Optimal Execution of Portfolio Transactions with Short-Term Alpha
In recent years, we have witnessed an increasing use of quantitative modeling tools and data processing infrastructure by high frequency trading firms and automated market makers. They monetize the value of the options written by institutional trade algorithms with every order placement on the market. This creates a challenge for institutional traders. The result for institutions is that trades with poor market timing typically execute too fast and those that have high urgency tend to execute too slowly and sometimes fail to complete. When the market controls the execution schedule, it is seldom to the advantage of the institutional trader.
To cope with this problem, the trader needs to perform three challenging tasks. First, develop an understanding of how urgent a trade is, i.e., when the benefits of speedier execution outweigh the additional impact costs. Second, map this urgency to an optimal execution schedule; and, third, implement the schedule efficiently in the presence of market noise – a stochastic optimization problem. The industry is increasingly working to solve each of these three problems.
Our purpose in this chapter is to address the second task: assign an optimal trade schedule given a view on short-term alpha. To this end, we propose an alternative framework to AC 2000 that is based on more realistic assumptions for market impact and ...