也有可能申请不成功。因此，制定一个实际的备选方案也是很有必要的。 + + + + + +GPA的重要性 +学术能力的指标： GPA可以反映出学生在高中期间的整体学术表现，它通常被看作是学生学术能力和学习态度的重要指标。 + +课程难度： 许多大学也会考虑你所选课程的难度。如果你在高中期间选修了AP、IB或者荣誉课程，并在这些课程中取得了不错的成绩，即便GPA不是顶尖，也可能得到积极的评价。 + +趋势： 招生官同样关注成绩的趋势。如果你的成绩随着时间的推移而提高，这可能会给招生官留下积极的印象，即使你早期的GPA不是很高。 + +其他同样重要的因素 +标准化考试成绩： SAT或ACT成绩可以为招生委员会提供另一种衡量学术能力的方式，特别是在GPA较低的情况下。 + +课外活动： 学生的领导力、社区服务、体育、音乐、艺术或其他个人才能可以展示学生的全面性和个性，这些在常青藤大学等寻求全面发展学生的高校尤其受重视。 + +个人陈述和补充论文： 这些写作部分是展现个性、价值观、写作能力和对所申请学校的热情的重要机会。 + +推荐信： 来自教师和辅导员的推荐信能提供关于学生学术和个人特质的第一手信息。 + +面试： 一些学校提供面试的机会，可以进一步了解学生的动机、兴趣和沟通能力。 + +特殊才能或成就： 如果你有国际国内的大奖或是创立了非盈利组织，这些都是十分闪耀的亮点，可能会对你的申请产生重大的正面影响。 + +最后，不同学校和专业对GPA的重视程度可能不同，一些艺术和表演艺术专业可能会更注重作品集或试听表现，而一些研究型或理论密集的专业可能会更加关注学术成绩。 + +因此，虽然GPA重要，但它并不是决定性的。申请者应当充分利用申请的每一部分来展现自己的优势，使整体申请更具吸引力。 + +User +我现在会想着学习金融创业赚大钱，但实际有时会偷懒，打游戏，找者未来成大事现在专心“学金融”的借口偷懒学习学校 +ChatGPT +面对学习和课外活动（如打游戏）之间的平衡，很多人都会有挣扎。专注于长期目标的同时保持日常动力是一项挑战，但也是一项可以通过实践和策略来提高的技能。以下是一些建议来帮助你保持专注，并在追求未来的大目标时不会偏离轨道： + +制定明确的目标： + +写下你的长期目标（如成为金融创业成功者），然后设定短期可实现的目标（如每学期保持一定的GPA，完成某个金融项目）。 +用SMART原则（具体、可衡量、可达成、相关性和时限性）来设定目标。 +时间管理： + +创造一个学习计划，并包括休息和娱乐时间。这可以帮助你把游戏时间当作奖励，在完成一定的学习任务后才可以享受。 +使用时间管理的工具和应用程序，如番茄钟技术（Pomodoro Technique），这种技术通过25分钟专注学习后休息5分钟的方式来增强学习效率。 +自我监控： + +记录你每天如何使用时间，并诚实地评估你的学习和娱乐时间的分配是否合理。 +定期回顾和调整你的行为以符合你的长期目标。 +寻找激励： + +阅读金融领域的成功故事或参与相关的讲座和活动，以此作为灵感和动力。 +参加学校的金融俱乐部或找到志同道合的学习伙伴，这样可以在追求金融知识的同时获得社交的乐趣。 +保持健康的生活方式： + +确保充足的睡眠、健康的饮食和定期的运动，这些都有助于保持高效的学习效率和良好的精神状态。 +避免长时间的连续游戏，这可能会影响你的身心健康。 +自我反思： + +了解自己偷懒的根本原因。是否是因为学习内容难以理解，或是因为缺乏内在的学习动力？ +可能你需要更具体的金融知识应用场景，来激发你学习的兴趣，例如通过实际的金融模拟软件或参与学校的投资项目。 +正视挑战： + +面对学习上的挑战，而不是用“将来要成大事”来作为逃避现在努力的借口。 +如果有必要，寻求导师或辅导员的帮助来克服学习中遇到的问题。 + +# 023《社会运行的真相和逻辑》 + +1. 社会结构与层次 +社会结构指的是社会中不同元素之间的关系和排列方式。它包括社会的各种组织（如家庭、教育机构、企业、政府等）和社会地位（如阶级、职业、种族、性别等）。社会结构决定了资源（如财富、权力、教育等）的分配，这种分配通常是不平等的，从而产生了社会层次和阶级。 + +2. 文化与规范 +文化是社会中共享的信仰、价值观、习俗和行为规范。它包括语言、宗教、艺术、风俗等。文化为社会成员提供了一套行为和思考的框架，影响他们的行为和决策。社会规范是文化的一部分，指导人们如何在不同情境下行动和互动。 + +3. 权力与政治 +权力是社会中的核心概念，涉及对资源、人员和决策的控制。政治是关于权力的斗争和分配。不同的政治体系（如民主、专制、社会主义等）有不同的权力结构和分配方式。权力不仅存在于政府和公共机构中，也存在于私人组织、家庭乃至日常生活的各个方面。 + +4. 经济系统 +经济是社会运行的基础，涉及资源的生产、分配和消费。不同的经济系统（如资本主义、社会主义、混合经济等）有不同的组织方式和运行机制。经济活动不仅影响人们的物质生活，还影响社会结构、文化和政治。 + +5. 社会变迁 +社会是动态变化的。技术进步、经济发展、政治变革、文化演变等因素都会引起社会的变迁。社会变迁可以是渐进的，也可以是突然的（如革命或重大社会事件）。 + +6. 社会问题与冲突 +社会问题如贫困、不平等、歧视、犯罪等，是社会运行中不可避免的一部分。这些问题通常是复杂的，涉及多个因素的交互作用。社会冲突可能源于资源的竞争、不同群体之间的利益冲突或价值观的差异。 + +7. 个体与社会 +虽然社会是由个体组成的，但社会结构和文化对个体行为有重要影响。社会化过程（如家庭教育、学校教育、媒体等）塑造了个体的价值观、信仰和行为模式。同时，个体也能通过行动和创新影响社会。 + +总结 +社会运行是一个复杂的、多层次的、动态变化的过程。它受到经济、政治、文化、技术等多方面因素的影响。了解社会运行的真相和逻辑需要跨学科的视角和深入的分析。 + +# 024《异步追踪功能改进报告》 + +文章讨论了OCaml语言的`ppx_tracing`语法扩展，这是一个用于程序内省的工具。它允许通过`@trace`标注来收集程序运行时的性能追踪信息，并可以通过基于Perfetto的用户界面来可视化这些信息。 + +原先，`ppx_tracing`不支持异步代码追踪，这限制了其在现实世界程序中的应用。异步操作在OCaml中通过"deferreds"（类似JavaScript中的Promise）来处理。 + +文章通过递归函数`process_directory`展示了如何检查磁盘空间使用情况。使用`ppx_tracing`对此异步函数进行追踪时，输出的追踪结果会很混乱，因为它只捕获了分配新的deferred所需的时间，并不能追踪多个待处理的函数调用。 + +为了解决这个问题，实习生Sasha Hydrie改进了`ppx_tracing`，使其能与Async调度器集成，通过为每个异步函数调用分配唯一ID来追踪多个并发执行上下文。这使得追踪系统能够识别每个函数调用对应的执行上下文。 + +通过使用`@trace.async`标注，成功地改进了对异步函数的追踪。追踪结果现在能准确表示每次调用的持续时间及其并发执行的数量。即时事件也能根据活动的相关ID确定它们属于哪个调用。 + +此外，为同步函数调用添加了一个新的异步模式，它也会查询当前的相关ID，并动态地连接到一个父异步调用。这些改进导致`ppx_tracing`在真实世界的程序中得到了更广泛的应用，例如在Iron代码审查系统中，它帮助将服务器启动时间减少了50%。 + +文章最后提到了未来工作计划，包括将`ppx_tracing`与一个新的分布式追踪系统集成，以及对Async调度器本身进行更详细的追踪。Sasha的项目所做的改进显示了`ppx_tracing`在提供OCaml程序性能洞察方面的潜力，特别是对于那些使用异步操作的程序。 + + + +简化： +抱歉让您感到困惑，我将简化文章的内容： + +文章描述了一个名为`ppx_tracing`的工具，它用于帮助OCaml程序开发者了解他们的程序是如何运行的。这个工具最初不能很好地支持异步代码——也就是那些不是立即完成，而是稍后结果才会返回的代码。 + +一位实习生Sasha Hydrie改进了这个工具，使其能够追踪包括异步代码在内的更多类型的代码执行情况。Sasha的工作允许`ppx_tracing`通过使用特殊的标记（例如`@trace.async`）来追踪程序中同时发生的多个任务，并且能够清楚地显示这些任务是如何随时间推移而进行的。 + +这项改进使得`ppx_tracing`更加有用，因为它现在可以帮助开发者更好地理解并优化他们程序中的异步操作。例如，它已经被用来帮助一个名为Iron的内部代码审查系统将它的启动时间减半。 + +未来，团队计划将`ppx_tracing`与其他高级的追踪系统集成，以提供更深入的性能分析。总的来说，Sasha的工作极大地增强了这个工具的功能，使它成为一个在现实世界中非常实用的工具。 + +# 025《81条操盘经验》 + +81条滴血的经验，最核心的是选择成长+确定的行业龙头，五倍十倍股都是从翻倍股开始的，只投资翻倍潜力股。一年十倍不是梦。 + + +1、我入市八年后，发现我比一般股民表现四大突出的优点：刻苦，认真，钻研，求异。相信我能有实现跨进赢家大门槛的能力。 + +2、操作中，要不断地发现自我，改变自我，挑战自我，战胜自我。校正自己，永远比研究市场更重要！ + +3、我炒股十年后才发现，十年后才证实了炒股赚钱的指路明灯——天道酬勤。我每天在重复只做一件最简单而又最单调复杂的事情，即枯燥又无味，即寂寞无聊！只要能够坚持再坚持，忍耐再忍耐，在忍无可忍的时候，有再忍下去的毅力，始终如一不断地观察坚持记录，一天也不能遗漏，然后通过不断地归纳总结筛选，积累沉淀一定会有我意想不到的惊喜！ + +4、我炒股十五年后，终于诞生了我的炒股总方针：追求稳定，长久，持续地获利。 + +5、我知道的炒股知识并不少，我在发问自己：真正做到的又有多少？能够做好的又有多少？最后要问独树一帜的你有吗？十五年后的当时我肯定地说，有！可能是独一无二，我坚信！我坚持！ + +6、我炒股赚钱的工具——我的操作系统，多赚50%甚至翻倍，少赔10%止损， + +7、信号第一，铁的纪律。不受个人的情绪影响。它是从由战胜市场转变为顺应市场，由主动性交易转变为被动性交易，操作主要考虑在“应变”而不是在“预测”上。 + +8、抓住试盘，守株待兔。在常人看来这是愚蠢和原始的，但是真正让我炒股能够稳定，长久，持续地赚到钱的功夫还真是“坐功”。守株待兔关键是选择在哪些树下可以耐心等待，可能这个选择是几年来的心血结晶，心法相同技法却不同。 + +9、不听忽悠，眼见为实。我能要到手的铜，不要隔山的金子。 + +10、专家的话是两头堵，总是说如果……那么就会是……，一旦说对了就会炫耀自己看的多么准！一旦说错了他们就会说，我说过如果……那么……，现在是如果的条件没有满足，所以没有走出预想的行情是对的。我说，要是听专家的话炒股，想成为赢家我觉得简直是梦想。 + +11、我看图是打开图形向左看，先看月线再看周线，压缩图形看趋势，看方向不重价。 + +12、强势时不看阻力，弱势时不看支撑。 + +13、顺势加码要持股！逆势斩仓要离场！ + +14、我无意中发现当我赚到钱的一个规律，要想赚到钱，“必须要敢重仓”。我一般是在底部看好一只股票基本上就重仓，如果不是，顺势加码持股也就逐步达到重仓了。这样，一拨行情下来赚个20%——40%很容易。但是，过去是见到大盘上涨明朗后才开始敢大买，而涨了点就卖，大盘继续涨，就在热点板块跳来蹦去频繁地买卖赚点差价操作忙个不休，或者手中分散持股几只，这样到最后一般是赚了指数不赚钱。应该是在底部区域看准机会，必须重仓，敢于重仓这是改变自己的收益的关键问题。这就是看对时要有赚大钱的豪情，看错时要有及时止损的果断。 + +15、自从我有了选股“本事”之后，我是坚决果断地把鸡蛋就敢放在一个筐里。要是不敢放?!说明我还没有能力找到一个结实的铁筐，也可以说还没有能力走上赢家的路。所以我就每天看管好这一筐鸡蛋就行了，我一赢就赢个盆满钵盈，我一见要输马上干净利落不用几秒钟就能逃个精光。 + +16、事不过三。有效站稳或跌穿应该以三个交易日为衡量标准，才能够称之为有效。 + +17、庄家在高位连续拉高，目的就是派发和自救，这种认识我必须“固执”。 + +18、明星股，不管价格有多高都会有不怕死的追星族跟风，何为胆大？无知才胆大！ + +19、赢家第一想到的是风险，而输家第一想到的是赚钱！ + +20、赢家常套在低位，一旦反转就开始赚，输家常套在高位，一旦反转就开始赔。 + +21、要深知股价的高山上长眠的人都得的是什么病？我认为大部分得的是追热点病高烧不退而死在山顶上，少部分得的是贪婪病。 + +22、洗盘时的底部是逐步在抬高，而出货时底部逐步在降低。前者经常以大阴线方式吓唬人，后者则以大阳线在吸引人。 + +23、出权的股票走势不填权，空喊说什么再好的分红送转的花言巧语我都不听。 + +24、我拿手抓住庄家的试盘手法是：多点共振且一阳穿三线。 + +25、我拿手抓住庄家操作态势的是：横盘—挖坑—无量—填平—放量—横盘—拉升。 + +26、以上两条如果能够练就把宏观和微观达到完美的结合——就能是无招胜有招，我个人经验体会是起码需要10年的时间孜孜不倦地看盘磨练。 + +27、我喜欢炒到的股票不是黑马，因为黑马股我是骑不住。而是喜欢能炒到小火慢炖的股票，从底部当我重仓介入的股票走势是，进二退一，进三退二，进五退三，有时甚至是进五退八。虽然这是老牛拉破车——嘎吱的股票，但是我完全不再关心经济数据和政治事件的好坏，因为基本面对于我来说毫无用处。也从不和别人说起交易的事，因为我知道没有人能够说明白。每天我也无需关心大盘在200点之内上下跳动，那是股市的噪音，它除了挑战和折磨我的神经和影响我的情绪之外，对于我的操作没有任何正面作用。我坚持的结果是优哉游哉，资金在滚，一波行情下来，全年的盈利任务就轻松地完成了。 + +28、炒股最难的事是什么？我认为就是方向选对了之后，如何能够“坚持”！人的本性弱点是错误的寻求机会扩大化，而不是使利润继续扩大。若能做到五倍波段股，两次做下来就是25倍收益了。 + +29、真正能让我赚钱的是能够把握住趋势，忽略小的波动，热衷于局部战役的小打小闹获得点蝇头小利无法保证全局的胜利。 + +30、正让我赚不到钱或者亏损的原因仍然是心理因素，固执，贪婪与侥幸，失败就是偏爱自负的人，顽固的人和不自律的人，使我重复老犯过去的低级错误。 + +31、部分输钱的人，宁可赔钱也不肯承认自己有错误。死要面子钱受罪！ + +32、是必看无疑。该看哪本不该看哪本没人告诉我，读书走弯路是必然的。另外一本书不同人会读出不同的效果来。 + +33、认为股市里大多数人的行为往往是错误的。 + +34、大家都怕的事不一定可怕，大家都爱的事不一定可爱。 + +35、想赚钱就要反大众，反来反去把自己反到与庄家共舞的队伍中去了。不必在意他人的看法，只研究自己的对与错，力争成为少数人，你想错它能错到哪里？ + +36、我的十个“不”字和两个“否定”。我是不找黑马，不追热点，不找重组的，不炒送配的，不炒出权不填权的，不炒ST股，不听股评，不预测大盘走势，只看基本面，不看证券报刊杂志，否定波浪理论，否定炒股软件（两个否定指的是不适合我，他的存在就是具有合理性）。到了我这个炒股氛围不是需要追求再学更多的炒股知识，而是应该减肥，当我除掉自身那些我自己认为没有用的东西后，我觉得从此炒股的路子更加清晰，技术更加精湛，收益更加稳定。 + +37、我的三个“一”字。一生中我可能只用“抓住试盘，守株待兔”这一种方法炒股;一生中我可能谁的话我都不会听，就听自己操作系统的；一生中我必须固执地执行自己设定的止损点，即便是有时是错误我下次也不会改变这操作一理念。 + +38、我赞成不要用眼睛和耳朵炒股，要用脑子炒股的理念。就是不看不听（这里指的是股评家，咨询机构的评论），用脑子独立思考。 + +39、凡是股市最热闹人多的地方，不会有我的影子。 + +40、人多的地方我归纳有五多：吹牛的多，股评的多，骗子多，赔钱人多，新人多。 + +41、我是待在被庄家和大家遗忘的角落里，我认为在这个角落里是最好自守孤独的地方。脱离浮躁与喧嚣，心静，不至于做出仓促的决定。 + +42、当我能够感觉到孤独是快乐时，我觉得这是修来了的一种仙气。那断定我的心灵一定是强大的，心灵强大就不怕赚不到钱！ + +43、我炒股不是走大路而是走小道，爬山坳越溪流。做不正常的人，走不正常的路。走大家走过的路，往往是捡不到什么好果子了，老跟着别人屁股后是呼吸不到新鲜空气的。 + +44、股市永远都不缺机会，踏空一次，仅失去一次机会，被套一次就可能丧失很多机会。 + +45、能看到机会和很好地把握机会是两码事。无知是谈不到把握机会的，一知半解是把握不好机会的，只有真知才能融会贯通紧紧地抓住机会不放。 + +46、会买的是徒弟，会卖的是师傅，卖出后能耐心等待机会的是神仙。等待不是无事可做，不是犹豫不决，不是思前怕后，等待见到机会要有一剑封喉的勇气和果断，一箭不中全身而退。等待反映一个人的综合素质，学等待，善于等待。 + +47、行为决定了习惯，习惯决定了性格，性格决定了命运。少到“五多”的人堆里去，近墨者黑。慢慢克服自己的贪心，狂妄自大，喜欢别人的认同，不肯承认错误，说话不算数等一些的不良行为，后面的好事就会接踵而来水到渠成。 + +48、世间财富分配永远是二八分成，八二分成那是暂时的。二八定律的市场是为孤独寂寞有耐心的人们而开的！ + +49、炒股的秘笈实质是秘而不宣。同仁堂能把牛黄清心丸的配方公布于世吗？可口可乐的配方也是如此的。真正炒股高手是待在家里静悄悄地敲键盘赚大钱。 + +50、我相信大盘走势的预测结论，不会在细节上有吻合或者在炒作上有具体的指导意义。有三种人能够准确预测大盘走势，神仙，疯子和骗子。既然炒股软件也是人编造出来的，那么它的买卖点也是不可信的。 + +51、我相信这个世界上没有一种绝对有效分析股市的方式。如果有，股市早就不存在了。 + +52、炒股如果指望是看一看零敲碎打的书籍，听一听似是而非的股评，要不再加上一点秘诀，东学一招，西凑一式，合在一起就用，赢一把，两把是凭运气，赢十把、百把是遇到了牛市，可时间一长，遇到牛皮市和熊市就现了原形，仍然还是陷入亏损的泥潭里，这样的人往往表现无知者无畏。 + +53、理论和心理素质就像是内功，像是心法，而操作方法就像是武功的套路。内功浮燥，心法混乱，武功套路在关键时刻必然就会乱了套，跩了大跟头那是必然。内功雄厚扎实，心法清晰明确坚定，这样的人往往表现大智大勇。 + +54、炒股的心法是什么？你看！均线在骗，K线在骗，技术指标在骗，成交量在骗，业绩在骗，重组在骗，送配在骗，股评家在骗，报刊杂志，广播电视在骗，整个归结股市就是一个“骗”字。下跌当中老是补仓，越跌越补，越补越套，抄底过早而被深套，这些人就是想及早捡便宜没捡到犯了一个“贪”字，股票涨了不卖，越涨越是不卖，结果不是被急跌或者阴跌把自己的利润又给吐回去了，或者是追高，而被套死。整个归结就是一个“贪”字。骗子非常喜欢爱贪的人，爱贪的人没有不被骗的，这是一对幽灵终生陪伴你我，所以股市的心法就是认清两个字，一个是“骗”，一个是“贪”，只要是心法清晰，明确，坚定，这样的人在接招时永远是得心应手，井然有序。 + +55、炒股初级阶段经常是盲目崇拜。不是说向谁学就一定能学成，巴菲特不是好学的，何况股市里的假巴菲特太多了。尤其是读几年金融专业再出国打了个滚，根本就没有大资金炒中国股票的实战经验，把国内国外的东拼西凑，断章取义，生搬硬套，就敢写书夸夸其谈的毛手毛脚的小伙子多于牛毛。 + +56、我说赢家门前挂有“稳”字牌匾的有三道大门。第一道是稳赔，第二道是稳不赔不赚，第三道是稳赚，最后才能跨进赢家的大门，那是稳定，长久，持续地赚钱。没有5年以上是不能真正走进第二道门槛里的。没有10年以上，是不能稳定获利的。20年后，你可能在股市里为所欲为。但是我认为，时间跟人的炒股经验没有必然成正比例关系。股市不是说只涨岁数不涨记性的人以靠混年头就能来提款的。 + +57、你一旦发现自己常常输的是时间而不输钱时！这就告诉你，离赢家的门槛就不远了。 + +58、求人不如求己，这个挂在嘴边浅显易懂的道理在我炒股五年后才领会到真正的含义。这也说明自己太无知，国际歌词早就告诉的明明白白。 + +59、炒股是艺术不是科学，今天的成功经验也许过些时候就是失败的定律。今天的失败教训过些时候就又可能是成功的法宝。一句话：没准！主要是因为你正用，庄家有时就反用，你反用庄家就正用，尤其同一个炒股软件两家同时用效果更加明显，出现双赢局面那是偶而与侥幸。 + +60、炒股高手一定是具备有自己的交易系统，而且是有稳定的准确率。这个稳定性来源于：个人的无意识，意识到，做到，做好。这中间是由于坚持而形成了惯，惯又变成了融会贯通。整个过程是直觉，本能，无招，大成的过程。 + +61、一个人好的交易系统，是经过多年不断地在痛苦的思考，提炼，再思考，再提炼的循环过程。也就是时时在保养，年年在保养。一旦不保养就会失效的。62、好多人成不了高手是悟性不足，韧性不够所以成为不了赢家，也许是一辈子。63、想做高手是痛苦的，需要毅力，更是孤独的，因为高手每天都在否定自己而要适应市场64、没有既能在振荡市中赚钱又能在趋势行情中获利的交易系统。 + +65、一年分四季，各个季节需穿不同的衣服。我有三种选股方法，它们是适应在大盘的底部，中部和顶部。 + +66、看高手不要看他怎么赚钱，最好能够看到他是怎样应对输钱的，看他是怎样止损和止盈的。 + +67、我认为炒股其实并不简单！说简单的人，就好比看齐白石画虾，徐悲鸿画马就这么简单！看到了表面，看到了现象却没有看到本质。 + +68、要让我说炒股简单，我说有两点，一是请一位好老师，二就是勤奋。这就是师傅领进门，修行在个人。 + +69、炒股千万不要与人攀比，容易搞坏心情，只有认真反思自己，大彻大悟！有的对于别人来说是好机会，而对于自己可能就是陷阱，只赚属于自己的钱。是你的就是你的，不是你的，争着抢着夺着也白搭!看看自己的交割单就是自己的老师。 + +70、不要迷信那些夸夸其谈每周都能买到涨停板的人，其实他的业绩是一塌糊涂，赔的可能比谁都惨！ + +71、不要跟随天天在预测大盘走势的人，他一是故弄玄虚炫耀自己，二是他另有企图，背后干些偷鸡摸狗的事。 + +72、抄底就是炒人气崩溃，等到交易所门可罗雀，让人伤心绝望到极点的时候，营业厅每天只来那么几个人就可以大胆抄底了。所以，抄底就是门可罗雀，逃顶就是人满为患。准确率虽然相当高，可是大多数人就是做不到。为什么？因为都套的死死的，没有钱等待解套。 + +73、我认为股票市场不是国民经济的晴雨表。现在经济不好，不能买进，或是等到所有利空都去尽以后，再买也不迟。所以，大家在家等着看报纸，看电视，确定经济已经转好才开始买股票，我说这时已经晚了。我们应该做到在极度悲观的气氛中，乐观地重仓进场。 + +74、我最怕的是大盘阴跌和不跌，我最不怕的是暴跌。大盘非理性的暴跌和无病的大跌，就是低档介入赚钱的好机会，遇到此时千万不要把财神爷拒之门外。 + +75、我的两次5%理论。我知道抄底很难抄到最低点，一般我分两次进场抄底，第一次我认为可能是低点时以2——4成仓位杀进后，结果抄的不是底时，需再等待至少跌7%以上再买同等仓位，两次平均价离真正的底5%以内时我认为就算是高手了。同理，我两次卖出的平均价离真正的顶部5%以内时也认为是高手了。我是社会最底层的人做股票，没有关系背景，没有消息来源，买进、卖出不可能那么准确，我只能是估计一个区域，在安全区域可以买进，也许买进还会跌一些，在风险区域就要卖出，也许卖出之后还能涨很多。能够每次做到精准买进卖出是不现实的。 + +76、我一旦重仓发动攻击时，身边出现再诱人的股票我都不会动心。炒的股票一旦定下就要专一，往往笑到最后是我而不是那些朝三暮四追龙头抢热点当初嘲笑我的人。77、熊市是真正培养耐心的土壤！牛市往往会使人的野心膨胀。 + +78、我炒股的高兴与痛苦，不是因为我的股票上涨而高兴与下跌而痛苦，而是我规划设计自己的股票十天半月应该怎么走的大概率框架蓝图，虽然中间有好多意想不到的波动，结果股票基本上没有走出这个框架之外，这是我最高兴的，因为我能与庄家基本上想到一块去了。想不到一块时就是最痛苦的，我需赶快找原因调整操作策略。从来就不要自以为是，不自作多情。 + +79、股市有风险，但股市相对是“公正”的。公不公正就看你的眼力。 + +80、股市是天堂，但股市也是地狱。我想好多股友还是没有真正尝试到地狱是什么滋味，但是我觉得我是嚐到了。即便是有炒股丰富经验的人，如果生活经历不够丰富，也很可能在遭受一次下地狱惨痛的打击之后，甚至有永远要放弃炒股的念头！只有经历丰富的人真正尝试到了这种滋味后，再炒股业绩必有飞跃，这就是被击落有多深，反弹就有多高。 + +81、炒股是谋事在人，成事在天。抓住低估+成长+确定=翻倍成功！ + +# 026《行业分析师的作用》 + +行业分析师的作用：行业分析师提供关于特定行业的深入分析，包括市场趋势、公司财务状况、竞争格局等。他们的目的是为基金经理或投资者提供信息，帮助他们做出更明智的投资决策。 + +公募基金和分析师的关系：即使是资金量巨大的公募基金，也可能在市场波动、选股策略、成本控制等方面遇到挑战。即使有优秀的行业分析师，也不能保证投资总是盈利，因为市场有很多不可预测的因素。 + +基本面分析的局限性：基本面分析着重于公司的财务健康和业务模型。然而，行业分析师可能由于过于关注基本面而忽视了市场情绪和宏观经济等因素，这可能导致他们的预测与市场实际走势不符。 + +基本面与技术面的冲突：在投资决策中，基本面分析（如财务数据、行业趋势）和技术分析（基于价格和交易量的图表分析）可能会出现分歧。平衡这两者是一个挑战，因为过分侧重任何一方都可能导致错失机会或承担额外风险。 + +行业分析师的主观性：虽然行业分析师试图提供客观的分析，但他们的判断和预测仍然包含主观成分。理解和平衡这种主观性与市场客观情况之间的关系是关键。 + +# 027《高税效》 + +"税效率"是指在遵守税法的前提下，通过各种方法和策略来尽量减少税务负担。这可以通过选择税率较低的投资产品、利用税收优惠账户，或者合理安排资产和收入来实现。无论是个人还是企业，提高税效率都有助于保留更多的收入或资本，从而优化财务状况。 + diff --git a/financial_programs/__init__.py b/financial_programs/__init__.py new file mode 100644 index 0000000..3c3421e --- /dev/null +++ b/financial_programs/__init__.py @@ -0,0 +1,15 @@ +"""Financial program utilities covering derivatives, portfolios, and fixed income.""" + +from .option_pricing import black_scholes_price, black_scholes_greeks +from .portfolio_analysis import Portfolio +from .fixed_income import bond_price, yield_to_maturity, duration, convexity + +__all__ = [ + "black_scholes_price", + "black_scholes_greeks", + "Portfolio", + "bond_price", + "yield_to_maturity", + "duration", + "convexity", +] diff --git a/financial_programs/fixed_income.py b/financial_programs/fixed_income.py new file mode 100644 index 0000000..4902de7 --- /dev/null +++ b/financial_programs/fixed_income.py @@ -0,0 +1,98 @@ +"""Fixed income analytics.""" +from __future__ import annotations + + +def bond_price( + face_value: float, + coupon_rate: float, + periods: int, + discount_rate: float, + frequency: int = 2, +) -> float: + """Present value of a standard coupon bond.""" + if periods <= 0: + raise ValueError("periods must be positive") + if frequency <= 0: + raise ValueError("frequency must be positive") + coupon = face_value * coupon_rate / frequency + price = 0.0 + for period in range(1, periods + 1): + price += coupon / (1 + discount_rate / frequency) ** period + price += face_value / (1 + discount_rate / frequency) ** periods + return price + + +def yield_to_maturity( + price: float, + face_value: float, + coupon_rate: float, + periods: int, + frequency: int = 2, + initial_guess: float = 0.05, + tolerance: float = 1e-6, + max_iterations: int = 100, +) -> float: + """Solve for the yield to maturity using Newton-Raphson.""" + if price <= 0 or face_value <= 0: + raise ValueError("price and face_value must be positive") + if periods <= 0: + raise ValueError("periods must be positive") + if frequency <= 0: + raise ValueError("frequency must be positive") + + coupon = face_value * coupon_rate / frequency + ytm = initial_guess + for _ in range(max_iterations): + denom = 1 + ytm / frequency + price_guess = 0.0 + derivative = 0.0 + for period in range(1, periods + 1): + discount = denom ** period + price_guess += coupon / discount + derivative -= (period * coupon) / (discount * denom) + price_guess += face_value / denom ** periods + derivative -= (periods * face_value) / (denom ** (periods + 1)) + + diff = price_guess - price + if abs(diff) < tolerance: + return ytm + ytm -= diff / derivative + raise RuntimeError("yield_to_maturity did not converge") + + +def duration( + price: float, + face_value: float, + coupon_rate: float, + periods: int, + yield_rate: float, + frequency: int = 2, +) -> float: + """Macaulay duration of a bond.""" + coupon = face_value * coupon_rate / frequency + weighted_sum = 0.0 + denom = 1 + yield_rate / frequency + for period in range(1, periods + 1): + cash_flow = coupon if period < periods else coupon + face_value + pv = cash_flow / denom ** period + weighted_sum += period * pv + return weighted_sum / price + + +def convexity( + price: float, + face_value: float, + coupon_rate: float, + periods: int, + yield_rate: float, + frequency: int = 2, +) -> float: + """Calculate the convexity of a bond.""" + coupon = face_value * coupon_rate / frequency + total = 0.0 + denom = 1 + yield_rate / frequency + for period in range(1, periods + 1): + cash_flow = coupon if period < periods else coupon + face_value + pv = cash_flow / denom ** period + total += period * (period + 1) * pv + return total / (price * denom * denom) diff --git a/financial_programs/option_pricing.py b/financial_programs/option_pricing.py new file mode 100644 index 0000000..fd1fae3 --- /dev/null +++ b/financial_programs/option_pricing.py @@ -0,0 +1,141 @@ +"""Tools for derivative pricing and sensitivities.""" +from __future__ import annotations + +import math +from dataclasses import dataclass +from typing import Dict + + +def _norm_cdf(x: float) -> float: + """Return the standard normal cumulative distribution.""" + return 0.5 * (1.0 + math.erf(x / math.sqrt(2.0))) + + +def _norm_pdf(x: float) -> float: + """Return the standard normal probability density.""" + return (1.0 / math.sqrt(2.0 * math.pi)) * math.exp(-0.5 * x * x) + + +def _validate_option_type(option_type: str) -> str: + opt = option_type.lower() + if opt not in {"call", "put"}: + raise ValueError("option_type must be 'call' or 'put'") + return opt + + +@dataclass(frozen=True) +class BlackScholesInputs: + """Container for Black-Scholes option inputs.""" + + spot: float + strike: float + time_to_maturity: float + risk_free_rate: float + volatility: float + dividend_yield: float = 0.0 + + def validate(self) -> None: + if self.spot <= 0 or self.strike <= 0: + raise ValueError("Spot and strike must be positive") + if self.time_to_maturity < 0: + raise ValueError("Time to maturity cannot be negative") + if self.volatility <= 0: + raise ValueError("Volatility must be positive") + + +def _d1_d2(inputs: BlackScholesInputs) -> tuple[float, float]: + inputs.validate() + if inputs.time_to_maturity == 0: + raise ValueError("Time to maturity must be positive for continuous pricing") + sqrt_t = math.sqrt(inputs.time_to_maturity) + log_ratio = math.log(inputs.spot / inputs.strike) + d1 = ( + log_ratio + + (inputs.risk_free_rate - inputs.dividend_yield + 0.5 * inputs.volatility**2) + * inputs.time_to_maturity + ) / (inputs.volatility * sqrt_t) + d2 = d1 - inputs.volatility * sqrt_t + return d1, d2 + + +def black_scholes_price( + spot: float, + strike: float, + time_to_maturity: float, + risk_free_rate: float, + volatility: float, + option_type: str = "call", + dividend_yield: float = 0.0, +) -> float: + """Return the Black-Scholes price for a European option.""" + option_type = _validate_option_type(option_type) + inputs = BlackScholesInputs( + spot=spot, + strike=strike, + time_to_maturity=time_to_maturity, + risk_free_rate=risk_free_rate, + volatility=volatility, + dividend_yield=dividend_yield, + ) + + if time_to_maturity == 0: + intrinsic = max(0.0, spot - strike) if option_type == "call" else max(0.0, strike - spot) + return intrinsic + + d1, d2 = _d1_d2(inputs) + discounted_spot = spot * math.exp(-dividend_yield * time_to_maturity) + discounted_strike = strike * math.exp(-risk_free_rate * time_to_maturity) + + if option_type == "call": + price = discounted_spot * _norm_cdf(d1) - discounted_strike * _norm_cdf(d2) + else: + price = discounted_strike * _norm_cdf(-d2) - discounted_spot * _norm_cdf(-d1) + return price + + +def black_scholes_greeks( + spot: float, + strike: float, + time_to_maturity: float, + risk_free_rate: float, + volatility: float, + dividend_yield: float = 0.0, +) -> Dict[str, float]: + """Return the primary Greeks for a European call option.""" + inputs = BlackScholesInputs( + spot=spot, + strike=strike, + time_to_maturity=time_to_maturity, + risk_free_rate=risk_free_rate, + volatility=volatility, + dividend_yield=dividend_yield, + ) + if time_to_maturity == 0: + raise ValueError("Greeks are undefined at expiration for this implementation") + + d1, d2 = _d1_d2(inputs) + sqrt_t = math.sqrt(time_to_maturity) + discounted_spot = spot * math.exp(-dividend_yield * time_to_maturity) + discounted_strike = strike * math.exp(-risk_free_rate * time_to_maturity) + + delta_call = math.exp(-dividend_yield * time_to_maturity) * _norm_cdf(d1) + gamma = ( + math.exp(-dividend_yield * time_to_maturity) + * _norm_pdf(d1) + / (spot * volatility * sqrt_t) + ) + vega = discounted_spot * _norm_pdf(d1) * sqrt_t + theta_call = ( + -discounted_spot * _norm_pdf(d1) * volatility / (2.0 * sqrt_t) + - risk_free_rate * discounted_strike * _norm_cdf(d2) + + dividend_yield * discounted_spot * _norm_cdf(d1) + ) + rho_call = time_to_maturity * discounted_strike * _norm_cdf(d2) + + return { + "delta": delta_call, + "gamma": gamma, + "theta": theta_call, + "vega": vega, + "rho": rho_call, + } diff --git a/financial_programs/portfolio_analysis.py b/financial_programs/portfolio_analysis.py new file mode 100644 index 0000000..84fd0eb --- /dev/null +++ b/financial_programs/portfolio_analysis.py @@ -0,0 +1,130 @@ +"""Portfolio analytics utilities.""" +from __future__ import annotations + +import math +from dataclasses import dataclass, field +from typing import List, Sequence + + +@dataclass +class Portfolio: + """A simple portfolio model supporting common performance measures.""" + + weights: Sequence[float] + expected_asset_returns: Sequence[float] + covariance: Sequence[Sequence[float]] + risk_free_rate: float = 0.0 + _normalized_weights: List[float] = field(init=False, repr=False) + + def __post_init__(self) -> None: + self._normalized_weights = self._normalize(self.weights) + self._validate_dimensions() + + @staticmethod + def _normalize(weights: Sequence[float]) -> List[float]: + weights_list = [float(w) for w in weights] + if not weights_list: + raise ValueError("Portfolio must contain at least one asset") + total = sum(weights_list) + if total == 0: + raise ValueError("Sum of weights cannot be zero") + return [w / total for w in weights_list] + + def _validate_dimensions(self) -> None: + n = len(self._normalized_weights) + if len(self.expected_asset_returns) != n: + raise ValueError("Expected returns must match number of weights") + if len(self.covariance) != n: + raise ValueError("Covariance matrix must match number of weights") + for row in self.covariance: + if len(row) != n: + raise ValueError("Covariance matrix must be square") + + @property + def weights_vector(self) -> List[float]: + """Return the normalized weights of the portfolio.""" + return list(self._normalized_weights) + + def expected_return(self) -> float: + return sum(w * r for w, r in zip(self._normalized_weights, self.expected_asset_returns)) + + def variance(self) -> float: + n = len(self._normalized_weights) + total = 0.0 + for i in range(n): + for j in range(n): + total += ( + self._normalized_weights[i] + * self._normalized_weights[j] + * float(self.covariance[i][j]) + ) + return total + + def standard_deviation(self) -> float: + return math.sqrt(self.variance()) + + def sharpe_ratio(self) -> float: + excess_return = self.expected_return() - self.risk_free_rate + deviation = self.standard_deviation() + if deviation == 0: + raise ValueError("Standard deviation is zero; Sharpe ratio undefined") + return excess_return / deviation + + def rebalance(self, target_weights: Sequence[float]) -> None: + self._normalized_weights = self._normalize(target_weights) + self._validate_dimensions() + + def marginal_contribution_to_risk(self) -> List[float]: + n = len(self._normalized_weights) + contributions: List[float] = [] + variance = self.variance() + if variance == 0: + return [0.0 for _ in range(n)] + std_dev = math.sqrt(variance) + for i in range(n): + cov_sum = 0.0 + for j in range(n): + cov_sum += self._normalized_weights[j] * float(self.covariance[i][j]) + contributions.append(cov_sum / std_dev) + return contributions + + def value_at_risk(self, confidence_level: float, horizon: float = 1.0) -> float: + if not 0 < confidence_level < 1: + raise ValueError("confidence_level must be between 0 and 1") + z_score = _inverse_normal_cdf(1 - confidence_level) + mean = self.expected_return() * horizon + deviation = self.standard_deviation() * math.sqrt(horizon) + return mean + z_score * deviation + + +def _inverse_normal_cdf(p: float) -> float: + """Approximate the inverse CDF using Acklam's rational approximation.""" + if not 0 < p < 1: + raise ValueError("p must be between 0 and 1") + a = [-3.969683028665376e01, 2.209460984245205e02, -2.759285104469687e02, + 1.383577518672690e02, -3.066479806614716e01, 2.506628277459239e00] + b = [-5.447609879822406e01, 1.615858368580409e02, -1.556989798598866e02, + 6.680131188771972e01, -1.328068155288572e01] + c = [-7.784894002430293e-03, -3.223964580411365e-01, -2.400758277161838e00, + -2.549732539343734e00, 4.374664141464968e00, 2.938163982698783e00] + d = [7.784695709041462e-03, 3.224671290700398e-01, 2.445134137142996e00, + 3.754408661907416e00] + + plow = 0.02425 + phigh = 1 - plow + + if p < plow: + q = math.sqrt(-2 * math.log(p)) + return (((((c[0] * q + c[1]) * q + c[2]) * q + c[3]) * q + c[4]) * q + c[5]) / ( + ((((d[0] * q + d[1]) * q + d[2]) * q + d[3]) * q + 1) + ) + if phigh < p: + q = math.sqrt(-2 * math.log(1 - p)) + return -(((((c[0] * q + c[1]) * q + c[2]) * q + c[3]) * q + c[4]) * q + c[5]) / ( + ((((d[0] * q + d[1]) * q + d[2]) * q + d[3]) * q + 1) + ) + q = p - 0.5 + r = q * q + return (((((a[0] * r + a[1]) * r + a[2]) * r + a[3]) * r + a[4]) * r + a[5]) * q / ( + (((((b[0] * r + b[1]) * r + b[2]) * r + b[3]) * r + b[4]) * r + 1) + )