Optimal Trend Following Trading Rules

被引:18
作者
Dai, Min [1 ,2 ]
Yang, Zhou [3 ]
Zhang, Qing [4 ]
Zhu, Qiji Jim [5 ]
机构
[1] Natl Univ Singapore, Dept Math, 10 Kent Ridge Crescent, Singapore 117548, Singapore
[2] Natl Univ Singapore, Risk Management Inst, Singapore 117548, Singapore
[3] S China Normal Univ, Sch Math Sci, Guangzhou, Guangdong, Peoples R China
[4] Univ Georgia, Dept Math, Athens, GA 30602 USA
[5] Western Michigan Univ, Dept Math, Kalamazoo, MI 49008 USA
关键词
trend following trading rule; bull-bear switching model; partial information; Hamilton-Jacobi-Bellman equations; TRANSACTION COSTS; PORTFOLIO SELECTION; BUY-LOW; INVESTMENT; CONSUMPTION; STRATEGIES; MODEL;
D O I
10.1287/moor.2015.0743
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
This paper is concerned with the optimality of a trend following trading rule. The underlying market is modeled like a bull-bear switching market in which the drift of the stock price switches between two states:the uptrend (bull market) and the down trend (bear market). We consider the case when the market mode is not directly observable and model the switching process as a hidden Markov chain. This is a continuation of our earlier study reported in Dai et al. [Dai M, Zhang Q, Zhu Q (2010) Trend following trading under a regime-switching model. SIAM J. Fin. Math. 1:780-810] where a trend following rule is obtained in terms of a sequence of stopping times. Nevertheless, a severe restriction imposed in Dai et al. [Dai M, Zhang Q, Zhu Q (2010) trend following trading under a regime-switching model. SIAM J. Fin. Math. 1:780-810] is that only a single share can be traded over time. As a result, the corresponding wealth process is not self-financing. In this paper, we relax this restriction. Our objective is to maximize the expected log-utility of the terminal wealth. We show, via a thorough theoretical analysis, that the optimal trading strategy is trend following. Numerical simulations and backtesting, in support of our theoretical findings, are also reported.
引用
收藏
页码:626 / 642
页数:17
相关论文
共 50 条
[21]   Optimal dynamic basis trading [J].
Angoshtari, Bahman ;
Leung, Tim .
ANNALS OF FINANCE, 2019, 15 (03) :307-335
[22]   Weekly Quantitative Analysis and Trend Trading in Futures Market [J].
Masteika, Saulius ;
Driaunys, Kestutis ;
Moskaliova, Vera .
BUSINESS INFORMATION SYSTEMS WORKSHOPS, BIS 2012, 2012, 127 :61-68
[23]   Optimal pairs trading with dynamic mean-variance objective [J].
Zhu, Dong-Mei ;
Gu, Jia-Wen ;
Yu, Feng-Hui ;
Siu, Tak-Kuen ;
Ching, Wai-Ki .
MATHEMATICAL METHODS OF OPERATIONS RESEARCH, 2021, 94 (01) :145-168
[24]   Does Data Frequency Matter for Trading Signals Emitted by Various Technical Trading Rules? [J].
Ni, Yensen ;
Day, Min-Yuh ;
Huang, Paoyu .
PACIFIC BUSINESS REVIEW INTERNATIONAL, 2019, 11 (10) :7-17
[25]   Optimal consumption-portfolio rules with biased beliefs [J].
Hou, Shehong ;
Niu, Yingjie ;
Yang, Jinqiang .
ECONOMICS LETTERS, 2018, 173 :152-157
[26]   Optimal liquidation using extended trading close for multiple trading days [J].
Zhu, Jianchang ;
Zhang, Leilei ;
Sun, Xuchu .
FINANCIAL INNOVATION, 2024, 10 (01)
[27]   Predictability in bond returns using technical trading rules [J].
Shynkevich, Andrei .
JOURNAL OF BANKING & FINANCE, 2016, 70 :55-69
[28]   Trading rules, competition for order flow and market fragmentation [J].
Kwan, Amy ;
Masulis, Ronald ;
McInish, Thomas H. .
JOURNAL OF FINANCIAL ECONOMICS, 2015, 115 (02) :330-348
[29]   Predictability of nonlinear trading rules in the US stock market [J].
Chong, Terence Tai-Leung ;
Lam, Tau-Hing .
QUANTITATIVE FINANCE, 2010, 10 (09) :1067-1076
[30]   Time series momentum and moving average trading rules [J].
Marshall, Ben R. ;
Nguyen, Nhut H. ;
Visaltanachoti, Nuttawat .
QUANTITATIVE FINANCE, 2017, 17 (03) :405-421