Decomposing the predictive performance of the moving average trading rule of technical analysis: the contribution of linear and non linear dependencies in stock returns
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- Alexandros E. Milionis & Evangelia Papanagiotou, 2013. "Decomposing the predictive performance of the moving average trading rule of technical analysis: the contribution of linear and non-linear dependencies in stock returns," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(11), pages 2480-2494, November.
References listed on IDEAS
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- Liu, Xiaojia & An, Haizhong & Wang, Lijun & Jia, Xiaoliang, 2017. "An integrated approach to optimize moving average rules in the EUA futures market based on particle swarm optimization and genetic algorithms," Applied Energy, Elsevier, vol. 185(P2), pages 1778-1787.
- Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
More about this item
KeywordsMarket Efficiency; Technical Analysis; Moving Average Trading Rules; Athens Stock Exchange.;
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
- C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2011-11-28 (All new papers)
- NEP-EFF-2011-11-28 (Efficiency & Productivity)
- NEP-FOR-2011-11-28 (Forecasting)
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