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The Impact of Jumps in Volatility and Returns

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  • Eraker, Bjorn
  • Johannes, Michael
  • Polson, Nicholas
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    Abstract

    This paper examines a class of continuous-time models incorporating jumps in returns and volatility, in addition to diffusive stochastic volatility. We develop a likelihood-based estimation strategy and provide estimates of model parameters, spot volatility, jump times and jump sizes using both S&P 500 and Nasdaq 100 index returns. Estimates of jump times, jump sizes and volatility are particularly useful for disentangling the dynamic effects of these factors during periods of market stress, such as those in 1987, 1997 and 1998. Using both formal and informal diagnostics, we find strong evidence for jumps in volatility, even after accounting for jumps in returns. We study the impact of these factors and of estimation risk on option prices.

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    File URL: http://www.econ.duke.edu/Papers/Abstracts02/abstract.02.18.html
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    Bibliographic Info

    Paper provided by Duke University, Department of Economics in its series Working Papers with number 02-18.

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    Date of creation: 2002
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    Publication status: Forthcoming in JOURNAL OF FINANCE
    Handle: RePEc:duk:dukeec:02-18

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    Postal: Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097
    Phone: (919) 660-1800
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    Web page: http://econ.duke.edu/

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    Cited by:
    1. Rubio Irigoyen, Gonzalo & León, Angel & Ferreira García, María Eva & Gago, Mónica, 2003. "An empirical comparison of the performance of alternative option pricing models," DFAEII Working Papers 2002-04, University of the Basque Country - Department of Foundations of Economic Analysis II.
    2. Gerlach, Richard & Tuyl, Frank, 2006. "MCMC methods for comparing stochastic volatility and GARCH models," International Journal of Forecasting, Elsevier, vol. 22(1), pages 91-107.
    3. Xibin Zhang & Maxwell L. King, 2002. "Influence Diagnostics in GARCH Processes," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics 19/02, Monash University, Department of Econometrics and Business Statistics.
    4. Chib, Siddhartha & Nardari, Federico & Shephard, Neil, 2002. "Markov chain Monte Carlo methods for stochastic volatility models," Journal of Econometrics, Elsevier, vol. 108(2), pages 281-316, June.
    5. Christoffersen, Peter & Heston, Steve & Jacobs, Kris, 2006. "Option valuation with conditional skewness," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 253-284.

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