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Abstract
Arrival price algorithms determine optimal trade schedules by balancing the market impact cost of rapid execution against the volatility risk of slow execution. In the standard formulation, mean variance optimal strategies are static: they do not modify the execution speed in response to price motions observed during trading. We show that with a more realistic formulation of the mean variance tradeoff, and even with no momentum or mean reversion in the price process, substantial improvements are possible for adaptive strategies that spend trading gains to reduce risk, by accelerating execution when the price moves in the trader's favor. The improvement is larger for large initial positions.
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