De winstgevendheid van een market timing strategie via technische analyse. Een onderzoek in ontwikkelde en opkomende markten

Joell De Smet
Persbericht

Technische analyse, een voorbijgestreefde investeringsstrategie

Investeerders trachten vaak de markt te timen om hogere rendementen te behalen dan de passieve buy-and-hold portefeuille. Onderzoek aan de KU Leuven toont aan dat een investeerder beter af is met de buy-and-hold strategie.

Veel investeerders hanteren een actieve marktstrategie waarin ze over- en onderwaardering van aandelen en indices trachten te onderscheiden om zo een mooi rendement te behalen. Eén van deze strategieën is technische analyse. Bij deze analysemethode kijkt men naar historische beurskoersen om een voorspelling te maken van toekomstige bewegingen van de aandelenmarkten. Het gebruik van technische analyse, waarbij allerlei verbanden tussen beurskoersen worden gezocht, is dan ook bijzonder populair in de praktijk. Dit onderzoek bekijkt technische analyse op gekende groeimarkten zoals Brazilië, China en India alsook Europese en Amerikaanse indices tussen 2002 en 2016.

De resultaten van dit onderzoek tonen aan dat er in de volledige onderzoeksperiode uitsluitend op groeimarkten hogere rendementen te behalen waren in vergelijking met de buy-and-hold portefeuille. Vooral de Shanghai en Shenzhen indices presteren sterk. Op Europese en Amerikaanse markten kan de buy-and-hold portefeuille niet worden geklopt. Voor een investeerder is het echter belangrijker om te weten of deze investeringsstrategie ook in de toekomst hogere rendementen zal opleveren. Uit de resultaten blijkt dat er de afgelopen vijf jaar enkel op de Shanghai index hogere rendementen te behalen waren via technische analyse. Na berekening van de transactiekosten blijkt ook de Shanghai index geen hogere rendementen te behalen. Dit is mogelijk te wijten aan de efficiëntie van de markten als gevolg van krachtigere algoritmes en hogere verhandelingsvolumes in financiële markten. Dit onderzoek stelt vast dat technische analyse niet gebruikt kan worden om de aandelenmarkten te voorspellen. De buy-and-hold portefeuille geeft de hoogste rendementsvergoeding voor het gelopen risico. Een potentiële investeerder kan dus het beste in deze buy-and-hold portefeuille beleggen.

Bibliografie

Allen, F., & Karjalainen, R. (1999). Using genetic algorithms to find technical trading rules. Journal of Financial economics, 51, 245-271.

Allen, H., & Taylor, M. P. (1992). The use of technical analysis in the foreign exchange market. Journal of International Money and Finance, 11, 304-314.

Annaert, J., De Ceuster, M., & Verstegen, K. (2013). Are extreme returns priced in the stock market? European evidence. Journal of Banking and Finance, 37, 3401-3411.

Bajgrowicz, P., & Scaillet, O. (2012). Technical trading revisited: False discoveries, persistence tests and transaction costs. Journal of Financial Economics, 106, 473-491.

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

Bessembinder, H., & Chan, K. (1998). Market efficiency and the returns to technical analysis. Financial Management Association International, 27(2), 5-17.

Black, F. (1986). Noise. Journal of Finance, 61(3), 529-543.

Bodie, Z., Kane, A., & Marcus, A. J. (2014). Investments. Berkshire: McGraw-Hill Education.

Brock, W., Lakonishok, J., & Le Baron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. Journal of Finance.

Chaudhuri, K., & Wu, Y. (2003). Random walk versus breaking trend in stock prices: Evidence from emerging markets. Journal of Banking and Finance, 27, 575-592.

Chen, C.-W., Huang, C.-S., & Lai, H.-W. (2009). The impact of data-snooping on the testing of technical analysis: an empirical study of Asian stock markets. Journal of Asian Economics, 20, 580-591.

Dooley, M. P., & Shafer, J. R. (1983). Analysis of short-run exchange rate behavior. In Exchange Rate and Trade Instability, 43-69.

European University Institute. (2016, oktober 13). Datastream (Thomson Reuters). Opgeroepen op november 19, 2016, van European University Institute: http://www.eui.eu/Research/Library/ResearchGuides/Economics/Statistics/…

Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance. Opgeroepen op november 3, 2016

Fama, E. F., & Blume, M. E. (1966). Filter rules and stock-market trading. Journal of Business, 39(1), 226-241.

Glass, G.V. & Hopkins, K.D. (1996). Statistical methods in education and psychology. Pearson.

Hsu, P.-H., & Kuan, C.-M. (2005). Re-examining the profitability of technical analysis with data snooping checks. Journal of Financial Econometrics, 3(4), 606-628.

Hsu, P.-H., Hsu, Y.-C., & Kuan, C.-M. (2010). Testing the predictive ability of technical analysis using a new stepwise test without data snooping bias. Journal of Empirical Finance, 17(3), 471-484.

Imrohoroglu, S., & Santis, G. (1997). Stock returns and volatility in emerging financial markets. Journal of International Money and Finance, 16(4), 561-579.

Ince, O.S., & Porter, R.B. (2006). Individual equity return data from Thomson Datastream : handle with care ! Journal of Financial Research, 29(4), 463-479.

James, F. (1968). Monthly Moving-Averages: An effective investment tool? Journal of Financial & Quantitative Analysis, 3(3), 315-326.

Jensen, M. C., & Benington, G. A. (1970). Random walks and technical theories: Some additional evidence. Journal of Finance, 25(2), 469-482.

Jones, C. M. (2002). A century of stock market liquidity and trading costs. Colombia: Graduate school of business.

Kirkpatrick, C. D., & Dahlquist, J. (2011). Technical Analysis: The complete resource for financial markets technicians. Pearson. Opgeroepen op november 3, 2016

Kuang, P., Schröder, M., & Wang, Q. (2014). Illusory profitability of technical analysis in emerging foreign exchange markets. International Journal of Forecasting, 30, 192-205.

Kwon, K.-Y., & Kish, R. J. (2002). A comparative study of technical trading strategies and return predictability: an extension of Brock, Lakonishok and Lebaron (1992) using NYSE and NASDAQ indices. The Quarterly Review of Economics and Finance, 42, 611-631.

Lento, C. (2008). A combined signal approach to technical analysis on the S&P 500. Ontario, Canada: Faculty of Business Administration.

Lento, C. (2009). Combined signal approach: Evidence from the Asian-Pacific equity markets. Applied Economics Letters, 16, 749-753.

Lento, C., & Gradojevic, N. (2007). The profitability of technical trading rules: A combined signal approach. Journal of Applied business Research, 23, 13-28.

Levich, R. M., & Thomas, L. R. (1993). The significance of technical trading-rule profits in the foreign exchange market: a bootstrap approach. Journal of International Money and Finance, 12, 451-474.

Liu, W., & Zheng, W. A. (2011). Stochastic volatility model and technical analysis of stock price. Acta Mathematica Sinica, 27(7), 1283-1296.

Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market efficiency from an evolutionary perspective. Journal of Portfolio Management, 30, 15-29.

Lukac, L. P., & Brorsen, W. B. (1990). A comprehensive test of futures market disequilibrium. Financial Review, 25(4), 593-622.

Makar, C., Smith, A. & Verstegen, K. (2010). Return predictibility and market timing of the American and French stock and bond markets.

Malkiel, B. (1981). A Random Walk down Wall Street. Norton: New York.

Malkiel, B. (2003). The efficient market hypothesis and its critics. Journal of Economic Perspectives, 17, 59–82.

 

Marquering, W., Nisser, J., & Valla, T. (2006). Dissappearing anomalies: a dynamic analysis of the persistence of anomalies. Applied Financial Economics, 16, 291-302.

Marshall, B., Cahan, R., & Cahan, J. (2008). Does intraday technical analysis in the U.S. have Value. Journal of Empirical Finance, 15, 199-210.

Menkhoff, L. (1997). Examining the use of technical currency analysis. Journal of Financial Economics, 307-318.

Mitra & Subrata, K. (2011). How rewarding is technical analysis in the Indian stock market. Quantitative Finance, 11(2), 287-297.

Morosan, A. T. (2011). The relative strength index revisited. African Journal of Business Management, 14(5), 5855-5862.

Musunuru, N., & Patton, J. (2012). Examining random walk hypothesis on major world financial indices. Indian Journal of Economic and Business, 11(2), 587-602.

Neely, C. J. (1997). Technical analysis in the foreign market: A layman's guide. St. Louis: Federal Reserve Bank.

Neely, C. J., Weller, P. A., & Ulrich, J. M. (2009). The adaptive markets hypothesis: Evidence from the foreign exchange market. Journal of Financial and Quantitative Analysis, 44, 467-488.

Olson, D. (2004). Have trading rule profits in the currency markets declined over time? Journal of Banking and Finance, 28, 85-105.

Park, C.-H., & Irwin, S. H. (2007). What do we know about the profitability of technical analysis. Journal of Economic Surveys, 21(4), 786-826.

Pring, M. (2002). Technical analysis explained. Berkshire: McGraw-Hill Education.

Ratner, M., & Leal, R.P.C. (1999). Tests of technical trading strategies in the emerging equity markets of Latin America and Asia. Journal of Banking and Finance, 23(12), 1887-1905.

Schwert, W. G. (2002). Anomalies and market efficiency. National Bureau of Economic Research, 3-54.

Shen, P. (2003). Market timing strategies that worked. Journal of Portfolio management, 29(2),  57-68.

Shiller, R. J. (2003). From efficient markets theory to behavioral finance. Journal of economic perspectives, 17(1), 83-104.

Shynkevich, A. (2012). Performance of technical analysis in growth and small cap segments of the U.S. equity market. Journal of Banking and Finance, 36, 193-208.

Simon, H. A. (1955). A behavioral model of rational choice. Quarterly Journal of Economics, 69(1), 99-118.

Sullivan, R., Timmermann, A., & White, H. (1999). Data-snooping, Technical trading rule performance, and the bootstrap. Journal of Finance, 54(5), 1647-1691.

Sweeney, R. J. (1986). Beating the foreign exchange market. Journal of Finance, 41(1), 163-182.

Terence, C. (1997). Technical analysis and the London Stock Exchange: Testing trading Rules using the FT30. International Journal of Finance Economy, 2, 319-331.

Tian, G. G., Wan, G. H., & Guo, M. (2002). Market efficiency and the returns to simple technical trading rules: Newe evidence from U.S. equity market and chinese equity markets. Asia-Pacific Financial Markets, 9, 241-258.

Timmermann, A., & Granger, C. W. (2004). Efficient market hypothesis and forecasting. Internationaling Journal of Forecasting, 20, 15-27.

Treynor, J.L., & Mazuy, F. (1966). Can mutual funds outguess the market? Harvard Business Review, 45, 131-136.

Wang, F., Yu, P. L., & Cheung, D. W. (2014). Combining technical trading rules using particle swarm optimization. Expert systems with applications, 41, 3016-3026.

Wong, W.-K., Manzur, M., & Chew, B.-K. (2003). How rewarding is technical analysis? Evidence from Singapore stock market. Applied Financial Economics, 13, 543-551.

Yu, H., Nartea, G., Gan, C., & Yao, L. J. (2013). Predictive ability and profitability of simple technical trading rules: Recent evidence from Southeast Asian stock markets. International Review of Economics and Finance, 25, 356-371.

Zhu, H., Jiang, Z.-Q., Li, S.-P., & Zhou, W.-X. (2015). Profitability of simple technical trading rules of Chinese stock exchange indexes. Physica A, 439, 75-84.

Universiteit of Hogeschool
Master in de Handelswetenschappen (Financieel Management)
Publicatiejaar
2017
Promotor(en)
Kurt Verstegen
Kernwoorden
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