Options Trading Backtest Engine Development
Budget: ₹1,500 – ₹12,500 INR
Backtest Engine Requirements:
• Users should be able to input predefined options strategies (Straddles, Strangles, Iron Condor, etc.).
• The engine should fetch historical options data (Open, High, Low, Close, IV, OI) for different strikes and expiries.
• It should simulate trade execution based on historical prices, including entry/exit conditions.
• Performance metrics such as P&L, max drawdown, win rate, and Sharpe ratio should be displayed.
• Backtest results should be generated in a report format with charts and key statistics.
• The system should support adjustments during the backtest, like stop-loss, profit booking, or position rolling.
• The engine should handle slippage, brokerage, and margin calculations.
Tech Requirements (Preferred, Open to Suggestions):
• Backend: Python (Django/Flask) or Node.js
• Database: PostgreSQL / MongoDB
• Data Source: NSE/Broker API (Zerodha, Angel One, Fyers, etc.) or any alternative for historical options data.
If interested, please share:
1. Your experience with building backtest engines.
2. Your approach to fetching and processing historical options data.
3. Estimated cost and timeline.
Looking forward to working with skilled developers!
• Users should be able to input predefined options strategies (Straddles, Strangles, Iron Condor, etc.).
• The engine should fetch historical options data (Open, High, Low, Close, IV, OI) for different strikes and expiries.
• It should simulate trade execution based on historical prices, including entry/exit conditions.
• Performance metrics such as P&L, max drawdown, win rate, and Sharpe ratio should be displayed.
• Backtest results should be generated in a report format with charts and key statistics.
• The system should support adjustments during the backtest, like stop-loss, profit booking, or position rolling.
• The engine should handle slippage, brokerage, and margin calculations.
Tech Requirements (Preferred, Open to Suggestions):
• Backend: Python (Django/Flask) or Node.js
• Database: PostgreSQL / MongoDB
• Data Source: NSE/Broker API (Zerodha, Angel One, Fyers, etc.) or any alternative for historical options data.
If interested, please share:
1. Your experience with building backtest engines.
2. Your approach to fetching and processing historical options data.
3. Estimated cost and timeline.
Looking forward to working with skilled developers!