[harrison_kreps] Update new lecture on Bayesian Learning and Speculative Behavior#650
[harrison_kreps] Update new lecture on Bayesian Learning and Speculative Behavior#650HumphreyYang merged 22 commits intomainfrom
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Pull Request Overview
This PR adds a new lecture on Morris' 1996 paper about speculative behavior and Bayesian learning, building upon the Harrison-Kreps model. The lecture demonstrates how traders with heterogeneous prior beliefs use Bayes' Law to update beliefs about dividend streams, leading to speculative premiums when no global optimist exists.
- Introduces Morris' extension of Harrison-Kreps model with Bayesian learning
- Implements computational methods for multi-trader equilibrium pricing
- Provides examples demonstrating speculative premiums and belief convergence
Reviewed Changes
Copilot reviewed 4 out of 4 changed files in this pull request and generated 6 comments.
| File | Description |
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| lectures/morris_learn.md | New lecture file covering Morris' model with mathematical framework, Python implementations, and exercises |
| lectures/harrison_kreps.md | Updated metadata format and corrected equation typo in pessimistic beliefs section |
| lectures/_toc.yml | Added morris_learn to table of contents after harrison_kreps |
| lectures/_static/quant-econ.bib | Added bibliography entries for Morris1996, Harsanyi, Miller, and Jeffreys papers |
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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This lecture looks very nice! Small comments: Is this correct English? "Morris [1996] evidently abandons the Harsanyi doctrine more blightly than Harrison and Kreps had." (What does blightly mean?) Also, "manifold" is used from the start of the lecture and I'm not sure what it means. Perhaps a wiki link would help? For matplotlib, please use the OOP style from the manual (fig, ax = ...) Thanks @HumphreyYang @mmcky I notice that definitions and theorems use the same blue color. They are probably the most common combination. Is there a spare color we could assign to definitions? (I would be in favor of dropping the bell at the far left, since it's a bit unusual in this context.) |
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It looks great @HumphreyYang . Many thanks. Super nice lecture. |
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Many thanks @jstac! |
This PR adds a new lecture on Morris' paper on speculative behavior and bayes learning.