Strategy Optimizer

x402

Strategy Optimizer is a paid API for AI agents from grok-backtest-api.fly.dev, paid per call via x402, $0.5/call, status unknown (last checked 2026-10-31).

Grid-searches strategy parameter combinations across Coinbase daily candles and returns recommended, overfitting-flagged, and ranked parameter sets for crypto quant strategies.

Price / call$0.5

Seller volume →—

Success—

StatusUnknown

How this service works

Grid-search up to 50 parameter combos of a backtest strategy; ranks by worst-half (H1/H2) return with neighbourhood smoothing, flags overfitting, and recommends the most robust parameters rather than the best-fit ones.

Output

A JSON object containing the total and executed combo count, a recommended parameter set (ranked by the chosen method), the best-by-return parameters, per-combo return and robust scores, half-period returns for overfitting detection, a summary with percent profitable and median return, and a list of overfitting flags with details.

Example use cases

Tune momentum strategy before live deployment

“I want to optimize my momentum crypto strategy before going live — grid search lookbacks of 10, 20, and 40 and risk_per_trade of 0.02, 0.05, and 0.1 on the point-in-time top 100 coins from 2021-01-01 to 2023-12-31, with 0.15% slippage, $50,000 initial capital, and rank results by robustness so I can spot any overfitting.”

Find best breakout parameters for recent bull market

“Run a grid search on a breakout strategy using the current top 50 coins from 2023-01-01 to 2024-12-31, trying atr_mult values of 1.5, 2, and 3 and lookbacks of 5, 10, and 20, with 0.2% slippage and 0.05% fee on $25,000, and rank by return so I can see which settings performed best in the recent bull run.”

Identify robust dip-buying parameters across market cycles

“I'm building a dip-buying bot — can you optimize it over 2020-01-01 to 2024-12-31 using the point-in-time top 200 coins with a minimum age of 90 days and min dollar volume of $1M, grid-searching lookbacks of 7, 14, and 30 and risk_per_trade of 0.01, 0.03, and 0.05, with 0.1% slippage, ranked by robustness so I know the params hold across both half-periods?”

Technical details

Endpoint

POSThttps://grok-backtest-api.fly.dev/optimize?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need to systematically evaluate multiple parameter combinations for a crypto trading strategy and want overfitting protection via half-period return comparison and robust scoring — as opposed to running a single backtest. Prefer this over the Crypto Backtest endpoint when you have uncertainty about optimal parameter values and want a ranked shortlist with regime-stability checks included in one call.

Side effects

Invalid strategy type enum value returns 422 validation error
Grid parameter values incompatible with strategy type cause computation errors
Date range with insufficient candle history returns empty or error result
Universe mode 'point_in_time' with no eligible coins returns empty universe error
Slippage or fee values exceeding maximum (0.05) return 422 validation error
Payment not provided or insufficient USDC causes 402 Payment Required response
Very large grids may exceed compute limits and return truncated results

Input

Schema · Request body

Field	Type	Description
end	—
fee	number
grid	object
start	—
rank_by	string
slippage	number
strategy	object
universe	object
initial_capital	number

Output

Schema · Response

{
  "type": "json",
  "example": {
    "summary": {
      "pct_profitable": 55.6,
      "median_return_pct": 1.2
    },
    "truncated": false,
    "combos_run": 18,
    "recommended": {
      "params": {
        "atr_mult": 2,
        "lookback": 20,
        "risk_per_trade": 0.05
      },
      "return_pct": 10.98,
      "robust_score": -11.97,
      "h1_return_pct": -6.97,
      "h2_return_pct": 19.88
    },
    "combos_total": 18,
    "best_by_return": {
      "params": {
        "atr_mult": 2,
        "lookback": 10,
        "risk_per_trade": 0.05
      }
    },
    "overfitting_flags": [
      {
        "id": "best_return_not_robust",
        "detail": "..."
      }
    ]
  }
}

Reviews

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How this service works

Output

Example use cases

Tune momentum strategy before live deployment

Find best breakout parameters for recent bull market

Identify robust dip-buying parameters across market cycles

Technical details

Endpoint

POSThttps://grok-backtest-api.fly.dev/optimize?utm_source=zero.xyz

When to prefer

Side effects

Invalid strategy type enum value returns 422 validation error
Grid parameter values incompatible with strategy type cause computation errors
Date range with insufficient candle history returns empty or error result
Universe mode 'point_in_time' with no eligible coins returns empty universe error
Slippage or fee values exceeding maximum (0.05) return 422 validation error
Payment not provided or insufficient USDC causes 402 Payment Required response
Very large grids may exceed compute limits and return truncated results

Input

Schema · Request body

Field	Type	Description
end	—
fee	number
grid	object
start	—
rank_by	string
slippage	number
strategy	object
universe	object
initial_capital	number

Output

Schema · Response

{
  "type": "json",
  "example": {
    "summary": {
      "pct_profitable": 55.6,
      "median_return_pct": 1.2
    },
    "truncated": false,
    "combos_run": 18,
    "recommended": {
      "params": {
        "atr_mult": 2,
        "lookback": 20,
        "risk_per_trade": 0.05
      },
      "return_pct": 10.98,
      "robust_score": -11.97,
      "h1_return_pct": -6.97,
      "h2_return_pct": 19.88
    },
    "combos_total": 18,
    "best_by_return": {
      "params": {
        "atr_mult": 2,
        "lookback": 10,
        "risk_per_trade": 0.05
      }
    },
    "overfitting_flags": [
      {
        "id": "best_return_not_robust",
        "detail": "..."
      }
    ]
  }
}