A Stochastic Approximation Approach for Trend-Following Trading

Duy Nguyen (), George Yin () and Qing Zhang ()
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Duy Nguyen: The University of Georgia
George Yin: Wayne State University
Qing Zhang: The University of Georgia

Chapter Chapter 7 in Hidden Markov Models in Finance, 2014, pp 167-184 from Springer

Abstract: Abstract This work develops a feasible computation procedure for trend-following trading under a bull-bear switching market model. In the asset model, the drift of the stock price switches between two parameters corresponding to an uptrend (bull market) and a downtrend (bear market) according to a partially observable Markov chain. The objective is to buy and sell the underlying stock to maximize an expected return. It is shown in Dai et al. (SIAM J Financ Math 1:780–810, 2010; Optimal trend following trading rules. Working paper) that an optimal trading strategy can be obtained in terms of two threshold levels. Finding the threshold levels turns out to be a difficult task. In this paper, we develop a stochastic approximation algorithm to approximate the threshold levels. One of the main advantages of this approach is that one need not solve the associated HJB equations. We also establish the convergence of the algorithm and provide numerical examples to illustrate the results.

Keywords: Stock Price; Sample Path; Stochastic Approximation; Sharpe Ratio; Bear Market (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-1-4899-7442-6_7

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