{
  "sources": [
    {
      "url": "https://api.imdnotdead.fun/artifacts/1f4f14f040b309e004904672ec6e2bb051f97b8d1195602d36b35a54c05d6c0f",
      "quote": "\"code\": \"// SPDX-License-Identifier: MIT\\npragma solidity ^0.8.24;\\n\\nimport {AMMStrategyBase} from \\\"./AMMStrategyBase.sol\\\";\\nimport {TradeInfo} from \\\"./IAMMStrategy.sol\\\";\\n\\ncontract Strategy is AMMStrategyBase {\\n    uint256 constant ELAPSED_CAP = 8;\\n    uint256 constant SIGNAL_THRESHOLD = WAD / 650;\\n    uint256 constant DIR_DECAY = 750000000000000000;\\n    uint256 constant ACT_DECAY = 530"
    },
    {
      "url": "https://api.imdnotdead.fun/artifacts/528a6da78583c6142644a552c86670f9d25c20e39e92f4de44deae05ddc8cecd",
      "quote": "\"code\": \"// SPDX-License-Identifier: MIT\\npragma solidity ^0.8.24;\\n\\nimport {AMMStrategyBase} from \\\"./AMMStrategyBase.sol\\\";\\nimport {TradeInfo} from \\\"./IAMMStrategy.sol\\\";\\n\\ncontract Strategy is AMMStrategyBase {\\n    uint256 constant ELAPSED_CAP = 8;\\n    uint256 constant SIGNAL_THRESHOLD = WAD / 650;\\n    uint256 constant DIR_DECAY = 750000000000000000;\\n    uint256 constant ACT_DECAY = 530"
    },
    {
      "url": "https://api.imdnotdead.fun/artifacts/da313379a2e69e9286668865e06b18dfcae25732c82b934b0fd9c2ef0d8c2ff5",
      "quote": "\"code\": \"// SPDX-License-Identifier: MIT\\npragma solidity ^0.8.24;\\n\\nimport {AMMStrategyBase} from \\\"./AMMStrategyBase.sol\\\";\\nimport {TradeInfo} from \\\"./IAMMStrategy.sol\\\";\\n\\ncontract Strategy is AMMStrategyBase {\\n    uint256 constant ELAPSED_CAP = 8;\\n    uint256 constant SIGNAL_THRESHOLD = WAD / 650;\\n    uint256 constant DIR_DECAY = 750000000000000000;\\n    uint256 constant ACT_DECAY = 530"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py",
      "quote": "BASELINE_VARIANCE = HyperparameterVariance(\n    retail_mean_size_min=19.0,\n    retail_mean_size_max=21.0,\n    vary_retail_mean_size=True,\n    retail_arrival_rate_min=0.6,\n    retail_arrival_rate_max=1.0,\n    vary_retail_arrival_rate=True,\n    gbm_sigma_min=0.000882,\n    gbm_sigma_max=0.001008,\n    vary_gbm_sigma=True,\n)\n\ndef _midpoint(min_val: float, max_val: float) -> float:\n    return (min_val + max_val) / 2\n\n\ndef baseline_nominal_sigma() -> float:\n    return _midpoint(BASE"
    },
    {
      "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py",
      "quote": "    def _build_configs(self) -> list[amm_sim_rs.SimulationConfig]:\n        \"\"\"Build simulation configs with optional variance.\"\"\"\n        import numpy as np\n\n        configs = []\n        for i in range(self.n_simulations):\n            rng = np.random.default_rng(seed=i)\n\n            retail_mean_size = (\n                rng.uniform(self.variance.retail_mean_size_min, self.variance.retail_mean_size_max)\n                if self.variance.vary_retail_mean_size\n                else"
    }
  ]
}