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Moving Average Trading Rules (moving + average_trading_rule)
Selected AbstractsOn the Use of the Moving Average Trading Rule to Test for Weak Form Efficiency in Capital MarketsECONOMIC NOTES, Issue 2 2008Alexandros E. Milionis The examination for the possible existence of predictive power in the moving average trading rule has been used extensively to test the hypothesis of weak form market efficiency in capital markets. This work focuses mainly on the study of the variation of the moving average (MA) trading rule performance as a function of the length of the longer MA. Empirical analysis of daily data from NYSE and the Athens Stock Exchange reveal high variability of the performance of the MA trading rule as a function of the MA length and on some occasions the series of successive trading rule total returns is non-stationary. These findings have direct implications in weak form market efficiency testing. Indeed, given this high variability of the performance of the MA trading rule, by just finding out that trading rules with some specific combinations of MA lengths can or cannot beat the market, as is the case in most of the published work thus far, is not enough evidence for or against the existence of weak form market efficiency. Results also show that on average in about three out of four cases trading rule signals are false, a fact that leaves a lot of space for improved trading rule performance if trading rule signals are combined with other information (e.g. filters, or volume of trade). Finally, some evidence of enhanced trading rule performance for the shorter MA lengths was found. This enhanced performance is partly attributed to the higher probability that a trading rule signal is not a whipsaw, as well as to the larger number of days out-of-the-market which are associated with shorter MA lengths. [source] The economic value of technical trading rules: a nonparametric utility-based approachINTERNATIONAL JOURNAL OF FINANCE & ECONOMICS, Issue 1 2005Hans Dewachter Abstract We adapt Brandt's (1999) nonparametric approach to determine the optimal portfolio choice of a risk averse foreign exchange investor who uses moving average trading signals as the information instrument for investment opportunities. Additionally, we assess the economic value of the estimated optimal trading rules based on the investor's preferences. The approach consists of a conditional generalized method of moments (GMM) applied to the conditional Euler optimality conditions. The method presents two main advantages: (i) it avoids ad hoc specifications of statistical models used to explain return predictability; and (ii) it implicitly incorporates all return moments in the investor's expected utility maximization problem. We apply the procedure to different moving average trading rules for the German mark,US dollar exchange rate for the period 1973,2001. We find that technical trading rules are partially recovered and that the estimated optimal trading rules represent a significant economic value for the investor. Copyright © 2005 John Wiley & Sons, Ltd. [source] Simple Trading Rules and the Market for Internet StocksINTERNATIONAL REVIEW OF FINANCE, Issue 4 2001Wai Mun Fong We investigate the profitability of moving average trading rules for Internet stocks based on the Dow Jones Internet Composite Index. Consistent with previous studies e.g. Brock et al. (1992), returns after buy signals exceed returns after sell signals. The average buy,sell spread is large and significant even after accounting for transaction costs. Bootstrap simulations based on a version of the dynamic CAPM show that the model is able to replicate the pattern of buy and sell returns. Simulated buy,sell spreads amount on average to more than 39% of the actual spread. However, actual profits are still too large to be explained in terms of risk compensation. [source] | ||||||||||