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Trading Rules (trading + rule)
Kinds of Trading Rules 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] 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] On 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] Direction-of-change forecasting using a volatility-based recurrent neural networkJOURNAL OF FORECASTING, Issue 5 2008S. D. Bekiros Abstract This paper investigates the profitability of a trading strategy, based on recurrent neural networks, that attempts to predict the direction-of-change of the market in the case of the NASDAQ composite index. The sample extends over the period 8 February 1971 to 7 April 1998, while the sub-period 8 April 1998 to 5 February 2002 has been reserved for out-of-sample testing purposes. We demonstrate that the incorporation in the trading rule of estimates of the conditional volatility changes strongly enhances its profitability, after the inclusion of transaction costs, during bear market periods. This improvement is being measured with respect to a nested model that does not include the volatility variable as well as to a buy-and-hold strategy. We suggest that our findings can be justified by invoking either the ,volatility feedback' theory or the existence of portfolio insurance schemes in the equity markets. Our results are also consistent with the view that volatility dependence produces sign dependence. Copyright © 2008 John Wiley & Sons, Ltd. [source] The economic value of volatility transmission between the stock and bond marketsTHE JOURNAL OF FUTURES MARKETS, Issue 11 2008Helena Chuliá This study has two main objectives. Firstly, volatility transmission between stocks and bonds in European markets is studied using the two most important financial assets in these fields: the DJ Euro Stoxx 50 index futures contract and the Euro Bund futures contract. Secondly, a trading rule for the major European futures contracts is designed. This rule can be applied to different markets and assets to analyze the economic significance of volatility spillovers observed between them. The results indicate that volatility spillovers take place in both directions and that the stock-bond trading rule offers very profitable returns after transaction costs. These results have important implications for portfolio management and asset allocation. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:1066,1094, 2008 [source] On 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] Bootstrapping Financial Time SeriesJOURNAL OF ECONOMIC SURVEYS, Issue 3 2002Esther Ruiz It is well known that time series of returns are characterized by volatility clustering and excess kurtosis. Therefore, when modelling the dynamic behavior of returns, inference and prediction methods, based on independent and/or Gaussian observations may be inadequate. As bootstrap methods are not, in general, based on any particular assumption on the distribution of the data, they are well suited for the analysis of returns. This paper reviews the application of bootstrap procedures for inference and prediction of financial time series. In relation to inference, bootstrap techniques have been applied to obtain the sample distribution of statistics for testing, for example, autoregressive dynamics in the conditional mean and variance, unit roots in the mean, fractional integration in volatility and the predictive ability of technical trading rules. On the other hand, bootstrap procedures have been used to estimate the distribution of returns which is of interest, for example, for Value at Risk (VaR) models or for prediction purposes. Although the application of bootstrap techniques to the empirical analysis of financial time series is very broad, there are few analytical results on the statistical properties of these techniques when applied to heteroscedastic time series. Furthermore, there are quite a few papers where the bootstrap procedures used are not adequate. [source] How efficient is the European football betting market?JOURNAL OF FORECASTING, Issue 5 2009Evidence from arbitrage, trading strategies Abstract This paper assesses the international efficiency of the European football betting market by examining the forecastability of match outcomes on the basis of the information contained in different sets of online and fixed odds quoted by six major bookmakers. The paper also investigates the profitability of strategies based on: combined betting, simple heuristic rules, regression models and prediction encompassing. The empirical results show that combined betting across different bookmakers can lead to limited but highly profitable arbitrage opportunities. Simple trading rules and betting strategies based on forecast encompassing are found capable of also producing significant positive returns. Despite the deregulation, globalization and increased competition in the betting industry over recent years, the predictabilities and profits reported in this paper are not fully consistent with weak-form market efficiency. Copyright © 2008 John Wiley & Sons, Ltd. [source] INSIDER TRADING, REGULATION, AND THE COMPONENTS OF THE BID,ASK SPREADTHE JOURNAL OF FINANCIAL RESEARCH, Issue 3 2008Bart Frijns Abstract In this article we investigate the relation between insider trading regulations and the bid,ask spread. We decompose the spread into its components before and after the enactment of strict new insider trading rules in New Zealand. We find that the enactment led to a significant decrease in the information asymmetry component of the spread, which is observed mainly in illiquid and high prechange information asymmetry companies. These findings are robust to model specification. In addition, we find a decrease in the contribution of information asymmetry to price volatility. [source] Implied volatility forecasts in the grains complexTHE JOURNAL OF FUTURES MARKETS, Issue 10 2002David P. Simon This article finds that the implied volatilities of corn, soybean, and wheat futures options 4 weeks before option expiration have significant predictive power for the underlying futures contract return volatilities through option expiration from January 1988 through September 1999. These implied volatilities also encompass the information in out-of-sample seasonal Glosten, Jagannathan, and Runkle (GJR;1993) volatility forecasts. Evidence also demonstrates that when corn-implied volatility rises relative to out-of-sample seasonal GJR volatility forecasts, implied volatility substantially overpredicts realized volatility. However, simulations of trading rules that involve selling corn option straddles when corn-implied volatility is high relative to out-of-sample GJR volatility forecasts indicate that none of the trading rules would have been significantly profitable. This finding suggests that these options are not necessarily overpriced. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:959,981, 2002 [source] | ||||||||||||||||||||||