Real-time stock trading program using a basic mean reversion algorithm

A profitable mean reversion stock trading algorithm

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.

Developed a simulation framework to model financial markets and evaluate algorithmic trading strategies. The system simulates stock prices using Geometric Brownian Motion (GBM) and tests strategies like Mean Reversion, Trend Following, and Weighted Trend Following to optimize returns.

Python program that compares the profit made with the traditional Buy and Hold strategy with a Mean reversion/Moving Average trading algorithm to conclude which option would have being superior given the outcome of the two. In the end it showed that for the specific stock in question, Blackberry Ltd (BB), Buying and holding would be the most profitable strategy.

An algorithmic trading bot that uses mean reversion on a stock's chart to buy and sell shares for a profit.

This automated trading bot uses a mean-reversion strategy, trading a specified stock based on statistical anomalies detected in the price deviation from an algorithmic analysis, considering market open and close times.

This repository contains the implementation of a mean reversion trading strategy using historical stock price data. The strategy is developed and backtested using Python and the Backtrader library. This project aims to demonstrate the process of building, testing, and optimizing an algorithmic trading strategy.