Title :
Optimality conditions for a trend-following strategy
Author :
Kong, Hoi Tin ; Zhang, Qing ; Yin, G. George
Author_Institution :
Dept. of Math., Univ. of Georgia, Athens, GA, USA
Abstract :
Based on trend-following trading strategies that are widely used in the investment world, this work provides a set of sufficient conditions that determines the optimality of the traditional trend-following strategies when the trends are completely observable. A dynamic programming approach is used to verify the optimality under these conditions. The value functions are characterized by the associated HJB equations, and are shown to be either linear functions or infinity depending on the parameter values. The results reveal two counter-intuitive facts: (a) trend following may not lead to optimal reward in some cases even when/if the investor knows exactly when a trend change occurs; (b) stock volatility is not relevant in trend following when trends are observable.
Keywords :
dynamic programming; investment; share prices; stock markets; HJB equation; Hamilton-Jacobi-Bellman equation; dynamic programming approach; infinity function; investment; linear function; optimal reward; optimality condition; stock price dynamics; stock volatility; sufficient condition; trend-following trading strategy; Closed-form solutions; Dynamic programming; Equations; Investments; Mathematical model; Switches; quasi-variational inequality; regime-switching process; trend-following strategy;
Conference_Titel :
Decision and Control and European Control Conference (CDC-ECC), 2011 50th IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-61284-800-6
Electronic_ISBN :
0743-1546
DOI :
10.1109/CDC.2011.6160490