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NIFTY24,318.60▲ 0.84%BANKNIFTY52,104.25▲ 1.12%FINNIFTY24,890.10▼ 0.31%RELIANCE2,945.70▲ 0.56%TCS4,102.35▼ 0.22%HDFCBANK1,688.90▲ 0.93%INFY1,876.40▲ 0.41%SENSEX79,943.00▲ 0.78%NIFTY24,318.60▲ 0.84%BANKNIFTY52,104.25▲ 1.12%FINNIFTY24,890.10▼ 0.31%RELIANCE2,945.70▲ 0.56%TCS4,102.35▼ 0.22%HDFCBANK1,688.90▲ 0.93%INFY1,876.40▲ 0.41%SENSEX79,943.00▲ 0.78%

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// Backtesting & Research

Optimisation & Robustness Testing

Find parameters that survive, not just the ones that fit the past.

Parameter sweeps, walk-forward analysis and Monte Carlo stress tests that separate a real edge from an overfit one — with clear recommendations.

  • Grid & random parameter sweeps
  • Walk-forward analysis
  • Monte Carlo drawdown bands
  • Stable-region recommendation
Optimisation & Robustness Testing — Find parameters that survive, not just the ones that fit the past.

Starting at

₹3,999 per strategy

4–6 business days Fixed quote before we start NDA on request
// overview

What this service covers

Any strategy can look brilliant with the right parameters on the right dates. We run structured sweeps across your parameter space, then apply walk-forward analysis and Monte Carlo resampling to see how the edge holds up out-of-sample and under randomised trade order and slippage.

The output is a parameter surface — not a single "best" number — so you can pick a stable region rather than a fragile peak, plus the confidence intervals that tell you what drawdown to actually expect.

What you receive

  • Parameter heat-maps and stability surface
  • Walk-forward report (in-sample vs out-of-sample)
  • Monte Carlo: expected vs worst-case drawdown, ruin probability
  • Recommended parameter set with rationale
Request this service

Starting at ₹3,999 per strategy · exclusive of GST

// how it works

From brief to delivery

A short, predictable process. You sign off at each step.

1

Define the space

Which parameters, which ranges, which objective (return, Sharpe, drawdown).

2

Sweep

Hundreds to thousands of runs on the engine.

3

Stress test

Walk-forward and Monte Carlo on the candidates.

4

Recommend

Report with a clear pick and the risks around it.

// faq

Optimisation & Robustness Testing — questions

How many parameters can you optimise?

Typically up to 6–8 meaningfully; beyond that overfitting risk dominates and we'll say so.

What is walk-forward analysis?

Optimising on one window and testing on the next, rolled through history — the closest thing to trading the strategy live in the past.

Ready to start with Optimisation & Robustness Testing?

Send a short brief and we'll reply with a fixed quote and timeline within one business day.