This script implements a mean reversion strategy for a given stock. It calculates the z-scores for the stock's price and generates entry and exit signals based on predefined thresholds. The script also performs a backtest on the strategy and visualizes the returns.

Comparative study between statistical and machine learning based strategies for high frequency trading of assets

Repository for the Trading Team Project based on Mean Reversion for QFin Semester 1 2022. Developed by Jake Lyell

Quick calculation for profit loss of trades.

Algorithmic trading strategies for pairs and basket trading in cross-commodity markets

SwitchGain is a Python-based algorithmic trading project implementing Momentum and Mean Reversion strategies on stock data. It automates signal generation using technical indicators (RSI, Bollinger Bands) and provides performance analytics.

This indicator is a modified version of SteverSteves's original work, enhanced by Erika Barker. It visually represents asset price movements in terms of standard deviations from a Hull Moving Average (HMA), commonly known as a Z-Score.

Mean Reversion Long Daily Strategy for VOO etf

An exposition of a simple pairs trading strategy on two stocks (Bajaj Finserv and Indian Bank) in the Nifty500, at the one-minute time frequency, in order to demonstrate some of the core ideas of statistical arbitrage strategies.

Pair trading strategy integrates multiple components, including technical analysis indicators, machine learning models, and risk management techniques.

OpenAI analysis of calculated Mean Reversion data for given [STOCK] including related news sentiment analysis

My Solutions to Trading Algorithms Course Practical Assignments

Backtesting algorithmic trading strategies on the PHI/WSOL pair (08.17-08.18) using z-score-based mean reversion signals and grid search optimization. Developed by David Yemchuk for Peanut Trade as a demonstration of motivation and commitment.