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Stock Bloc Quant Sim – Strategy Performance Simulator
x402
Stock Bloc Quant Sim – Strategy Performance Simulator is a paid API for AI agents from stockbloc.ai.studio, paid per call via x402, $0.1/call, status unknown (last checked 2026-10-12).
Runs a quantitative simulation of a trading strategy and returns performance metrics including Sharpe ratio, alpha, max drawdown, annualized return, and benchmark comparison.
Price / call$0.1
Success—
StatusUnknown
How this service works
Financial research API for AI agents: Stock Bloc SEC Analyst (10-K/10-Q/8-K filing analysis), market data, MCP tools, and x402 USDC payments on Base.
Output
Returns a JSON object with: status (success/error), evaluatedAt (ISO timestamp), sharpeRatio (risk-adjusted return metric), alpha (excess return vs benchmark), maxDrawdown (largest peak-to-trough loss as a decimal), annualizedReturn (annualized % return), and benchmarkReturn (benchmark comparison return).
Example use cases
Momentum strategy risk assessment
“Simulate my momentum-based equity strategy and tell me the Sharpe ratio, alpha, and worst drawdown so I can decide whether the risk is worth it.”
Benchmark comparison for portfolio model
“Can you run a quant sim on my mean-reversion strategy and show me how the annualized return stacks up against the benchmark, along with the risk metrics?”
Pre-launch quant model validation
“Before I deploy this new quant model, simulate it and give me the full performance breakdown — Sharpe, alpha, max drawdown, and benchmark return — so I can validate it looks solid.”
Technical details
Endpoint
POSThttps://stockbloc.ai.studio/api/v1/agent/quant-sim?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need quantitative performance metrics (Sharpe ratio, alpha, max drawdown, annualized return) for a trading strategy simulation. It is distinct from SEC filing analysis or real-time market data endpoints on the same platform — use this specifically for strategy backtesting and risk-adjusted performance computation. Best for AI agents evaluating or comparing trading models before deployment.
Side effects
- Missing required 'input' object causes validation error
- Invalid method enum value (not POST/PUT/PATCH) returns 400
- Invalid bodyType enum (not json/form-data/text) returns 400
- Malformed strategy parameters in body may produce empty or error response
- Payment failure via x402/USDC results in 402 Payment Required
- Network timeout if simulation is computationally intensive
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"alpha": 0.116,
"status": "success",
"evaluatedAt": "2026-09-29T00:00:00.000Z",
"maxDrawdown": -0.092,
"sharpeRatio": 2.65,
"benchmarkReturn": 0.312,
"annualizedReturn": 0.428
}
}Tags
x402
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