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Technical trading rules for nonlinear dynamics of stock returns: evidence from the G-7 stock markets
Authors:Kwang-il Choe  Joshua Krausz  Kiseok Nam
Institution:(1) Department of Economics, Minnesota State University, Mankato, MN 56001, USA;(2) Sy Syms School of Business, Yeshiva University, 500 W. 185th Street, New York, NY 10033, USA;;
Abstract:This paper explores a possible link between an asymmetric dynamic process of stock returns and profitable technical trading rules. Using the G-7 stock market indexes, we show that the dynamic process of daily index returns is better characterized by nonlinearity arising from an asymmetric reverting property. The asymmetric reverting property of stock returns is exploitable in generating profitable buy and sells signals for technical trading strategies. The bootstrap analysis shows that not all nonlinearities generate profitable buy and sell signals, but rather only the nonlinearities generating a consistent asymmetrical pattern of return dynamics can be exploitable for the profitability of the trading rules. The significant positive (negative) returns from buy (sell) signals are a consequence of trading rules that exploit the asymmetric nonlinear dynamics of the stock returns that revolve around positive (negative) unconditional mean returns under prior positive (negative) return patterns. Our results corroborate the arguments for the usefulness of technical trading strategies in stock market investments.
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