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Trading styles and long-run variance of asset prices

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  • Lawrence Middleton
  • James Dodd
  • Simone Rijavec

Abstract

Trading styles can be classified into either trend-following or mean-reverting. If the net trading style is trend-following the traded asset is more likely to move in the same direction it moved previously (the opposite is true if the net style is mean-reverting). The result of this is to introduce positive (or negative) correlations into the time series. We here explore the effect of these correlations on the long-run variance of the series through probabilistic models designed to explicitly capture the direction of trading. Our theoretical insights suggests that relative to random walk models of asset prices the long-run variance is increased under trend-following strategies and can actually be reduced under mean-reversal conditions. We apply these models to some of the largest US stocks by market capitalisation as well as high-frequency EUR/USD data and show that in both these settings, the ability to predict the asset price is generally increased relative to a random walk.

Suggested Citation

  • Lawrence Middleton & James Dodd & Simone Rijavec, 2021. "Trading styles and long-run variance of asset prices," Papers 2109.08242, arXiv.org.
  • Handle: RePEc:arx:papers:2109.08242
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    References listed on IDEAS

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    1. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    2. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    3. repec:pri:cepsud:91malkiel is not listed on IDEAS
    4. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    5. Narasimhan Jegadeesh & Sheridan Titman, 2001. "Profitability of Momentum Strategies: An Evaluation of Alternative Explanations," Journal of Finance, American Finance Association, vol. 56(2), pages 699-720, April.
    6. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    7. Chan, Louis K C & Jegadeesh, Narasimhan & Lakonishok, Josef, 1996. "Momentum Strategies," Journal of Finance, American Finance Association, vol. 51(5), pages 1681-1713, December.
    8. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
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