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Some Like it Smooth, and Some Like it Rough: Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset Return Volatility

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Author Info
Torben G. Andersen () (Kellogg School of Management, Northwestern University and NBER)
Tim Bollerslev () (Department of Economics, Duke University and NBER)
Francis X. Diebold () (Department of Economics, University of Pennsylvania and NBER)

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Abstract

A rapidly growing literature has documented important improvements in volatility measurement and forecasting performance through the use of realized volatilities constructed from high frequency returns coupled with relatively simple reduced-form time series modeling procedures. Building on recent theoretical results from Barndorff-Nielsen and Shephard (2003c,d) for related bi-power variation measures involving the sum of high-frequency absolute returns, the present paper provides a practical framework for non-parametrically measuring the jump component in realized volatility measurements. Exploiting these ideas for a decade of high-frequency five-minute returns for the DM/$ exchange rate, the S&P500 market index, and the 30-year U.S. Treasury bond yield, we find the jump component of the price process to be distinctly less persistent than the continuous sample path component. Explicitly including the jump measure as an additional explanatory variable in an easy-to implement reduced form model for realized volatility results in highly significant jump coefficient estimates at the daily, weekly and quarterly forecast horizons.

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Paper provided by Penn Institute for Economic Research, Department of Economics, University of Pennsylvania in its series PIER Working Paper Archive with number 03-025.

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Length: 42 pages
Date of creation: 01 Feb 2003
Date of revision: 01 Sep 2003
Handle: RePEc:pen:papers:03-025

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Keywords: Continuous-time methods jumps quadratic variation realized volatility bi-power variation high-frequency data volatility forecasting HAR-RV model

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C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General
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. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Econometrics of testing for jumps in financial economics using bipower variation," Economics Papers 2003-W21, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
    Other versions:
  2. Benjamin Yibin Zhang & Hao Zhou & Haibin Zhu, 2005. "Explaining credit default swap spreads with the equity volatility and jump risks of individual firms," Finance and Economics Discussion Series 2005-63, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  3. Mende, Alexander, 2005. "09/11 on the USD/EUR Foreign Exchange Market," Diskussionspapiere der Wirtschaftswissenschaftlichen Fakultät der Universität Hannover dp-312, Universität Hannover, Wirtschaftswissenschaftliche Fakultät. [Downloadable!]
    Other versions:
  4. Jeremy Large, 2005. "Estimating quadratic variation when quoted prices jump by a constant increment," Economics Papers 2005-W05, Economics Group, Nuffield College, University of Oxford. [Downloadable!]
    Other versions:
  5. Heather Anderson & Fashid Vahid, 2005. "Forecasting the Volatility of Australian Stock Returns: Do Common Factors Help?," ANUCBE School of Economics Working Papers 2005-451, Australian National University, College of Business and Economics, School of Economics. [Downloadable!]
    Other versions:
  6. Ole E. Barndorff-Nielsen & Sven Erik Graversen & Jean Jacod & Neil Shephard, 2005. "Limit theorems for bipower variation in financial econometrics," OFRC Working Papers Series 2005fe09, Oxford Financial Research Centre. [Downloadable!]
    Other versions:
  7. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," NBER Working Papers 10914, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
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