Your backtest passed. Here's why the signal still failed.

Strategy validation and quantitative research.

Most strategy failures trace to a single unstable feature. The question is whether you find it before your capital does.

The methodology

01

You bring your strategy

NDA intake, strategy hypothesis, data requirements

02

Your data becomes features

Vol surface decomposition, skew, term structure, dealer positioning

03

Your features get screened for regime stability

Spearman sign consistency, 7/10 year test, causal filter

04

Your predictions get tested on data the model never saw

Walk-forward OOS, holdout on untouched data, confidence intervals

05

You get a confidence report

Edge assessment, feature explanations, deployment recommendations

Perspective

Most backtests lie. Here's what they leave out.

01NO CHAIN STATE AT ENTRY

Your backtest is trading options that never existed.

Real strikes require the full chain snapshot — bid/ask, OI, Greeks at decision time. Not a single delta column.

02NO LIFECYCLE MODELING

Your backtest is reporting returns from a strategy nobody can actually run.

Rolls, early exercise, assignment, corporate actions — real positions encounter events that change the P&L trajectory.

03NO EXECUTION REALISM

Your backtest overstates returns in exactly the moments that matter most.

NBBO spreads widen in stress. Queue position matters. Slippage is regime-dependent. Filling at mid in all conditions is fiction.

04NO STABILITY SCREENING

Your in-sample result is suspect until proven otherwise.

Features that predict in one regime fail in the next. Without causal screening — asking whether the mechanism is hard to vary — optimization is just overfitting.

Ready to find out if your strategy holds up?

Find out before your capital does

Strategy validation from $20k

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