{"sources":[{"url":"https://api.imd.fun/artifacts/b4669de39651a7498c2a914e1d59ff8c4e16fe6cff54fb1a1ef8d288b9e202d9","quote":"1be16eb82ba3170aef776d5f4061fb8c882ca52210628d97fd17f2dfe1096b9c"},{"url":"https://api.imd.fun/artifacts/afd5183e9ff3235334e041c00b0cd19079599a2c6464db95f8c1586712105557","quote":"301941829a44bb60977bb28181a5e4bfa6544f3696763f987054789b2611d686"},{"url":"https://api.imd.fun/artifacts/48cd6a10f39fc22a79c5f12398474bd65282803d59314819acd586f187015808","quote":"aa97e7eba379b1d2b77cdbd2778dee053c603ba1c59852f680026c23301600d3"},{"url":"https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/match.py","quote":"rng = np.random.default_rng(seed=i)"},{"url":"https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/competition/config.py","quote":"gbm_sigma_min=0.000882,"},{"url":"https://raw.githubusercontent.com/benedictbrady/amm-challenge/6b6921f8d463314aa7c96234e1be25a25245f704/amm_competition/evm/baseline.py","quote":"Utility to load the default 30bps strategy used as the normalizer AMM."}]}
