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invinoveritas Strategy Overfitting Validator
x402
invinoveritas Strategy Overfitting Validator is a paid API for AI agents from api.babyblueviper.com, paid per call via x402, $0.24/call, status unknown (last checked 2026-10-29).
Statistically validates trading strategy returns for overfitting using Deflated Sharpe Ratio, permutation tests, and k-fold out-of-sample decay analysis
Price / call$0.24
Success—
StatusUnknown
How this service works
invinoveritas /validate — EdgeProof: is a strategy's edge real or curve-fit noise? Get a verdict (likely_real / borderline / overfit) backed by Deflated Sharpe
Output
A JSON object containing a verdict ('overfit' or similar), permutation p-value indicating statistical significance, deflated Sharpe ratio after correcting for multiple testing, and k-fold out-of-sample decay percentage showing how much the strategy degrades on unseen data.
Example use cases
Validate backtest before live deployment
“I've got a strategy showing a Sharpe of 2.1 on 3 years of daily returns but I tried probably 30 different parameter combos to get there — run invinoveritas on these returns [0.001, 0.003, -0.002, 0.004, 0.002, -0.001, 0.003, 0.005, -0.003, 0.002, 0.004, 0.001, -0.002, 0.003, 0.002] and tell me if this edge is real or if I'm just overfitting to historical noise before I put real money in.”
Detect data snooping in quant research
“My research team screened 120 factor combinations looking for alpha signals and landed on one with a really strong backtest — can you send these monthly returns [0.03, 0.01, -0.02, 0.04, 0.02, 0.01, -0.01, 0.03, 0.02, -0.005, 0.035, 0.015] through invinoveritas with the trial count set to 120 so we get the multiple-testing correction and an honest out-of-sample decay estimate?”
Audit strategy edge for investor reporting
“Before we present this algorithmic strategy to LPs, I want an independent statistical audit — here are the weekly returns [0.005, 0.008, -0.003, 0.006, 0.004, -0.002, 0.007, 0.009, -0.004, 0.005, 0.006, 0.003, -0.001, 0.008, 0.004, 0.007], we tested around 60 variants, and I need the permutation p-value and deflated Sharpe so we're not overselling a lucky backtest.”
Technical details
Endpoint
POSThttps://api.babyblueviper.com/validate?utm_source=zero.xyzWhen to prefer
Use this endpoint when an AI agent or quant needs an objective, statistically rigorous check of a trading strategy's backtested returns before committing capital — especially when multiple variants were tried, making naive Sharpe ratios misleading. Prefer over simple Sharpe ratio calculators when data snooping or overfitting risk is the core concern.
Side effects
- Missing or empty returns array returns validation error
- n_variants_tried of zero or negative may cause division errors or undefined deflation haircut
- Returns array too short for meaningful k-fold cross-validation may yield unreliable results
- Malformed numeric values in returns array cause schema rejection
- Insufficient balance of USDC for x402 payment causes 402 Payment Required before processing
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| returns | array | Realized per-period returns of the strategy (never the strategy itself) |
| n_trials | integer | How many variants you tested (drives the Deflated Sharpe haircut) |
Output
Schema · Response
{
"type": "json",
"example": {
"schema": "invinoveritas.validate.v1",
"verdict": "overfit",
"disclaimer": "Statistical edge-reality check, not financial advice.",
"permutation_p": 0.42,
"deflated_sharpe": 0.31,
"kfold_oos_decay_pct": 61
}
}Tags
x402
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