Portfolio Management and Optimal Execution Via Convex Optimization
Author | : Enzo Busseti |
Publisher | : |
Total Pages | : |
Release | : 2018 |
ISBN-10 | : OCLC:1035646073 |
ISBN-13 | : |
Rating | : 4/5 (73 Downloads) |
Book excerpt: We study three related applications, in the field of finance, and in particular of multi-period investment management, of convex optimization and model predictive control. First, we look at the classical multi-period trading problem, consisting in trading assets within a certain universe for a sequence of periods in time. We develop a framework for single- and multi-period optimization: the trades in each period are found by solving a convex optimization problem that trades off expected return, risk, transaction cost and holding cost. Second, we look at the classical Kelly gambling problem, consisting in repeatedly allocating wealth among bets so as to maximize the expected growth rate of wealth. We develop a convex constraint that controls the risk of drawdown, i.e., the risk of losing a certain (high) amount of wealth. Third, we look at an optimal execution problem, consisting in buying, or selling, a given quantity of some asset on a limit-order book market. We study the case when the execution is benchmarked to the market volume weighted average price, and the objective is to minimize the mean-variance of the slippage. In all three cases, we provide extensive numerical simulations (using real-world data, whenever possible), developed as open-source software. In practice, these problems are solved to high accuracy in little time on commodity hardware, thanks to strong theoretical guarantees from modern convex optimization and a rich and growing ecosystem of open source software.