A Mathematical Analysis of Technical Analysis. Issue 1 (2nd January 2019)

• Record Type: Journal Article
• Authors: Lorig, Matthew; Zhou, Zhou; Zou, Bin
• Is Part Of: Applied mathematical finance. Volume 26:Issue 1(2019)
• Page Start: 38
• Page End: 68
• Publication Date: 2019-01-02
• Subjects: Long-term growth -- continuous-time markov chain -- moving average -- optimal investment -- ornstein-uhlenbeck process -- partial information -- simulation -- utility maximization; Business mathematics -- Periodicals; 650.0151
• DOI: 10.1080/1350486X.2019.1588136
• Languages: English
• ISSNs: 1350-486X

Abstract

ABSTRACT: In this paper, we investigate trading strategies based on exponential moving averages (ExpMAs) of an underlying risky asset. We study both logarithmic utility maximization and long-term growth rate maximization problems and find closed-form solutions when the drift of the underlying is modelled by either an Ornstein-Uhlenbeck process or a two-state continuous-time Markov chain. For the case of an Ornstein-Uhlenbeck drift, we carry out several Monte Carlo experiments in order to investigate how the performance of optimal ExpMA strategies is affected by variations in model parameters and by transaction costs.