This Python project is designed for backtesting trading strategies using historical data from the Indian Stocks Market, specifically sourced from Finvasia Broker (Shoonya Broker). The entire code is structured using object-oriented programming (OOP) principles, ensuring a clean and modular design.
- Backtesting of trading strategies using historical data (Open, High, Low, Close, Volume) for Indian Stocks Market.
- Utilizes OOP's concepts for a modular and maintainable codebase.
- Incorporates sophisticated statistical analysis for trade generation and trade life.
- Integrates popular financial indicators like RSI, MACD, SMA, EMA, etc., using third-party libraries.
- Fetches historical data from Finvasia Broker (Shoonya Broker).
- Saves detailed trade statistics, including MTM, best profit/loss, and various metrics.
- Stock.Indicators.Python List of third-party libraries used for financial indicators.
The backtesting results are summarized in the results/ directory. Key metrics include:
Probability of Win Trade Probability of Loss Trade Total Return(s) Point Total Point Lost (Point) Total Point Earned (Point) Total Trades Total Loss Trades Total Profit Trades
Metrics Explanation: Executed trade Analysis: The number of trades executed during backtesting. Total Trades: The total number of trades considered in the analysis. Max Profit: The maximum profit achieved in any single trade. Max Loss: The maximum loss incurred in any single trade. Profit/Loss Ratio: The ratio of winning trades to losing trades. Total Point Gained: The total points gained across all trades. Total Return: The total return, which is the sum of profits and losses. Loss Point: The total points lost across all trades. Max Profit: The maximum point gain in any single trade. Max Loss: The maximum point loss in any single trade.
If you are interested in collaborating or need assistance with algorithmic trading strategies, feel free to reach out.