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Do Mean Reverting based trading strategies outperform Buy and Hold?

Author

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  • Dooruj Rambaccussing

    (University of Exeter)

Abstract

If prices of assets are not aligned to their net present value, a trading strategy may be implemented when actual prices revert to fundamentals. This hypothesis is informally tested in real-time using a trading strategy which consists of identifying whether the equity index is over or under- priced. The fundamental price is constructed in real time using the net present value approach which requires the series for expected dividends, expected returns and expected dividend growth rate. These series, typi- cally unobservable, are derived from a structural state space model and econometric models. The performance of the rules depend on the fre- quency of the data. Cyclical behaviour within the the one year frequency may not be discarded. The trading strategy performs poorly implying that mean reversion may not be uncovered in real-time. However a hybrid variant of the structural and econometric model is shown to outperform the passive Buy and Hold strategy.

Suggested Citation

  • Dooruj Rambaccussing, 2011. "Do Mean Reverting based trading strategies outperform Buy and Hold?," Working Papers 1113, Department of Applied Economics II, Universidad de Valencia.
    • Handle: RePEc:eec:wpaper:1113
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    References listed on IDEAS

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    1. Bulkley, George & Tonks, Ian, 1989. "Are U.K. Stock Prices Excessively Volatile? Trading Rules and Variance Bounds Tests," Economic Journal, Royal Economic Society, vol. 99(398), pages 1083-1098, December.
    2. Ignacio N. Lobato & Peter M. Robinson, 1998. "A Nonparametric Test for I(0)," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(3), pages 475-495.
    3. John Y. Campbell, Robert J. Shiller, 1988. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," The Review of Financial Studies, Society for Financial Studies, vol. 1(3), pages 195-228.
    4. Allan G. Timmermann, 1993. "How Learning in Financial Markets Generates Excess Volatility and Predictability in Stock Prices," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(4), pages 1135-1145.
    5. Bohl, Martin T. & Siklos, Pierre L., 2004. "The present value model of U.S. stock prices redux: a new testing strategy and some evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 44(2), pages 208-223, May.
    6. Martin D. D. Evans, 1998. "Dividend Variability and Stock Market Swings," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(4), pages 711-740.
    7. Conrad, Jennifer & Kaul, Gautam, 1988. "Time-Variation in Expected Returns," The Journal of Business, University of Chicago Press, vol. 61(4), pages 409-425, October.
    8. Chow, Gregory C, 1989. "Rational versus Adaptive Expectations in Present Value Models," The Review of Economics and Statistics, MIT Press, vol. 71(3), pages 376-384, August.
    9. Brandt, Michael W. & Kang, Qiang, 2004. "On the relationship between the conditional mean and volatility of stock returns: A latent VAR approach," Journal of Financial Economics, Elsevier, vol. 72(2), pages 217-257, May.
    10. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
    11. Allan Timmermann, 1996. "Excess Volatility and Predictability of Stock Prices in Autoregressive Dividend Models with Learning," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 63(4), pages 523-557.
    12. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2004. "Fractional cointegration and tests of present value models," Review of Financial Economics, Elsevier, vol. 13(3), pages 245-258.
    13. Rangvid, Jesper, 2006. "Output and expected returns," Journal of Financial Economics, Elsevier, vol. 81(3), pages 595-624, September.
    14. Cuthbertson, Keith & Hyde, Stuart, 2002. "Excess volatility and efficiency in French and German stock markets," Economic Modelling, Elsevier, vol. 19(3), pages 399-418, May.
    15. JULES H. Van BINSBERGEN & RALPH S. J. KOIJEN, 2010. "Predictive Regressions: A Present‐Value Approach," Journal of Finance, American Finance Association, vol. 65(4), pages 1439-1471, August.
    16. Strauss, Jack & Yigit, Taner, 2001. "Present value model, heteroscedasticity and parameter stability tests," Economics Letters, Elsevier, vol. 73(3), pages 375-378, December.
    17. Kanas, Angelos, 2005. "Nonlinearity in the stock price-dividend relation," Journal of International Money and Finance, Elsevier, vol. 24(4), pages 583-606, June.
    18. Michael Cooper & Huseyin Gulen, 2006. "Is Time-Series-Based Predictability Evident in Real Time?," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1263-1292, May.
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    More about this item

    Keywords

    Trading Rule; Asset Pricing; State Space Modeling;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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