VALIDATE

Test a strategy on data it has not seen.

Run walk-forward, out-of-sample tests with trading costs and overfitting checks. Each result shows the universe, assumptions and qualified performance measures.

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Walk-forward backtesting, live at app.tradepolaris.com/backtests

What you get

Walk-forward, not curve-fit

Rolling out-of-sample folds, next-bar-open fills, gap-aware stops, bid/ask spread, square-root market impact and short-borrow costs.

An institutional tearsheet

Equity curve vs the S&P 500, Sharpe / Sortino / Calmar, drawdown, VaR / CVaR, a monthly heatmap and a 6-factor attribution.

Is the edge real?

Probabilistic & Deflated Sharpe, minimum track-record length, and Probability of Backtest Overfitting separate a real edge from luck.

Overfitting suiteTearsheetPaper tradingStrategy Builder

Zero code to full control

Build it your way.

Use the visual builder, write Python or export the signals. Every route uses the same validation engine.

From point-and-click to production Python.

Every strategy runs through the same walk-forward tests and overfitting checks.

No-code builder. Set factors, exits, optimisers and risk models.
Python SDK. Use a sandboxed runtime with full control.
Export your work. Take the spec, rule sheet or Pine output with you.

strategy: momentum-x-sectoruniverse:   { region: US, top: 500 }signals:  - momentum(126) - momentum(21)  - filter: adx(14) > 20portfolio:  { long: 50, weighting: risk_parity }exits:      { trailing: 8%, invalidation: signal_flip }validate:   { walk_forward: 5y, costs: realistic, gates: [DSR, PBO] }