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Unravelling the Asymmetric Volatility Puzzle: A Novel Explanation of Volatility Through Anchoring

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  • Mihaly Ormos
  • Dusan Timotity

Abstract

This paper discusses a novel explanation for asymmetric volatility based on the anchoring behavioral pattern. Anchoring as a heuristic bias causes investors focusing on recent price changes and price levels, which two lead to a belief in continuing trend and mean-reversion respectively. The empirical results support our theoretical explanation through an analysis of large price fluctuations in the S&P 500 and the resulting effects on implied and realized volatility. These results indicate that asymmetry (a negative relationship) between shocks and volatility in the subsequent period indeed exists. Moreover, contrary to previous research, our empirical tests also suggest that implied volatility is not simply an upward biased predictor of future deviation compensating for the variance of the volatility but rather, due to investors systematic anchoring to losses and gains in their volatility forecasts, it is a co-integrated yet asymmetric over/under estimated financial instrument. We also provide results indicating that the medium-term implied volatility (measured by the VIX Index) is an unbiased though inefficient estimation of realized volatility, while in contrast, the short-term volatility (measured by the recently introduced VXST Index representing the 9-day implied volatility) is also unbiased and yet efficient.

Suggested Citation

  • Mihaly Ormos & Dusan Timotity, 2016. "Unravelling the Asymmetric Volatility Puzzle: A Novel Explanation of Volatility Through Anchoring," Papers 1606.03597, arXiv.org.
  • Handle: RePEc:arx:papers:1606.03597
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Ormos, Mihály & Timotity, Dusán, 2016. "Market microstructure during financial crisis: Dynamics of informed and heuristic-driven trading," Finance Research Letters, Elsevier, vol. 19(C), pages 60-66.
    2. repec:eee:quaeco:v:71:y:2019:i:c:p:79-94 is not listed on IDEAS
    3. Ormos Mihály & Timotity Dusán, 2017. "The Case of “Less is More”: Modelling Risk-Preference with Expected Downside Risk," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 17(2), pages 1-14, June.

    More about this item

    JEL classification:

    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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