Building a Backtesting Engine

This project uses python for data acquisition and preprocessing, and the backtesting engine has been built with C++. The engine fetches historical stock data from Yahoo Finance. The data is then processed and includes adjustments for stock splits and dividends.

Some key features:

1. Simulation & Analysis: The c++ backtesting engine simulates trading strategies and computes portfolio values, daily returns, and implementing portfolio rebalancing based on predefined target allocations.

2. Risk Metrics: Volatility, maximum drawdown and sharpe ratio have been calculated

3. Scalability: It handles portfolios of varying sizes

Here is an example result for a portfolio consisting of equity stocks (AAPL, MSFT, GOOGL, AMZN, META, TSLA, NVDA, NFLX, ADBE, PYPL)

Dependencies:

1. Python Libraries - yfinance, pandas, numpy, datetime

2. C++ libraries - standard C++ libraries for file handling, data structures and numerical computations.

Access the repo here - https://github.com/sanjanarajesh-ctrl/Backtesting_Engine