Optimal control of execution costs for portfolios

D. Bertimas, Andrew W. Lo, Patrik Hummel

Computing in Science & Engineering · 1999 · 68 citations · 16 references

Concepts

Abstract

The authors apply stochastic dynamic programming to derive trading strategies that minimize the expected cost of executing a portfolio of securities over a fixed time period. They test their strategies using real-world stock data.

References

16