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Moving Average Timing Strategy from a Volatility Perspective: Evidence of the Taiwan Stock Market

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Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS 2017)

Abstract

We apply the approach of [5] by examining whether the portfolios based on the trend-following strategy delivers abnormal returns. Sorted by volatility in previous year, portfolios are traded by following moving average timing strategy to examine their investment performance within the sample period from 1996–2011 for companies listed in the Taiwan stock market. We find that the moving average timing strategy outperforms the buy-and-hold strategy. The CAPM and the Fama-French three-factor models can explain the abnormal returns of the moving average timing strategy. Furthermore, the performance 10-day moving average timing strategy outperforms other timing strategies based on 20-, 50-, 100- and 200-day moving average across volatility quintiles. That means higher volatility quintile portfolios with 10-day moving average timing strategy tend to have better performance than those portfolios with longer days of moving average timing strategy.

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Notes

  1. 1.

    \(M\!K\!T\) is the difference between daily index return of the Taiwan stock market and risk-free rate which is proxied by 1-year time deposit rate.

References

  1. Brock, W., Lakonishok, J., LeBaron, B.: Simple technical trading rules and the stochastic properties of stock returns. J. Finan. 47(5), 1731–1764 (1992)

    Article  Google Scholar 

  2. Covel, M.: Trend Following: How Great Traders Make Millions in Up or Down Markets. Prentice Hall, New York (2005)

    Google Scholar 

  3. Faber, M.T.: A quantitative approach to tactical asset allocation. J. Wealth Manag. 9(4), 69–79 (2007)

    Article  MathSciNet  Google Scholar 

  4. French, K.R., Schwert, G., Stambaugh, R.F.: Expected stock returns and volatility. J. Finan. Econ. 19(1), 3–29 (1987)

    Article  Google Scholar 

  5. Han, Y., Yang, K., Zhou, G.: A new anomaly: the cross-sectional profitability of technical analysis. J. Finan. Quant. Anal. 48(5), 1433–1461 (2013)

    Article  Google Scholar 

  6. Henriksson, R.D., Merton, R.C.: On market timing and investment performance. II. statistical procedures for evaluating forecasting skills. J. Bus. 54(4), 513–533 (1981)

    Article  Google Scholar 

  7. Hibbert, A.M., Daigler, R.T., Dupoyet, B.: A behavioral explanation for the negative asymmetric return-volatility relation. J. Bank. Finan. 32(10), 2254–2266 (2008)

    Article  Google Scholar 

  8. Li, Q., Yang, J., Hsiao, C., Chang, Y.-J.: The relationship between stock returns and volatility in international stock markets. J. Empirical Finan. 12(5), 650–665 (2005)

    Article  Google Scholar 

  9. Lo, A.W., Mamaysky, H., Wang, J.: Foundations of technical analysis: computational algorithms, statistical inference, and empirical implementation. J. Finan. 55(4), 1705–1765 (2000)

    Article  Google Scholar 

  10. Poon, S.-H., Taylor, S.J.: Stock returns and volatility: an empirical study of the UK stock market. J. Bank. Finan. 16(1), 37–59 (1992). Special Issue on European Capital Markets

    Article  Google Scholar 

  11. Poterba, J.M., Summers, L.H.: The persistence of volatility and stock market fluctuations. Am. Econ. Rev. 76(5), 1142–1151 (1986)

    Google Scholar 

  12. Santis, G.D., Ímrohoŏlu, S.: Stock returns, volatility in emerging financial markets. J. Int. Money Finan. 16(4), 561–579 (1997)

    Article  Google Scholar 

  13. Treynor, J.L., Mazuy, K.K.: Can mutual funds outguess the market? Harvard Bus. Rev. 44, 131–136 (1966)

    Google Scholar 

  14. Yu, H., Nartea, G.V., Gan, C., Yao, L.J.: Predictive ability and profitability of simple technical trading rules: recent evidence from Southeast Asian stock markets. Int. Rev. Econ. Finan. 25, 356–371 (2013)

    Article  Google Scholar 

  15. Zhu, Y., Zhou, G.: Technical analysis: an asset allocation perspective on the use of moving averages. J. Finan. Econ. 92(3), 519–544 (2009)

    Article  Google Scholar 

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Correspondence to Shyh-Weir Tzang .

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Tzang, SW., Tsai, YS., Chang, CP., Yang, YP. (2018). Moving Average Timing Strategy from a Volatility Perspective: Evidence of the Taiwan Stock Market. In: Barolli, L., Enokido, T. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing . IMIS 2017. Advances in Intelligent Systems and Computing, vol 612. Springer, Cham. https://doi.org/10.1007/978-3-319-61542-4_69

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  • DOI: https://doi.org/10.1007/978-3-319-61542-4_69

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