Revisiting the Performance of MACD and RSI Oscillators

Chong, Terence Tai-Leung and Ng, Wing-Kam and Liew, Venus Khim-Sen (2014): Revisiting the Performance of MACD and RSI Oscillators.

Abstract

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’ believe in these two technical indicators in different developed markets.

• Item Type: MPRA Paper
• Language: English
• Keywords: Relative Strength Index; Trading Rules; Moving Average Convergence-Divergence.
• Subjects: G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency ; Event Studies ; Insider Trading

References

Allen, F. and R. Karjalainen, 1999. Using genetic algorithms to find technical trading rules. Journal of Financial Economics 51, 245-271.

Bessembinder, H. and K. Chan, 1995. The profitability of technical rules in the Asian stock markets. Pacific-Basin Finance Journal 3, 257 - 284.

Brock, W., J. Lakonishok and B. LeBaron, 1992. Simple technical trading rules and the stochastic properties of stock returns. Journal of Finance 5, 1731-1764.

Chen, H., T. T. L. Chong and X. Duan, 2010. A principal-component approach to measuring investor sentiment. Quantitative Finance 10(4), 339-347.

Chong, T. T. L. and H. Ip, 2009. Do momentum-based strategies work in emerging currency markets? Pacific-Basin Finance Journal 17, 479-493.

Chong, T. T. L. and W. K. Ng. 2008. Technical analysis and the London stock exchange: testing the MACD and RSI rules using the FT30. Applied Economics Letters 15, 1111-1114.

Fama, E. F., 1970. Efficient capital market, a review of theory and empirical work. Journal of Finance 25, 383- 417.

Gunasekarage, A. and D. M. Power, 2001. The profitability of moving average trading rules in South Asian stock markets. Emerging Market Review 2, 17 - 33.

Hudson, R., M. Dempsey and K. Keasey, 1996. A note on the weak form efficiency of capital markets: The application of simple technical trading rules to UK stock prices — 1935 to 1994. Journal of Banking and Finance 20, 1121-1132.

Jensen, M. C. and G. A. Benington, 1970. Random walk and technical theories: some additional evidence. Journal of Finance 25, 469 - 482.

Kwon, K. Y. and R. J. Kish. 2002. Technical trading strategies and return predictability: NYSE. Applied Financial Economics 12, 639-653.

Lui, K. M. and T. T. L. Chong, 2013. Do technical analysts outperform novice traders: Experimental evidence. Economics Bulletin 33(4), 3080-3087.

Mills, T. C., 1997. Technical analysis and the London Stock Exchange: Testing trading rules using the FT30. International Journal of Finance and Economics 2, 319-331.

Murphy, J. J., 1999. Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications, New York Institute of Finance.

Neftçi, S. N., 1991. Naïve trading rules in financial markets and Wiener-Kolmogorov prediction theory: A study of “technical analysis”. Journal of Business 64, 549-571.

Ni, H. and H. Yin. 2009. Exchange rate prediction using hybrid neural networks and trading indicators. Neurocomputing 72, 2815-2823.

Pring, M. J., 2002. Momentum Explained, Volume 1 & 2, McGraw-Hill, New York.

Rosillo, R,; D. de la Fuente and J. A. L. Brugos. 2013. Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies. Applied Economics 45(12), 1541 -1550.Rouwenhorst, K.G., 1998. International momentum strategies. Journal of Finance 53, 267-284.

Stawicki, S. P. 2007. Application of financial analysis techniques to vital sign data: a novel method of trend interpretation in the intensive care unit. OPUS12 Scientist 1, 14-16.

Sullivan, R., A. Timmerman and H. White, 1999. Data-snooping, technical trading rule performance and the Bootstrap, Journal of Finance 54, 1647-1691.

Tanaka-Yamawaki, M. and S. Tokuoka. 2007. Adaptive use of technical indicators for the prediction of intra-day stock prices. Physica A 383, 125-133.

Timmermann, A. and C.W.J. Granger, 2004. Efficient market hypothesis and forecasting. International Journal of Forecasting 20, 15– 27.

Treynor, J. L. and R. Ferguson, 1985. In defense of technical analysis. Journal of Finance 40, 757-773.

Ülkü, N. and E. Prodan, 2013. Drivers of technical trend-following rules' profitability in world stock markets. International Review of Financial Analysis 30 (2013) 214–229.

White, R. 2013. Technical Analysis Indicator That Works Turns Positive For These Stocks, Forbes, April 15, 2013. Available at: http://www.forbes.com/sites/greatspeculations/2013/04/15/technical-analysis-indicator-that-works-turns-positive-for-these-stocks/. Accessed: Dec 27, 2013.

Wilder, J. W. 1978. New Concepts in Technical Trading Systems. USA: Trend Research.