Option Trading Strategy

PythonPython
Quantitative TradingQuantitative Trading
Options TradingOptions Trading
Algorithmic TradingAlgorithmic Trading
Risk Management
Time-Series Analysis
Financial EngineeringFinancial Engineering
BacktestingBacktesting
DerivativesDerivatives
Alpha GenerationAlpha Generation
Option Trading Strategy

This project implements a short-horizon options trading strategy designed to exploit intraday and short-term volatility dislocations in Indian index derivatives.

Over a 16-day live execution window, the strategy scaled capital from ₹21,000 to ₹4.7L, achieving an 88% win rate and a Sortino Ratio greater than 4.0, demonstrating strong risk-adjusted performance under high-frequency trading conditions.

The project reflects a practical implementation of quantitative trading principles, including signal generation, risk management, and performance evaluation.

Features

  • •Volatility Dislocation Capture: Identifies short-term inefficiencies in options pricing
  • •Structured Gamma Exposure: Positions designed to benefit from rapid price movement
  • •Rule-Based Execution: Entry and exit driven by predefined signals
  • •Strict Risk Management: Position sizing, stop-loss, and loss containment rules
  • •Momentum + Volatility Signals: Combines directional and volatility-based indicators
  • •Intraday / Short-Term Focus: Optimized for high-frequency trading windows
  • •Drawdown Control: Prioritizes capital preservation over aggressive exposure
  • •Performance Tracking: Evaluates win rate, PnL, and risk-adjusted returns
  • •Adaptive Execution: Adjusts to changing market volatility conditions
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