← All products
BUILD & PROVE

Build a strategy and test the rules before you use it.

Set the universe, signal, weighting and risk limits in the builder or Python. Every strategy runs through the same walk-forward tests and overfitting checks before it reaches Aegis or paper trading.

Point-in-time data Cost-aware Out-of-sample
What you get

Build it three ways

Use the visual builder, write Python with the sandboxed SDK or describe the rules and let Vega draft them.

Test for overfitting

Walk-forward tests include universe warnings, Deflated Sharpe and Probability of Backtest Overfitting. Results that fail the checks are clearly marked.

Move from test to monitoring

Open a tested strategy in Aegis to track VaR, stress and factor risk, or paper trade it with email signals.

Alpha DSLStrategy SDKOptimizerRisk model
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] }

Turn your next thesis into evidence.

Start with a sentence or a template, keep control of every rule, and let the evidence decide what survives.

Join beta

Backtested / walk-forward results are hypothetical, do not represent actual trading, and are not indicative of future results.