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Volatility forecasts, trading volume, and the ARCH versus option-implied volatility trade-off

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Glen Donaldson
Mark Kamstra

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Abstract

Market expectations of future return volatility play a crucial role in finance; so too does our understanding of the process by which information is incorporated in security prices through the trading process. The authors seek to learn something about both of these issues by investigating empirically the role of trading volume in predicting the relative informativeness of volatility forecasts produced by ARCH models versus the volatility forecasts derived from option prices and in improving volatility forecasts produced by ARCH and option models and combinations of models. Daily and monthly data are explored. The authors find that if trading volume was low during period $t – 1$ relative to the recent past, then ARCH is at least as important as options for forecasting future stock market volatility. Conversely, if volume was high during period $t – 1$ relative to the recent past, then option-implied volatility is much more important than ARCH for forecasting future volatility. Considering relative trading volume as a proxy for changes in the set of information available to investors, their findings reveal an important switching role for trading volume between a volatility forecast that reflects relatively stale information (the historical ARCH estimate) and the option-implied forward-looking estimate.

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Paper provided by Federal Reserve Bank of Atlanta in its series Working Paper with number 2004-6.

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Date of creation: 2004
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Handle: RePEc:fip:fedawp:2004-6

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  5. Christensen, B. J. & Prabhala, N. R., 1998. "The relation between implied and realized volatility1," Journal of Financial Economics, Elsevier, vol. 50(2), pages 125-150, November. [Downloadable!] (restricted)
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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Kim, Joocheol & Kim, WooWhan & Kim, KiHyung, 2006. "Implied Volatility using Variance Decomposition Method," MPRA Paper 936, University Library of Munich, Germany. [Downloadable!]
  2. Marwan Izzeldin & Ana-Maria Fuertes & Elena Kalotychou, 2008. "On forecasting daily stock volatility: the role of intraday information and market conditions," Working Papers 005439, Lancaster University Management School, Economics Department. [Downloadable!]
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