PROFITABILITY OF TECHNICAL ANALYSIS INDICATORS TO EARN ABNORMAL RETURNS IN INTERNATIONAL EXCHANGE MARKETS

Abstract

Technical analysis is one of the most interesting and challenging topics in recent financial science. In addition, its one of the most common methods that investors use, to make investment decisions .This study evaluates the profitability of technical analysis indicators in obtaining abnormal returns using ten technical indicators as trading rules. Therefore, trading signal returns done by these ten rules have been evaluated. In This study, abnormal returns are the difference between indicators returns and average return of risk free interest rate over set period. Sample prices data Include Copper, Palladium, Oil, Gold, Silver, Wheat, Sugar and Dollar Index “between 2008 to 2013”by referring to transaction costs. We next rely on T-TEST to evaluate their Returns, ANOVA to compare Returns and Pearson Correlation experiments to find indicators Correlation. The results revealed the positive returns according to technical analysis indicators. According to the results, STO, RSI, CCI, SMA, MFI, in sequence have more returns and all their returns were more than London Interbank Offered Rate.

References

1. Atkins, A. and E. Dyl (1990) “Price reversals, bid-ask spreads, and market efficiency,” Journal of Financial and Quantitative Analysis, 25, 535–47
2. Audley Delory, Eccles (2003), Stock selection method: Fundamental analysis departure in the United States stock market compared and contrasted a dissertation of Ph.D. in finance. Nova Southeastern University. Economics 78, 187-20
3. Bremer, M.; T. Hiraki; and R.J. Sweeney (1997) “Predictable patterns after large stock price changes on the Tokyo
4. Stock Exchange,” Journal of Financial and Quantitative Analysis, 33, 345-365. Brown, K.; W.V. Harlow; and S.M.Tinic (1993) “The risk and required return of common stock following major price innovations,” Journal of Financial and Quantitative Analysis, 28, 101-106.
5. Bulkowski, Thomas. 2013. Getting Started in Chart Patterns. Wiley.
6. Carmona René, Statistical Analysis of Financial Data, Springer Texts in Statistics, 2013.
7. Cox, D.R., and D.R. Peterson (1994) “Stock returns following large one-day declines: evidence on short-term reversals and long-term performance,” Journal of Finance, 49, 255-267.
8. Fama E. (1969) “Efficient Capital Markets: A Review of Theory and Empirical Works,” Papers and Proceedings of the Twenty-Eighth Annual Meeting of the American Finance Association, 28-30.

9. Ghobadi Mohsen. 2014. “Profitability of Technical Analysis Strategy to Earn Abnormal Returns in Tehran Stock
10. Exchange (2007-2013).” M.A Thesis, Islamic Azad University, Dehaghan Branch, Iran.
11. Ghobadi Mohsen. 2014. “Profitability of Technical Analysis Strategy to Earn Abnormal Returns in TSE(2007- 2013).” Paper presented at The Accounting, Economics and Financial Management Conference, Tehran, Iran, October 26–27.
12. Ghobadi Mohsen. 2014. “Profitability of Technical Analysis Indicators to Earn Abnormal Returns in International
13. Exchange Markets.” Paper presented at International Conference on Economic, Accounting, Management and Social Science, Szczecin, Poland, December 11. Graham , Benjamin (1934), Security Analysis: Sixth Edition, Foreword by Warren Buffett (Security Analysis Prior
14. Editions), McGraw-Hill. Hansen, L.P. (1982) “Large sample properties of the generalized method of moments estimators,” Econometrica, 50, 1029-1054.
15. Lim Mark Andrew, a Handbook of Technical Analysis: The Practitioner's Comprehensive Guide to Technical Analysis, Wiley, 2014.
16. MacKinlay, A.C. and M. Richardson (1991) “Using generalized method of moments to test mean-variance efficiency,” Journal of Finance, 46, 511-27.
17. MacKinlay, A.C. (1997) “Event Studies in Economics and Finance,” Journal of Economic Literature, 35, 13-39.
18. Park, J (1995) “A market microstructure explanation for predictable variations in stock returns following large price changes,” Journal of Financial and Quantitative Analysis, 30, 241-256.
19. Pring Martin J., Technical Analysis Explained, Wiley, 2013.
20. Trabelsi, Elleuch, J. L.,(2009)“Fundamental Analysis Strategy and the Prediction of Stock Returns”, International
21. Research Journal of Finance and Economics, ISSN,1450-2887,Issue30.
22. Tonks Hon M T,.I, Momentum in the UK stock market , Journal of Multinational Financial Management, Title (or Abbreviated Title) of Journal, 13 (1), PP. 43–70. 2003.
23. Viskanta Tadas , Abnormal Returns: Winning Strategies from the Frontlines of the Investment Blogosphere, the McGraw-Hill companies, 2012.