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The Information Content of Treasury Bond Options Concerning Future Volatility and Price Jumps

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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 relation between realized and implied volatility in the bond market. Realized volatility is constructed from high-frequency (5-minute) returns on 30 year Treasury bond futures. Implied volatility is backed out from prices of associated bond options. Recent nonparametric statistical techniques are used to separate realized volatility into its continuous sample path and jump components, thus enhancing forecasting performance. We generalize the heterogeneous autoregressive (HAR) model to include implied volatility as an additional regressor, and to the separate forecasting of the realized components. We also introduce a new vector HAR (VecHAR) model for the resulting simultaneous system, controlling for possible endogeneity of implied volatility in the forecasting equations. We show that implied volatility is a biased and inefficient forecast in the bond market. However, implied volatility does contain incremental information about future volatility relative to both components of realized volatility, and even subsumes the information content of daily and weekly return based measures. Perhaps surprisingly, the jump component of realized bond return volatility is, to some extent, predictable, and bond options appear to be calibrated to incorporate information about future jumps in Treasury bond prices, and hence interest rates.

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File URL: http://www.econ.queensu.ca/working_papers/papers/qed_wp_1188.pdf
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Publisher Info
Paper provided by Queen's University, Department of Economics in its series Working Papers with number 1188.

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Length: 37 pages
Date of creation: Feb 2006
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Handle: RePEc:qed:wpaper:1188

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Related research
Keywords: Bipower variation; bond futures options; HAR; Heterogeneous Autoregressive Model; implied volatility; jumps; 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
G1 - Financial Economics - - General Financial Markets

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