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A Bayesian analysis of time-varying jump risk in S&P 500 returns and options

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  • Carverhill, Andrew
  • Luo, Dan

Abstract

We examine time-varying jump risk for modeling stock price dynamics and cross-sectional option prices. We explore jump-diffusion specifications with two independently evolving processes for stochastic volatility and jump intensity, respectively. We explicitly impose time-series consistency in model estimation using a Markov Chain Monte Carlo (MCMC) method. We find that both the jump size and standard deviation of jump size premia are more prominent under time-varying jump risk. Simultaneous jumps in returns and volatility help reconcile the time series of returns, volatility, and jump intensities. Finally, independent time-varying jump intensities improve the cross-sectional fit of option prices, especially at longer maturities.

Suggested Citation

  • Carverhill, Andrew & Luo, Dan, 2023. "A Bayesian analysis of time-varying jump risk in S&P 500 returns and options," Journal of Financial Markets, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:finmar:v:64:y:2023:i:c:s1386418122000751
    DOI: 10.1016/j.finmar.2022.100786
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    More about this item

    Keywords

    Time-varying jump risk; Markov Chain Monte Carlo; Risk premium; Time-series consistency; Option pricing;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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