Optimal Trading Stops and Algorithmic Trading

20 Pages Posted: 21 Jan 2014

Date Written: January 19, 2014

Abstract

Trading stops are often used by traders to risk manage their positions. In this note, we show how to derive optimal trading stops for generic algorithmic trading strategies when the P&L of the position is modelled by a Markov modulated diffusion. Optimal stop levels are derived by maximising the expected discounted utility of the P&L. The approach is independent of the signal used to enter the position. We analyse in details the case of trading signals with a limited (random) life. We show how to calibrate the model to market data and present a series of numerical examples to illustrate the main features of the approach.

Keywords: Trading stops, Algorithmic trading, Stop loss, Target profit, Utility functions, Markov chain, Calibration

JEL Classification: C51, G12, G13

Suggested Citation

Di Graziano, Giuseppe, Optimal Trading Stops and Algorithmic Trading (January 19, 2014). Available at SSRN: https://ssrn.com/abstract=2381830 or http://dx.doi.org/10.2139/ssrn.2381830

Giuseppe Di Graziano (Contact Author)

Deutsche Bank AG ( email )

Winchester House
1 Great Winchester Street
London, EC2N 2DB
United Kingdom

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