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The Role of Implied Volatility in Forecasting Future Realized Volatility and Jumps in Foreign Exchange, Stock, and Bond Markets

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Author Info
Thomas Busch () (Danske Bank and CREATES)
Bent Jesper Christensen () (University of Aarhus and CREATES)
Morten Ørregaard Nielsen () (Queen's University and CREATES)

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Abstract

We study the forecasting of future realized volatility in the foreign exchange, stock, and bond markets from variables in the information set, including implied volatility backed out from option prices. Realized volatility is separated into its continuous and jump components, and the heterogeneous autoregressive (HAR) model is applied with implied volatility as an additional forecasting variable. A vector HAR (VecHAR) model for the resulting simultaneous system is introduced, controlling for possible endogeneity issues. We find that implied volatility contains incremental information about future volatility in all three markets, relative to past continuous and jump components, and it is an unbiased forecast in the foreign exchange and stock markets. Out-of-sample forecasting experiments confirm that implied volatility is important in forecasting future realized volatility components in all three markets. Perhaps surprisingly, the jump component is, to some extent, predictable, and options appear calibrated to incorporate information about future jumps in all three markets.

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Paper provided by Queen's University, Department of Economics in its series Working Papers with number 1181.

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Length: 25 pages
Date of creation: Oct 2008
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Handle: RePEc:qed:wpaper:1181

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Related research
Keywords: Bipower variation; HAR; Heterogeneous Autoregressive Model; implied volatility; jumps; options; realized volatility; VecHAR; volatility forecasting;

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Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions
F31 - International Economics - - International Finance - - - Foreign Exchange
G1 - Financial Economics - - General Financial Markets

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Full references

Cited by:
(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. Gael M. Martin & Andrew Reidy & Jill Wright, 2009. "Does the option market produce superior forecasts of noise-corrected volatility measures?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 77-104. [Downloadable!]
    Other versions:
  2. Bo-Young Chang & Peter Christoffersen & Kris Jacobs & Gregory Vainberg, 2009. "Option-Implied Measures of Equity Risk," CIRANO Working Papers 2009s-33, CIRANO. [Downloadable!]
  3. Fulvio Corsi & Davide Pirino & Roberto Renò, 2008. "Volatility forecasting: the jumps do matter," Department of Economics University of Siena 534, Department of Economics, University of Siena. [Downloadable!]
  4. Peter Christoffersen & Kris Jacobs & Gregory Vainberg, 2007. "Forward-Looking Betas," CREATES Research Papers 2007-39, School of Economics and Management, University of Aarhus. [Downloadable!]
  5. Fulvio Corsi & Davide Pirino & Roberto Reno, 2009. "Volatility Forecasting: The Jumps Do Matter," Global COE Hi-Stat Discussion Paper Series gd08-036, Institute of Economic Research, Hitotsubashi University. [Downloadable!]
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