Indian options backtesting is the testing of options strategies against historical NSE options data, accounting for the things that make options uniquely hard: weekly expiry cycles, fixed lot sizes, time decay, and slippage across multiple legs. A backtest that ignores these produces P&L that evaporates in live trading.

This page explains how to backtest NSE options strategies correctly and how alphabench does it with AI agents on the open-source RaptorBT engine. For the index-specific deep dive, see BANKNIFTY options backtesting.

What you can backtest

  • Vertical spreads: bull/bear call and put spreads.
  • Volatility structures: long/short straddles and strangles.
  • Range structures: iron condors and related multi-leg trades.
  • On index options (NIFTY, BANKNIFTY) and single-stock options.

Why Indian options backtesting is hard

  • Expiry cycles: weekly and monthly expiries drive predictable decay and volatility patterns that must be modelled explicitly.
  • Lot sizes: fixed contract lots constrain sizing and rounding.
  • Multi-leg slippage: every leg has its own spread; entering/exiting a four-leg condor compounds cost.
  • Time decay (theta): holding period and expiry distance dominate short-option P&L.
  • Liquidity: far-OTM strikes are thin; assuming mid-price fills is unrealistic.

Modelling costs correctly

Each leg incurs brokerage, STT, exchange charges, SEBI fees, GST, and stamp duty, plus bid-ask slippage. alphabench's options tooling applies these per leg so the reported P&L reflects what's actually achievable.

Validate the edge

Options edges are especially prone to overfitting because there are many strikes, expiries, and parameters to tune. Use walk-forward and Monte Carlo validation and follow the Best Practices checklist.

How alphabench backtests options for you

Describe an options idea in Strategy Chat. AI agents select strikes and expiries, construct the multi-leg structure, backtest it on NSE options data with realistic per-leg costs through RaptorBT, and validate robustness. The Options Spreads guide and Options Strategies guide cover the workflow end-to-end, and you can move validated ideas to paper options trading.

Key takeaways

  • Indian options backtesting must model expiry cycles, lot sizes, per-leg slippage, and decay.
  • Per-leg cost modelling is essential for realistic options P&L.
  • Options strategies overfit easily; always validate out-of-sample.
  • alphabench backtests NSE options strategies with AI agents on RaptorBT.