Revisiting the Performance of MACD and RSI Oscillators

Chong and Ng (2008) find that the Moving Average Convergence–Divergence (MACD) and Relative Strength Index (RSI) rules can generate excess return in the London Stock Exchange. This paper revisits the performance of the two trading rules in the stock markets of five other OECD countries. It is found that the MACD(12,26,0) and RSI(21,50) rules consistently generate significant abnormal returns in the Milan Comit General and the S&P/TSX Composite Index. In addition, the RSI(14,30/70) rule is also profitable in the Dow Jones Industrials Index. The results shed some light on investors’ belief in these two technical indicators in different developed markets.

[1]  D. de la Fuente,et al.  Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies , 2013 .

[2]  Mieko Tanaka-Yamawaki,et al.  Adaptive use of technical indicators for the prediction of intra-day stock prices , 2007 .

[3]  Susan M. Mangiero International Momentum Strategies , 1998 .

[4]  Application of financial analysis techniques to vital sign data : A novel method of trend interpretation in the intensive care unit , 2007 .

[5]  Terence Tai-Leung Chong,et al.  Technical analysis and the London stock exchange: testing the MACD and RSI rules using the FT30 , 2008 .

[6]  J. Wilder New Concepts in Technical Trading Systems , 1978 .

[7]  Hujun Yin,et al.  Exchange rate prediction using hybrid neural networks and trading indicators , 2009, Neurocomputing.

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

[9]  E. Fama EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .

[10]  Franklin Allen,et al.  Using genetic algorithms to find technical trading rules , 1999 .

[11]  Salih N Neftci,et al.  Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis." , 1991 .

[12]  C. Granger,et al.  Efficient Market Hypothesis and Forecasting , 2002 .

[13]  J. Murphy Technical Analysis of the Futures Markets: A Comprehensive Guide to Trading Methods and Applications , 1986 .

[14]  David Power,et al.  The profitability of moving average trading rules in South Asian stock markets , 2001 .

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

[16]  Michael C. Jensen,et al.  Random Walks and Technical Theories: Some Additional Evidence , 1970 .

[17]  Terence C. Mills,et al.  Technical Analysis and the London Stock Exchange: Testing Trading Rules Using the FT30 , 1997 .

[18]  Robert Ferguson,et al.  In Defense of Technical Analysis , 1985 .

[19]  Haiqiang Chen,et al.  A principal-component approach to measuring investor sentiment , 2010 .

[20]  H. White,et al.  Data‐Snooping, Technical Trading Rule Performance, and the Bootstrap , 1999 .

[21]  Terence Tai Leung Chong,et al.  Do Momentum-based Strategies Work in Emerging Currency Markets? , 2009 .

[22]  Terence Tai Leung Chong,et al.  Do Technical Analysts Outperform Novice Traders: Experimental Evidence , 2013 .

[23]  Numan Ülkü,et al.  Drivers of technical trend-following rules' profitability in world stock markets , 2013 .

[24]  Kalok Chan,et al.  The profitability of technical trading rules in the Asian stock markets , 1995 .

[25]  Robert Hudson,et al.  A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices - 1935 to 1994 , 1996 .

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