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Cited by 312

The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.

Volatility Dynamics for the S&P500: Evidence from Realized Volatility, Daily Returns, and Option Prices

Open access
Christoffersen, Peter, Jacobs, Kris, Mimouni, Karim·2010·Review of Financial Studies

Abstract

Most recent empirical option valuation studies build on the affine square root (SQR) stochastic volatility model. The SQR model is a convenient choice, because it yields closed-form solutions for option prices. We investigate alternatives to the SQR model, by comparing its empirical performance with that of five different but equally parsimonious stochastic volatility models. We provide empirical evidence from three different sources: realized volatilities, S&P500 returns, and an extensive panel of option data. The three sources of data all point to the same conclusion: the best volatility specification is one with linear rather than square root diffusion for variance. This model captures the stylized facts in realized volatilities, it performs well in fitting various samples of index returns, andit has the lowest option implied volatility mean squared error in and out of sample.

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Crossref · 10.1093/rfs/hhq032

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Metadata

Authors
Christoffersen, P., Jacobs, K., & Mimouni, K.
Venue
Review of Financial Studies
Published
2010-04-29
Volume
23
Issue
8
Pages
3141-3189
ISSN
  • 0893-9454 (ISSN-L)
  • 1465-7368
OpenAlex
W3122832813
Cited by
312
References
43
FWCI
33.74
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Volatility Dynamics for the S&P500: Evidence from Realized Volatility, Daily Returns, and Option Prices. https://app.cochat.ai/papers/10.1093/rfs/hhq032
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Christoffersen, P., Jacobs, K., & Mimouni, K. (2010). Volatility Dynamics for the S&P500: Evidence from Realized Volatility, Daily Returns, and Option Prices. Review of Financial Studies. https://doi.org/10.1093/rfs/hhq032

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.