{ "approach": "Retune NP fair-price filter jointly: first-in-step PHAT_ALPHA, later-trade PHAT_ALPHA_RETAIL, and the conditional 30 bps normalizer-implied-price weight. All other fee and state-estimation equations retain CH/NP behavior. Three small factorial grids, then a single frozen-candidate fresh paired test.", "tried": [ { "variant": "a200_r30_w70", "seeds": [ 30000, 31999 ], "n": 2000, "mean_diff": -1.3359630076070208, "se": 0.022186660269705654, "worst": [ { "seed": 30872, "diff": -10.85447664640185 }, { "seed": 31872, "diff": -10.531159813812792 }, { "seed": 31377, "diff": -6.746381369439746 }, { "seed": 30053, "diff": -6.163469510093364 }, { "seed": 30673, "diff": -5.498167969510064 } ], "sha256": "c66908d0f226205eccf0fa66bd7ada91fb875672d0e2834dca998bc936a3a32a", "reference": "NP", "seed_start": 30000, "seed_end": 31999, "mean_edge": 522.5448064115849, "tuning_rank": 14 }, { "variant": "a200_r30_w130", "seeds": [ 30000, 31999 ], "n": 2000, "mean_diff": -1.2349740187985376, "se": 0.020712518214253, "worst": [ { "seed": 31872, "diff": -9.925331703895722 }, { "seed": 30053, "diff": -5.560758254101188 }, { "seed": 30216, "diff": -4.542540869767379 }, { "seed": 30673, "diff": -4.5006903629350745 }, { "seed": 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"mean_diff": -0.04542152439028962, "se": 0.00855140578842152, "worst": [ { "seed": 31017, "diff": -2.3236916886967265 }, { "seed": 30865, "diff": -2.30127944500839 }, { "seed": 31725, "diff": -1.7845768609613515 }, { "seed": 31715, "diff": -1.6102018713290818 }, { "seed": 31028, "diff": -1.4911051370734185 } ], "sha256": "cac4969489d192dd108712b4d4934f1a9ecaaa9d2caa2e5025cb44d53f17e628", "reference": "NP", "seed_start": 30000, "seed_end": 31999, "mean_edge": 523.8353478948017, "tuning_rank": 4 } ], "next": "Do not promote this candidate. Retain NP. The frozen candidate did not establish a fresh gain above two standard errors; a future experiment could probe smaller changes around the best tuning cell on unused tuning seeds, with a new holdout.", "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 = 530000000000000000;\n uint256 constant SIZE_DECAY = 530000000000000000;\n uint256 constant TOX_DECAY = 910000000000000000;\n uint256 constant SIGMA_DECAY = 690000000000000000;\n uint256 constant LAMBDA_DECAY = 990000000000000000;\n uint256 constant SIZE_BLEND_DECAY = 828000000000000000;\n uint256 constant TOX_BLEND_DECAY = 51000000000000000;\n uint256 constant ACT_BLEND_DECAY = 985000000000000000;\n uint256 constant PHAT_ALPHA = 260000000000000000;\n uint256 constant PHAT_ALPHA_RETAIL = 55000000000000000;\n uint256 constant DIR_IMPACT_MULT = 4;\n uint256 constant GATE_SIGMA_MULT = 7200000000000000000;\n uint256 constant MIN_GATE = 30000000000000000;\n uint256 constant TRADE_TOX_BOOST = 3500 * BPS;\n uint256 constant STALE_ATTRACT_FRAC = 1050000000000000000;\n uint256 constant RET_CAP = WAD / 35;\n uint256 constant TOX_CAP = WAD / 5;\n uint256 constant TRADE_RATIO_CAP = WAD / 5;\n uint256 constant LAMBDA_CAP = 1820000000000000000;\n uint256 constant STEP_COUNT_CAP = 64;\n uint256 constant BASE_FEE = 4 * BPS;\n uint256 constant SIGMA_COEF = 200000000000000000;\n uint256 constant LAMBDA_COEF = 12 * BPS;\n uint256 constant FLOW_SIZE_COEF = 4842 * BPS;\n uint256 constant TOX_COEF = 300 * BPS;\n uint256 constant TOX_QUAD_COEF = 15000 * BPS;\n uint256 constant ACT_COEF = 91843 * BPS;\n uint256 constant DIR_COEF = 20 * BPS;\n uint256 constant DIR_TOX_COEF = 100 * BPS;\n uint256 constant STALE_DIR_COEF = 6850 * BPS;\n uint256 constant SIGMA_TOX_COEF = 500 * BPS;\n uint256 constant TAIL_KNEE = 600 * BPS;\n uint256 constant TAIL_SLOPE_PROTECT = 930000000000000000;\n uint256 constant TAIL_SLOPE_ATTRACT = 850000000000000000;\n\n function afterInitialize(uint256 initialX, uint256 initialY) external override returns (uint256, uint256) {\n slots[0] = BASE_FEE; slots[1] = BASE_FEE; slots[2] = 0; slots[3] = WAD; slots[4] = 0;\n slots[5] = initialX > 0 ? wdiv(initialY, initialX) : 100 * WAD;\n slots[6] = 950000000000000; slots[7] = 800000000000000000; slots[8] = 2000000000000000;\n slots[9] = 0; slots[10] = 0;\n return (BASE_FEE, BASE_FEE);\n }\n\n function afterSwap(TradeInfo calldata trade) external override returns (uint256, uint256) {\n uint256 prevBidFee = slots[0]; uint256 prevAskFee = slots[1]; uint256 lastTs = slots[2];\n uint256 dirState = slots[3]; uint256 actEma = slots[4]; uint256 pHat = slots[5];\n uint256 sigmaHat = slots[6]; uint256 lambdaHat = slots[7]; uint256 sizeHat = slots[8];\n uint256 toxEma = slots[9]; uint256 stepTradeCount = slots[10];\n\n bool isNewStep = trade.timestamp > lastTs;\n if (isNewStep) {\n uint256 elapsedRaw = trade.timestamp - lastTs;\n uint256 elapsed = elapsedRaw > ELAPSED_CAP ? ELAPSED_CAP : elapsedRaw;\n dirState = _decayCentered(dirState, DIR_DECAY, elapsed);\n actEma = wmul(actEma, _powWad(ACT_DECAY, elapsed));\n sizeHat = wmul(sizeHat, _powWad(SIZE_DECAY, elapsed));\n toxEma = wmul(toxEma, _powWad(TOX_DECAY, elapsed));\n if (stepTradeCount > 0 && elapsedRaw > 0) {\n uint256 lambdaInst = (stepTradeCount * WAD) / elapsedRaw;\n if (lambdaInst > LAMBDA_CAP) lambdaInst = LAMBDA_CAP;\n lambdaHat = wmul(lambdaHat, LAMBDA_DECAY) + wmul(lambdaInst, WAD - LAMBDA_DECAY);\n }\n stepTradeCount = 0;\n }\n\n bool firstInStep = stepTradeCount == 0;\n uint256 spot = trade.reserveX > 0 ? wdiv(trade.reserveY, trade.reserveX) : pHat;\n if (pHat == 0) pHat = spot;\n\n uint256 feeUsed = trade.isBuy ? prevBidFee : prevAskFee;\n uint256 gamma = feeUsed < WAD ? WAD - feeUsed : 0;\n uint256 pImplied;\n if (gamma == 0) { pImplied = spot; }\n else { pImplied = trade.isBuy ? wmul(spot, gamma) : wdiv(spot, gamma); }\n\n {\n uint256 ret = pHat > 0 ? wdiv(absDiff(pImplied, pHat), pHat) : 0;\n uint256 alpha = firstInStep ? PHAT_ALPHA : PHAT_ALPHA_RETAIL;\n uint256 adaptiveGate = wmul(sigmaHat, GATE_SIGMA_MULT);\n if (adaptiveGate < MIN_GATE) adaptiveGate = MIN_GATE;\n if (ret <= adaptiveGate) { pHat = wmul(pHat, WAD - alpha) + wmul(pImplied, alpha); }\n if (firstInStep) {\n if (ret > RET_CAP) ret = RET_CAP;\n sigmaHat = wmul(sigmaHat, SIGMA_DECAY) + wmul(ret, WAD - SIGMA_DECAY);\n }\n }\n\n if(!firstInStep&&feeUsed>30*BPS&&gamma>0){uint256 nS=trade.isBuy?wdiv(wmul(spot,gamma),WAD-30*BPS):wdiv(wmul(spot,WAD-30*BPS),gamma);pHat=wmul(pHat,870000000000000000)+wmul(nS,130000000000000000);}\n uint256 tradeRatio = trade.reserveY > 0 ? wdiv(trade.amountY, trade.reserveY) : 0;\n if (tradeRatio > TRADE_RATIO_CAP) tradeRatio = TRADE_RATIO_CAP;\n\n if (tradeRatio > SIGNAL_THRESHOLD) {\n uint256 push = tradeRatio * DIR_IMPACT_MULT;\n if (push > WAD / 4) push = WAD / 4;\n if (trade.isBuy) {\n dirState = dirState + push;\n if (dirState > 2 * WAD) dirState = 2 * WAD;\n } else {\n dirState = dirState > push ? dirState - push : 0;\n }\n actEma = wmul(actEma, ACT_BLEND_DECAY) + wmul(tradeRatio, WAD - ACT_BLEND_DECAY);\n sizeHat = wmul(sizeHat, SIZE_BLEND_DECAY) + wmul(tradeRatio, WAD - SIZE_BLEND_DECAY);\n if (sizeHat > WAD) sizeHat = WAD;\n }\n\n uint256 tox = pHat > 0 ? wdiv(absDiff(spot, pHat), pHat) : 0;\n if (tox > TOX_CAP) tox = TOX_CAP;\n toxEma = wmul(toxEma, TOX_BLEND_DECAY) + wmul(tox, WAD - TOX_BLEND_DECAY);\n uint256 toxSignal = toxEma;\n\n stepTradeCount = stepTradeCount + 1;\n if (stepTradeCount > STEP_COUNT_CAP) stepTradeCount = STEP_COUNT_CAP;\n\n uint256 flowSize = wmul(lambdaHat, sizeHat);\n uint256 fBase = BASE_FEE + wmul(SIGMA_COEF, sigmaHat) + wmul(LAMBDA_COEF, lambdaHat) + wmul(FLOW_SIZE_COEF, flowSize);\n uint256 fMid = fBase + wmul(TOX_COEF, toxSignal) + wmul(TOX_QUAD_COEF, wmul(toxSignal, toxSignal)) + wmul(ACT_COEF, actEma);\n fMid = fMid + wmul(SIGMA_TOX_COEF, wmul(sigmaHat, toxSignal));\n\n uint256 dirDev; bool sellPressure;\n if (dirState >= WAD) { dirDev = dirState - WAD; sellPressure = true; }\n else { dirDev = WAD - dirState; sellPressure = false; }\n\n uint256 skew = wmul(DIR_COEF, dirDev) + wmul(DIR_TOX_COEF, wmul(dirDev, toxSignal));\n uint256 bidFee; uint256 askFee;\n if (sellPressure) {\n bidFee = fMid + skew;\n askFee = fMid > skew ? fMid - skew : 0;\n } else {\n askFee = fMid + skew;\n bidFee = fMid > skew ? fMid - skew : 0;\n }\n\n {\n uint256 staleShift = wmul(STALE_DIR_COEF, toxSignal);\n uint256 attractShift = wmul(staleShift, STALE_ATTRACT_FRAC);\n if (spot >= pHat) {\n bidFee = bidFee + staleShift;\n askFee = askFee > attractShift ? askFee - attractShift : 0;\n } else {\n askFee = askFee + staleShift;\n bidFee = bidFee > attractShift ? bidFee - attractShift : 0;\n }\n }\n\n {\n bool tradeAligned = (trade.isBuy && spot >= pHat) || (!trade.isBuy && spot < pHat);\n if (tradeAligned) {\n uint256 tradeBoost = wmul(TRADE_TOX_BOOST, tradeRatio);\n if (trade.isBuy) { bidFee = bidFee + tradeBoost; }\n else { askFee = askFee + tradeBoost; }\n }\n }\n\n if (sellPressure) {\n bidFee = clampFee(_compressTailWithSlope(bidFee, TAIL_SLOPE_PROTECT));\n askFee = clampFee(_compressTailWithSlope(askFee, TAIL_SLOPE_ATTRACT));\n } else {\n askFee = clampFee(_compressTailWithSlope(askFee, TAIL_SLOPE_PROTECT));\n bidFee = clampFee(_compressTailWithSlope(bidFee, TAIL_SLOPE_ATTRACT));\n }\n\n slots[0] = bidFee; slots[1] = askFee; slots[2] = trade.timestamp;\n slots[3] = dirState; slots[4] = actEma; slots[5] = pHat;\n slots[6] = sigmaHat; slots[7] = lambdaHat; slots[8] = sizeHat;\n slots[9] = toxEma; slots[10] = stepTradeCount;\n\n return (bidFee, askFee);\n }\n\n function _compressTailWithSlope(uint256 fee, uint256 slope) internal pure returns (uint256) {\n if (fee <= TAIL_KNEE) return fee;\n return TAIL_KNEE + wmul(fee - TAIL_KNEE, slope);\n }\n\n function _powWad(uint256 factor, uint256 exp) internal pure returns (uint256 result) {\n result = WAD;\n if (exp & 1 == 1) result = wmul(result, factor);\n factor = wmul(factor, factor);\n if (exp & 2 == 2) result = wmul(result, factor);\n factor = wmul(factor, factor);\n if (exp & 4 == 4) result = wmul(result, factor);\n factor = wmul(factor, factor);\n if (exp & 8 == 8) result = wmul(result, factor);\n }\n\n function _decayCentered(uint256 centered, uint256 decayFactor, uint256 elapsed) internal pure returns (uint256) {\n uint256 mul = _powWad(decayFactor, elapsed);\n if (centered >= WAD) { return WAD + wmul(centered - WAD, mul); }\n uint256 below = wmul(WAD - centered, mul);\n return below < WAD ? WAD - below : 0;\n }\n\n function getName() external pure override returns (string memory) { return \"no_cubic\"; }\n}\n", "code_sha256": "0dae5bb9096c647983a4200dc879407042f5e889ee70033f4d479136904d2205", "delta": { "reference": "NP", "reference_sha256": "95d21646a5b6d293c86c36a184769477be7b1ff39ab2adde7668ed79fb22dd38", "PHAT_ALPHA": { "before": "0.27", "after": "0.26" }, "PHAT_ALPHA_RETAIL": { "before": "0.06", "after": "0.055" }, "normalizer_weight": { "before": "0.10", "after": "0.13" }, "structural": "Unroll _powWad into four binary exponent tests. All call sites use elapsed <= 8; this preserves WAD truncation and removes the inherited loop. No new slots or fee mechanisms." }, "score": { "seed_start": 0, "n": 1000, "mean_edge": 526.0096790592407, "se": 2.7911923417947935 }, "paired": { "n": 2000, "mean_diff": -0.012058842207524123, "se": 0.007788621128756689, "worst": [ { "seed": 801130, "diff": -2.962100069567441 }, { "seed": 800111, "diff": -1.9347142770884602 }, { "seed": 800840, "diff": -1.7131245546487435 }, { "seed": 801528, "diff": -1.458747047745078 }, { "seed": 801014, "diff": -1.3827213283504989 } ], "reference": "NP", "seed_start": 800000, "n_covered": 2000, "reference_sha256": "95d21646a5b6d293c86c36a184769477be7b1ff39ab2adde7668ed79fb22dd38", "chunks": [ { "seed_start": 800000, "n": 500 }, { "seed_start": 800500, "n": 500 }, { "seed_start": 801000, "n": 500 }, { "seed_start": 801500, "n": 500 } ], "candidate_sha256": "0dae5bb9096c647983a4200dc879407042f5e889ee70033f4d479136904d2205" }, "seconds_per_simulation": 0.11459878683206626, "validate_ok": true, "blocked": null, "promotion": { "accepted": false, "criterion": "Fresh paired mean_diff > 2 * standard error", "threshold": 0.015577242257513379, "recommended_best_sha256": "95d21646a5b6d293c86c36a184769477be7b1ff39ab2adde7668ed79fb22dd38" }, "promotions": [], "scoreboard": { "incumbent": { "name": "NP", "sha256": "95d21646a5b6d293c86c36a184769477be7b1ff39ab2adde7668ed79fb22dd38", "seed_start": 0, "n": 1000, "mean_edge": 526.0337302497852, "se": 2.7912248204542776 }, "calibration_reference": { "name": "CH", "sha256": "6dd68f77a70900319460215374143dbd5d924198450a46d9f5f91f6b1e3d35c3", "seed_start": 0, "n": 1000, "mean_edge": 525.5258821780834, "se": 2.7894264590251843 }, "ranked_tuning": [ { "rank": 1, "variant": "a260_r55_w130", "code_sha256": "0dae5bb9096c647983a4200dc879407042f5e889ee70033f4d479136904d2205", "n": 2000, "mean_edge": 523.8931821052236, "mean_diff": 0.012412686031698456, "se": 0.008290983693351938 }, { "rank": 2, "variant": "a280_r55_w130", "code_sha256": "cbd2ee446f406184165a6c9d205b9243e105012657f814a825fbcc0979da0654", "n": 2000, "mean_edge": 523.8876512140806, "mean_diff": 0.0068817948887485445, "se": 0.00792336509711462 }, { "rank": 3, "variant": "a250_r50_w115", "code_sha256": "a1d0720dbc946626ebe431df165f5feba67770c9df5da6a122ee48c17e2e9abf", "n": 2000, "mean_edge": 523.8419577572463, "mean_diff": -0.038811661945655315, "se": 0.009642733637476048 }, { "rank": 4, "variant": "a280_r65_w130", "code_sha256": "cac4969489d192dd108712b4d4934f1a9ecaaa9d2caa2e5025cb44d53f17e628", "n": 2000, "mean_edge": 523.8353478948017, "mean_diff": -0.04542152439028962, "se": 0.00855140578842152 }, { "rank": 5, "variant": "a260_r65_w130", "code_sha256": "6f57e6e4a36ee5277e71b79c69763631bd6c2923534305bb1feb19a2547544ed", "n": 2000, "mean_edge": 523.8339406407729, "mean_diff": -0.04682877841904093, "se": 0.008757663857724802 }, { "rank": 6, "variant": "a250_r50_w85", "code_sha256": "172f07015c07071c672a1ea3cfec6ec4fd79907289353d7a585fa76416feb234", "n": 2000, "mean_edge": 523.800881747603, "mean_diff": -0.07988767158889257, "se": 0.010794825642760996 }, { "rank": 7, "variant": "a250_r70_w115", "code_sha256": "154773def5693c019bb6b85c9b64169535440139da4d5acb353dc189356e62e5", "n": 2000, "mean_edge": 523.7311289575679, "mean_diff": -0.14964046162397718, "se": 0.009833993002837754 }, { "rank": 8, "variant": "a250_r70_w85", "code_sha256": "e6dff85c5966d65f1c5921c270afb5641896e593020600bd4c2fe50188919ed5", "n": 2000, "mean_edge": 523.7137912001858, "mean_diff": -0.16697821900603638, "se": 0.009236191270490296 }, { "rank": 9, "variant": "a300_r50_w115", "code_sha256": "2f0efd408992feda11915e1de0f1b260fee99d55f949c52d566ecb97a092f9c8", "n": 2000, "mean_edge": 523.7126427250346, "mean_diff": -0.16812669415734924, "se": 0.01154571787057502 }, { "rank": 10, "variant": "a300_r50_w85", "code_sha256": "cfd7aed5eefb24e4cec1add05b90b58bd0bb396ab24dc3fba020b184917bc28f", "n": 2000, "mean_edge": 523.6626282481465, "mean_diff": -0.2181411710454878, "se": 0.012081022340615278 }, { "rank": 11, "variant": "a300_r70_w115", "code_sha256": "c29c341cae0c2125a9454815c7d70e37eeb3e3425e8eefa1d4f69e658533f327", "n": 2000, "mean_edge": 523.6308353998372, "mean_diff": -0.2499340193546178, "se": 0.011498986315329907 }, { "rank": 12, "variant": "a300_r70_w85", "code_sha256": "876c2decf09761d85f11518f44f9083e67b1fff19d5b6ffc55c7a76fccdb3913", "n": 2000, "mean_edge": 523.6044043425509, "mean_diff": -0.27636507664100407, "se": 0.011383111258289846 }, { "rank": 13, "variant": "a200_r30_w130", "code_sha256": "7247256ce0f190d6c4aac2e6c3c41dc04ff3a47368f5df406b69c7976b061d2b", "n": 2000, "mean_edge": 522.6457954003934, "mean_diff": -1.2349740187985376, "se": 0.020712518214253 }, { "rank": 14, "variant": "a200_r30_w70", "code_sha256": "c66908d0f226205eccf0fa66bd7ada91fb875672d0e2834dca998bc936a3a32a", "n": 2000, "mean_edge": 522.5448064115849, "mean_diff": -1.3359630076070208, "se": 0.022186660269705654 }, { "rank": 15, "variant": "a350_r30_w130", "code_sha256": "fd032c39b25e0418e9841a72ece8e6eab6e3fc2135fdabffac4299eecc659c76", "n": 2000, "mean_edge": 522.4915014415913, "mean_diff": -1.389267977600629, "se": 0.020981510885277842 }, { "rank": 16, "variant": "a350_r30_w70", "code_sha256": "ed19ab77dd365b1eca2d42b05c7d88b9a9dda1ff0beb4b0607b6ab0d82af915a", "n": 2000, "mean_edge": 522.3430264899531, "mean_diff": -1.5377429292388038, "se": 0.022564827376123735 }, { "rank": 17, "variant": "a350_r100_w70", "code_sha256": "3e23f8217fe5634cfdb7856c1011be26ff16a516186032f96148e7b4c341a32e", "n": 2000, "mean_edge": 522.0426941745206, "mean_diff": -1.8380752446712452, "se": 0.0200808776650191 }, { "rank": 18, "variant": "a350_r100_w130", "code_sha256": "45997d5e3907d48eb8f6f2b6aefefa6fd23e0a5bcd8e1efc0cbe43ef31e0deaf", "n": 2000, "mean_edge": 521.9835546432803, "mean_diff": -1.8972147759116522, "se": 0.020268649556498583 }, { "rank": 19, "variant": "a200_r100_w70", "code_sha256": "963b5674276e768392e5f7710a6a71425231134ea1d554e67d477824c26ee9b6", "n": 2000, "mean_edge": 521.8924870826044, "mean_diff": -1.9882823365875648, "se": 0.021149532418424127 }, { "rank": 20, "variant": "a200_r100_w130", "code_sha256": "d8bca3c69a4b5031019a04e205cd75beb38a655eb7860cc9cff61f75d68f19a5", "n": 2000, "mean_edge": 521.76511941836, "mean_diff": -2.1156500008319226, "se": 0.0212842415423577 } ] }, "reproduction": { "results": [ { "name": "CH", "sha256": "6dd68f77a70900319460215374143dbd5d924198450a46d9f5f91f6b1e3d35c3", "seed_start": 0, "n": 1000, "mean_edge": 525.5258821780834, "se": 2.7894264590251843 }, { "name": "NP", "sha256": "95d21646a5b6d293c86c36a184769477be7b1ff39ab2adde7668ed79fb22dd38", "seed_start": 0, "n": 1000, "mean_edge": 526.0337302497852, "se": 2.7912248204542776 } ], "np_minus_ch": { "n": 1000, "mean_diff": 0.5078480717017371, "se": 0.02478168812598005 }, "interpretation": "Calibration only: these supplied reproduction seeds are not independent promotion evidence. No fresh StarterStrategy comparison was requested for this item or performed." }, "methodology": { "engine_commit": "6b6921f8d463314aa7c96234e1be25a25245f704", "normalizer": "Each candidate and NP is simulated separately against the same fixed 30 bps VanillaStrategy. Paired diff is candidate submission edge minus NP submission edge for the same seed; it is not a candidate-versus-NP liquidity-pool matchup.", "parameter_draws": "numpy.random.default_rng(seed): uniform(19,21) size, uniform(0.6,1.0) arrival rate, uniform(0.000882,0.001008) sigma, in that order. 10000 steps; initial price 100; reserves 100 X, 10000 Y; zero drift; dt 1; retail size sigma 1.2; buy probability 0.5. Price seed=seed; retail seed=seed+1.", "se": "Sample standard deviation (ddof=1) of paired seed differences divided by sqrt(n). Score SE uses raw submission edges.", "tuning": "Initial 2x2x2 endpoint grid: alpha {0.20,0.35}, retail {0.03,0.10}, weight {0.07,0.13}. Following early endpoint losses, fixed a second 2x2x2 grid: alpha {0.25,0.30}, retail {0.05,0.07}, weight {0.085,0.115}. Final 2x2 grid: alpha {0.26,0.28}, retail {0.055,0.065}, weight fixed at 0.13. Every cell uses 30000..31999 only, n=2000. Select highest tuning mean difference across all 20 cells. No holdout data used for selection.", "frozen_variant": "a260_r55_w130", "tuning_seeds_covered": [ 30000, 31999 ], "holdout_seeds_covered": [ 800000, 801999 ], "holdout_evaluations_per_strategy": 1, "excluded_seed_block": "900000..909999 was never simulated.", "runtime": "Wall-clock seconds per simulation for the frozen candidate fresh run, excluding compilation, with eight Rust workers. Includes config generation and result extraction. This is batch wall time / n, not CPU time.", "limits": "Only slots 0..10 referenced; two allowed imports; no loops in candidate. Rust EVM callback limits are 250000 gas. CLI validation passed for StarterStrategy, NP, and frozen candidate." }, "checks": { "setup": "Supplied scratch/setup.sh run once from pinned checkout root; exit 0; starter validation passed.", "candidate_validation": "Validating strategy...\nCompiling strategy...\nStrategy 'no_cubic' validated successfully!", "arithmetic": "Original and unrolled exponentiation compared for every exponent 0..8 over 106 factors, including the strategy decay factors; all 954 comparisons matched.", "completed_tuning_cells": 20, "tuning_simulations": 40000, "reference_tuning_simulations": 2000, "fresh_candidate_simulations": 2000, "fresh_reference_simulations": 2000, "calibration_simulations": 3000 }, "citations": [ { "url": "https://raw.githubusercontent.com/ChengHua926/amm-challenge/d34a5199c59a4c44d5336a25f1436b4ae1f21104/contracts/src/Strategy.sol", "usage": "Pinned CH source and its two initial smoothing constants. NP insertion is supplied by the task, not claimed as content of this URL." }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py", "usage": "Canonical seed-indexed parameter draws and run_batch invocation." }, { "url": "https://raw.githubusercontent.com/jiayaoqijia/amm-challenge-yq/main/README.md", "usage": "Public background: adaptive shock-gated fair-price tracking and first-trade alpha. This write-up did not supply measured results here." }, { "url": "https://raw.githubusercontent.com/dipankar/amm-challenge/main/ANALYSIS.md", "usage": "Public background: state estimation and implied-price reconstruction. Its reported scores were not treated as our measurements." }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py", "usage": "Canonical randomized simulation parameter ranges." }, { "url": "https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_sim_rs/src/evm/strategy.rs", "usage": "250000-gas initialization and trade callback limits." } ] }