# Market2000 Trading Performance API

> Market2000 Trading Performance API is a paid API for AI agents from market2000.xyz, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-15).

Retrieves trading performance metrics and time series pattern matching results for a given ticker over a specified lookback window

## Facts

- Endpoint: GET https://market2000.xyz/trading/performance
- Price: $0.05/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/market2000-trading-performance-api-9e6c0cd7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_FFZqWZW_xTizO0UjpEU7a

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability market2000-trading-performance-api-9e6c0cd7
```

Example prompt: Can you pull the trading performance and pattern matching data for AAPL over the last 90 days from market2000?

## When to prefer this

Use this endpoint when you need time series pattern matching and trading performance analysis for a specific ticker over a customizable lookback window, especially in agentic workflows that support x402 micropayments on Base. Prefer this over general market data APIs when you specifically need pattern-matched performance signals rather than raw OHLCV data.

## Known failure modes

- Missing or invalid ticker returns an error or empty result
- last_n_days outside the 7–365 range may return a validation error
- Payment failure via x402 results in a 402 Payment Required response
- Unsupported ticker symbols may return no data
- Network timeout if the pattern matching computation takes too long

## How this service works

Signal Performance — historical win rate, avg return, Sharpe ratio, per-ticker breakdown.

Aggregates all resolved signals from both the internal algo and x402 callers. Outcomes resolved at forward_days horizon using actual prices. This is the track record that proves the pattern engine has edge.

HOW TO CALL:
  GET /trading/performance
  GET /trading/performance?ticker=BTC&last_n_days=90

PARAMETERS:
  ticker      — filter to one ticker (optional)
  last_n_days — lookback window 7–365 (default 90)

RESPONSE:
  win_rate_pct, avg_return_pct, sharpe_ratio, total_resolved, by_ticker

PRICING: $0.05 per call.

## Output

Returns trading performance metrics and time series pattern matching results for the specified ticker over the requested lookback window; the response schema is not fully documented but likely includes performance statistics, matched patterns, and historical data points.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method",
    "queryParams"
   ],
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "GET",
      "HEAD",
      "DELETE"
     ],
     "type": "string"
    },
    "queryParams": {
     "type": "object",
     "properties": {
      "ticker": {
       "type": "string",
       "description": "Filter to one ticker (optional, e.g. BTC)"
      },
      "last_n_days": {
       "type": "integer",
       "default": 90,
       "description": "Lookback window in days (7–365)"
      }
     }
    }
   }
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object"
    }
   }
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/market2000-trading-performance-api-9e6c0cd7/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market2000.xyz](https://www.zero.xyz/host/market2000.xyz/llms.txt)