Dancing in the Dark: Optimal Liquidity Search under Portfolio Constraints

Abstract

One of the core responsibilities of many institutional traders is managing cash and risk constraints of a portfolio. Traders often do not take advantage of dark trading and block trading because of the risk of an unpredictable and unbalanced change to the composition of the executing list. Said differently, the randomness of dark fills makes it very difficult to constrain an optimization using dark as the only source of liquidity. In this article, the authors offer a solution to this problem using stochastic programming to create linear constraints for a quadratic optimization. They believe this research can be used by algorithm designers to bridge the gap between two dissimilar, yet useful, products: dark aggregation and portfolio trading algorithms.