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Money Mind — Clustered T-Stat Adjudication
x402
Money Mind — Clustered T-Stat Adjudication is a paid API for AI agents from money-mind-extract.onrender.com, paid per call via x402, $0.25/call, status unknown (last checked 2026-10-18).
Corrects inflated t-statistics in backtests by clustering trades by date to account for non-independence, returning both naive and date-adjusted t-values.
Price / call$0.25
Success—
StatusUnknown
How this service works
Pay-per-call adjudication for trading research. Eleven gates that killed 35 of our own concepts. Is your backtest real, is your price data real, is your t-stat inflated? USDC on Base, no account needed.
Output
Returns a JSON object with the naive (unadjusted) t-statistic, the date-clustered (corrected) t-statistic, the number of independent trading days identified, and the inflation factor — showing how much the naive t-stat overstates true statistical significance due to non-independent trades.
Example use cases
Day-trading strategy significance check
“I built a mean-reversion strategy that fires several trades per day. My naive t-stat is 6.2, but I'm worried it's inflated because the trades aren't independent. Can you run the date-cluster correction on my trade returns and dates to see what the real t-stat is?”
Correlated basket backtest validation
“I'm trading a basket of correlated ETFs and my backtest shows a t-stat of 4.8, but many trades happen on the same dates across instruments. Can you compute the cluster-adjusted t-stat to tell me how much inflation there is and how many truly independent days I have?”
Regime-clustered strategy adjudication
“My momentum strategy trades in bursts during trending regimes — lots of trades clustered in the same few weeks. My reported t-stat is 5.5 but I suspect it's way overstated. Run the date-cluster t-stat correction on these returns and dates and tell me the inflation factor.”
Technical details
Endpoint
POSThttps://money-mind-extract.onrender.com/clusteredt?utm_source=zero.xyzWhen to prefer
Use this endpoint when your backtest has multiple trades on the same day, trades in the same market regime, or a correlated basket — any situation where the standard independent-draws t-stat assumption is violated. It directly quantifies how inflated your t-stat is, providing both naive and corrected values so you can assess whether your strategy's edge is real or a statistical artifact of clustering.
Side effects
- Missing required per-trade returns or dates causes validation error
- Too few unique trading dates to compute a meaningful cluster adjustment
- All trades on unique dates — clustering has no effect, inflation factor near 1.0
- Payment failure in USDC on Base blocks the call
- Malformed date formats in the trade log cause parsing errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"naive_t": 5.98,
"date_clustered_t": 1.29,
"independent_days": 10,
"inflation_factor": 4.65
}
}Tags
x402
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