Technical Analysis of the Taiwanese Stock Market

We study the profitability of technical trading rules based on 9 popular technical indicators. To further examine whether investors can design technical trading strategies that can beat the buy-and-hold strategy, we establish 13 trading models based on one indicator, 25 models based on two indicators, and 28 models based on three indicators. The empirical results show that 58 out of 66 models reject the null hypothesis of equality of the mean returns between buy days and sell days. Our findings provide support for the predictive power of technical trading rules. Finally we employ Hansen’s (2005) Superior Predictive Ability to investigate data snooping problem. Overall we observe an inverse association between the number of technical indicator combinations and trading profitability.

[1]  P. Hansen A Test for Superior Predictive Ability , 2005 .

[2]  Metghalchi Massoud,et al.  Trading Rules for the Abu Dhabi Stock Index , 2011 .

[3]  Chin-Sheng Huang,et al.  Technical Analysis, Investment Psychology, and Liquidity Provision: Evidence from the Taiwan Stock Market , 2010 .

[4]  B. LeBaron,et al.  Simple Technical Trading Rules and the Stochastic Properties of Stock Returns , 1992 .

[5]  Nikolaos Eriotis,et al.  How rewarding is technical analysis? Evidence from Athens Stock Exchange , 2006, Oper. Res..

[6]  Min Wu,et al.  Technical Trading-Rule Profitability, Data Snooping, and Reality Check: Evidence from the Foreign Exchange Market , 2005 .

[7]  Profiting from a contrarian application of technical trading rules in the US stock market , 2009 .

[8]  D. Power,et al.  An analysis of trading strategies in eleven European stock markets , 2005 .

[9]  Ownership Restriction, Information Diffusion Speed, and the Performance of Technical Trading Rules in Chinese Domestic and Foreign Shares Markets , 2007 .

[10]  Guofu Zhou,et al.  Technical analysis: An asset allocation perspective on the use of moving averages , 2009 .

[11]  Yixi Ning,et al.  Validation of Moving Average Trading Rules: Evidence From Hong Kong, Singapore, South Korea, Taiwan , 2009 .

[12]  C. Lento,et al.  Investment information content in Bollinger Bands? , 2007 .

[13]  Mark P. Taylor,et al.  The Obstinate Passion of Foreign Exchange Professionals : , 2006 .

[14]  Cheolbeom Park,et al.  What Do We Know About the Profitability of Technical Analysis? , 2007 .

[15]  The Combined Signal Approach to Technical Analysis: A Review & Commentary , 2009 .

[16]  S. Mitra Usefulness of Moving Average Based Trading Rules in India , 2011 .

[17]  Richard J. Kish,et al.  Technical trading strategies and return predictability: NYSE , 2002 .

[18]  Mark Larson Moving Average Convergence/Divergence (MACD) , 2012 .

[19]  R. Sweeney,et al.  Beating the Foreign Exchange Market , 1986 .

[20]  M. McKenzie,et al.  Technical Trading Rules in Emerging Markets and the 1997 Asian Currency Crises , 2007 .

[21]  P. Weller,et al.  The Predictive Power of Head-and-Shoulders Price Patterns in the U.S. Stock Market , 2006 .

[22]  Gerald Appel,et al.  Technical Analysis: Power Tools for Active Investors , 2005 .

[23]  Technical trading strategies and cross-national information linkage: the case of Taiwan stock market , 2006 .

[24]  Joseph E. Granville Granville's New strategy of daily stock market timing for maximum profit , 1976 .

[25]  J. Murphy Technical Analysis of the Financial Markets , 1999 .

[26]  Mark P. Taylor,et al.  The use of technical analysis in the foreign exchange market , 1992 .

[27]  Elaine Loh,et al.  An alternative test for weak form efficiency based on technical analysis , 2007 .

[28]  Mark P. Taylor,et al.  The Obstinate Passion of Foreign Exchange Professionals: Technical Analysis , 2007 .

[29]  S. Mengoli,et al.  On the source of contrarian and momentum strategies in the Italian equity market , 2004 .

[30]  T. Mills,et al.  Calendar effects in the London Stock Exchange FT-SE indices , 1995 .

[31]  A. Milionis,et al.  A test of significance of the predictive power of the moving average trading rule of technical analysis based on sensitivity analysis: application to the NYSE, the Athens Stock Exchange and the Vienna Stock Exchange. Implications for weak-form market efficiency testing , 2011 .

[32]  Microstructure and Seasonality in the UK Equity Market , 1997 .

[33]  Wing-Keung Wong,et al.  *Efficiency of the Taiwan Stock Market , 2009 .

[34]  Scott H. Irwin,et al.  A test of futures market disequilibrium using twelve different technical trading systems , 1988 .

[35]  Gary Chen,et al.  The Chinese Stock Market: An Examination of the Random Walk Model and Technical Trading Rules , 2007 .

[36]  H. White,et al.  A Reality Check for Data Snooping , 2000 .

[37]  Camillo Lento Tests of Technical Trading Rules in the Asian-Pacific Equity Markets: A Bootstrap Approach , 2008 .