Most validation confirms what traders already believe. Ours does the opposite. Our proprietary framework applies a sequence of statistical tests designed to identify the failure modes that standard backtesting misses.
A fast, rigorous screen designed to kill quickly. Multiple layers of statistical testing assess whether the core signal has any validity before deeper resources are committed.
For survivors only. Real market microstructure data, bid-ask analysis, regime robustness across multiple environments, decay diagnostics, and portfolio-level correlation testing.
Every engagement produces a structured validation report. Binary pass/fail on each test layer, supported by quantitative evidence.
A comprehensive document designed to serve as an independent due diligence artifact, for your own capital allocation decisions, or to present to investors and allocators.
Anonymized case studies from our internal research. Each illustrates a different failure mode that the framework is designed to catch — and that standard backtesting misses.
| Layer | Test | Statistic | Verdict |
|---|---|---|---|
| L1 | Direction shuffle | p = 0.048 | PASS |
| L2 | Bootstrap CI | CI excludes 0 | PASS |
| L3 | Sharpe floor | 0.52 | PASS |
| L4 | Cost absorption | +18.4 bps net | PASS |
| L5 | Walk-forward | 3/5 positive | PASS |
| L6 | Bonferroni | p = 0.048 | PASS |
| L7 | N floor | N = 174 | PASS |
| L8 | Timing alpha — regime-conditional | p = 0.991 | KILL |
Month-end portfolio rebalancing by index funds and pension managers creates predictable flow in equity/bond pairs. The signal captures the rebalancing window and fades the expected flow direction.
Positive mean return of +23.6 bps per trade, Sharpe of 0.52, and a statistically significant direction shuffle (p = 0.048). Six of the first seven layers passed. By any conventional backtest standard, this looked like a viable strategy.
The L8 timing shuffle compares the strategy's entries against regime-conditional random entries on the same asset. The result: p = 0.991 — meaning random entries at the same frequency produced better returns than the signal. The entire apparent edge was explained by directional exposure to the underlying asset, not by the rebalancing mechanism. The signal was an expensive way to be long in an uptrend.
Research finding: Rebalancing flow at month-end is continuation, not reversion. The signal was anti-signal — fading flow that was informationally correct. This closed the daily-frequency rebalancing frontier across all tested asset pairs.
| Layer | Test | Statistic | Verdict |
|---|---|---|---|
| L1 | Direction shuffle | p = 0.001 | PASS |
| L2 | Bootstrap CI | CI excludes 0 | PASS |
| L3 | Sharpe floor | 0.71 | PASS |
| L4 | Cost absorption | +9.2 bps net | PASS |
| L5 | Walk-forward | 4/5 positive | PASS |
| L6 | Bonferroni | p = 0.009 | PASS |
| L7 | N floor (Domain B = 300) | N = 170 | KILL |
| L8 | Timing alpha | p = 0.0005 | PASS |
Algorithmic reaction to major macroeconomic releases creates a temporary overshoot in the first 30 seconds. Real-money flow normalizes the price over the following 5–35 minutes. The signal captures this reversion.
The mechanism is real. L8 returned p = 0.0005 — the strongest timing alpha confirmation in the entire research program. The forced actor is identifiable, the constraint is binding, and the statistical evidence is overwhelming. But the event occurs only ~17 times per year, producing N = 170 over 10 years of data. Domain B requires N ≥ 300. The strategy was killed by sample sufficiency, not by lack of edge.
We attempted cross-pair pooling (testing the same mechanism on correlated pairs to increase N). The correlation between pairs was ρ = 0.82, meaning the effective independent sample size barely increased. Pooling correlated observations inflates apparent statistical power without adding real information. The N floor exists precisely to prevent this.
Research finding: A confirmed mechanism is not the same as a tradeable edge. The N floor is the binding constraint for event-driven FX at minute resolution — a structural limitation of the data, not a framework calibration error. Cross-pair pooling does not solve the problem when pairs are correlated.
| Layer | Test | Statistic | Verdict |
|---|---|---|---|
| L1 | Direction shuffle | p = 0.042 | PASS |
| L4 | Cost absorption (16 bps RT) | −2.4 bps net | KILL |
| L8 | Timing alpha | p = 0.030 | PASS |
When a large-cap cryptocurrency drops sharply, exchange liquidation engines force-sell correlated altcoin positions. This creates a temporary overshoot that reverts as organic liquidity returns. The signal captures the reversion on a mid-cap altcoin at hourly resolution.
The mechanism is confirmed — L8 timing alpha is significant at p = 0.030. But the gross edge of +13.6 bps per trade cannot survive 16 bps in round-trip transaction costs (spread + commission + impact). Net return is negative. The edge exists but is not tradeable at this resolution and cost structure.
Research finding: The same mechanism tested at higher resolution (15-minute bars) with tighter spreads survived cost absorption and passed full validation. Resolution and cost structure determine whether a confirmed mechanism translates into a tradeable edge. The framework tests both independently.
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