Backtest Expert — Indian Market Strategy Validation

Core Philosophy

"Find strategies that break the least, not profit the most."

A strategy that survives stress testing across multiple market regimes, transaction cost assumptions, and parameter perturbations is far more valuable than one that shows spectacular returns on a single optimized parameter set. Overfitting is the silent killer of trading accounts.

6-Step Backtesting Workflow

Step 1: State the Hypothesis (1 Sentence Edge)

Before writing a single line of code, articulate why the strategy should work in one clear sentence.

Good hypotheses:

• "Stocks that gap up >3% on above-average volume after consolidation tend to continue higher for 2-5 days on NSE."
• "Nifty 50 stocks that revert to their 20-day mean after RSI drops below 30 produce positive expectancy within 5 trading sessions."
• "Selling strangles on Bank Nifty on Wednesday expiry with delta <0.15 captures time decay faster than gamma risk materializes."

Bad hypotheses:

• "This indicator combination looks good on the chart." (no edge articulated)
• "I saw someone on Twitter making money with this." (no reasoning)

Ask yourself:

• What behavioral or structural edge am I exploiting?
• Why would this edge persist? (Structural > Behavioral > Statistical)
• Who is on the other side of this trade, and why are they losing?

Step 2: Codify Rules (No Ambiguity)

Every rule must be binary — a computer must be able to execute it without interpretation.

Rule Categories

India-Specific Rules to Consider

• Circuit limits: Stocks hitting upper/lower circuit cannot be exited. Define handling.
• F&O ban period: Stocks crossing 95% MWPL cannot add fresh F&O positions.
• T+1 settlement: Cash equity settles next trading day (changed from T+2 in 2023).
• Pre-open session: 9:00-9:08 AM orders, 9:08-9:15 AM matching. Define if you use pre-open.
• Muhurat trading: Special Diwali session — include or exclude?
• Corporate actions: Adjust for splits, bonuses, dividends, rights issues.

Step 3: Run Initial Backtest

Minimum Requirements

Indian Market Regimes to Cover

Key Metrics to Record

Returns: CAGR, total return, monthly returns distribution
Risk: Max drawdown, average drawdown, drawdown duration, Calmar ratio
Efficiency: Sharpe ratio (use 6% risk-free for India), Sortino ratio
Trade quality: Win rate, avg win/loss, profit factor, expectancy per trade
Consistency: % profitable months, worst month, longest losing streak

Step 4: Stress Test (Spend 80% of Your Time Here)

This is where most backtests fail — and where the real value lies.

4a. Parameter Sensitivity

Perturb every parameter by +/-20% and check if performance degrades gracefully or collapses.

Rule of thumb: If the strategy only works with exact parameter values, it is overfit. You want a "plateau" of profitability, not a "peak."

4b. Execution Friction (India-Specific Costs)

Apply realistic transaction costs:

Total round-trip cost estimates:

• Delivery large-cap: ~0.3-0.5%
• Intraday large-cap: ~0.1-0.2%
• F&O (options): ~0.15-0.4%
• Small-cap delivery: ~0.5-1.0% (wider spreads)

4c. Time Robustness

• Split data into 3-year rolling windows. Is the strategy profitable in each?
• Check year-by-year returns. Is any single year driving total performance?
• Remove the best month. Is the strategy still positive?

4d. Sample Size Validation

• Minimum 30 trades for any statistical claim (even this is weak)
• 100+ trades: Moderate confidence
• 200+ trades: Good confidence
• Use the t-test: Is average trade return significantly different from zero?

Step 5: Out-of-Sample Validation (Walk-Forward Analysis)

Never skip this step.

Walk-Forward Method for Indian Markets

1. In-sample period: Train on 5 years of data (e.g., 2015-2019)
2. Out-of-sample period: Test on next 1-2 years (e.g., 2020-2021)
3. Roll forward: Move window, retrain on 2016-2020, test on 2021-2022
4. Combine: Aggregate all out-of-sample periods for true performance estimate

Walk-Forward Efficiency (WFE):

WFE = Out-of-Sample Return / In-Sample Return

• WFE > 50%: Good — strategy generalizes
• WFE 30-50%: Acceptable — some overfitting present
• WFE < 30%: Poor — likely overfit

Paper Trading Validation

Before deploying capital, paper trade for at least:

• 30 trades minimum
• 2 months minimum
• Cover at least one volatile period (expiry week, results season, RBI policy)

Step 6: Evaluate Results (Deploy / Refine / Abandon)

Use the evaluation script to get an objective score:

python3 evaluate_backtest.py \
  --total-trades 150 \
  --win-rate 62 \
  --avg-win-pct 1.8 \
  --avg-loss-pct 1.2 \
  --max-drawdown-pct 15 \
  --years-tested 8 \
  --num-parameters 3 \
  --slippage-tested

Decision Framework