Getting more for less: better A / B testing via causal regularisation
A causal machine learning algorithm is used to estimate trades’ price impact
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Causal regularisation solves several practical problems in live trading applications: estimating the price impact when alpha is unknown and estimating alpha when price impact is unknown. In addition, it increases the value of small A / B tests, allowing more robust conclusions to be drawn from live trading experiments that are smaller than those for traditional
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