An inverse framework uses quantile-normalized orderbook data and machine learning models to predict allocative efficiency in double auctions from bids, asks, and prices without knowing induced values.
An experimental study of competitive market behavior.Journal of Political Economy, 70(2):111–137, 1962
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An `Inverse' Experimental Framework to Estimate Market Efficiency
An inverse framework uses quantile-normalized orderbook data and machine learning models to predict allocative efficiency in double auctions from bids, asks, and prices without knowing induced values.