Equity index variance: Evidence from flexible parametric jump–diffusion models
Paulo Rodrigues and
Norman J. Seeger
Journal of Banking & Finance, 2017, vol. 83, issue C, 85-103
This paper analyzes a wide range of flexible drift and diffusion specifications of stochastic-volatility jump–diffusion models for daily S&P 500 index returns. We find that model performance is driven almost exclusively by the specification of the diffusion component whereas the drift specifications is of second-order importance. Further, the variance dynamics of non-affine models resemble popular non-parametric high-frequency estimates of variance, and their outperformance is mainly accumulated during turbulent market regimes. Finally, we show that jump diffusion models yield more reliable estimates for the expected return of variance swap contracts.
Keywords: Stochastic volatility; Jump–diffusion models; Bayesian inference; Markov chain Monte Carlo; Particle filter; Deviance information criteria; Realized variance; High-frequency returns; Variance risk premium (search for similar items in EconPapers)
JEL-codes: C11 G11 G12 G17 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (1) Track citations by RSS feed
Downloads: (external link)
Full text for ScienceDirect subscribers only
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:83:y:2017:i:c:p:85-103
Access Statistics for this article
Journal of Banking & Finance is currently edited by Ike Mathur
More articles in Journal of Banking & Finance from Elsevier
Bibliographic data for series maintained by Dana Niculescu ().