On the Number of State Variables in Options Pricing

Li, Gang; Zhang, Chu

doi:10.1287/mnsc.1100.1222

Cited by 34 publications

(23 citation statements)

References 44 publications

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“…They also find that the estimated variance factors can be identified as a strongly mean-reverting shortterm variance factor and a slowly mean-reverting long-term factor. In addition, Li and Zhang (2010) use a non-parametric approach to analyze the index option dataset and verify the conclusion in Christoffersen et al (2009). They find that one needs to use at least two factors in order to sufficiently capture the dynamics of implied volatility in both the time-series and cross-sectional dimensions.…”

Section: Introductionmentioning

confidence: 96%

Asymptotic Expansion Formula of Option Price Under Multifactor Heston Model

Nagashima

Chung

Tánaka

2014

Asia-Pac Financ Markets

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The stochastic volatility model of Heston (Rev Financ Stud 6(2): [327][328][329][330][331][332][333][334][335][336][337][338][339][340][341][342][343] 1993) has found difficulty in describing some of the important features of implied volatility dynamics, leading to a quest for multifactor extensions as well as the incorporation of time-dependent model parameters. In this paper, an asymptotic expansion approach to the multifactor Heston model with time-dependent parameters is developed. The results of Benhamou et al. (SIAM J Financ Math 1(1):289-325, 2010) are extended and it is shown that the extension to the multifactor model involves an extra expansion term that captures the interaction between variance factors. The expansion formula under constant parameters can be explicitly computed and the incorporation of time-dependent parameters is straightforward under the framework. As illustration, a two-factor model is calibrated to data of index options and variance swaps and it is found that it is possible to distinguish a short-term and long-term variance factor from the implied volatility surface and variance swap rates. Moreover, the two-factor model is able to reproduce the shapes of the implied volatility surface during various market scenarios.

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Section: Introductionmentioning

confidence: 96%

Asymptotic Expansion Formula of Option Price Under Multifactor Heston Model

Nagashima

Chung

Tánaka

2014

Asia-Pac Financ Markets

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“…For instance, Li and Zhang (2010), using nonlinear principal components analysis, find that two factors are needed to explain the variation in the IV surface. Christoffersen, Jacobs, Ornthanalai, and Wang (2008) employ a modified version of the two-factor component GARCH in Engle and Lee (1999) for options pricing in discrete-time, while Bates (2000) proposes a two-factor jump-diffusion model to fit the implicit distribution in futures options.…”

Section: Introductionmentioning

confidence: 99%

Realizing smiles: Options pricing with realized volatility

Corsi¹,

Fusari²,

Vecchia³

2013

Journal of Financial Economics

112

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Bates, our referee, for helpful comments and suggestions. We are also grateful to Torben Andersen, Giovanni Barone-Adesi, Francesco Permanent repository linkCorielli, Christian Gourieroux, Peter Gruber, Patrick Gagliardini, Loriano Mancini, Nour Meddahi, Alain Monfort, Fulvio Pegoraro, Roberto Renó, Viktor Todorov, and Fabio Trojani for their constructive discussions and remarks. We also thank the participants at the SoFiE conference held in Chicago. All errors are our own responsibility. The authors acknowledge the Swiss National Science Foundation Pro*Doc program, the NCCR FinRisk, and the Swiss Finance Institute for partial financial support. AbstractWe develop a discrete-time stochastic volatility option pricing model exploiting the information contained in the Realized Volatility (RV), which is used as a proxy of the unobservable log-return volatility. We model the RV dynamics by a simple and effective long-memory process, whose parameters can be easily estimated using historical data. Assuming an exponentially affine stochastic discount factor, we obtain a fully analytic change of measure. An empirical analysis of Standard and Poor's 500 index options illustrates that our model outperforms competing time-varying and stochastic volatility option pricing models.

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“…following Li and Zhang (2010) to determine the improvement in performance after adding the second PC.…”

Section: Non-parametric Estimationmentioning

confidence: 99%

How Important is a Non‐Default Factor for CDS Valuation?

Guo

Han

Lee

et al. 2014

Journal of Futures Markets

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Unlike previous research based on structural or reduced-form models, we investigate the importance of a non-default factor for credit default swap (CDS) valuation by conducting nonparametric local linear regression analyses using corporate CDS data from 2002 to 2011. We find that a model with an additional non-default factor significantly outperforms a model with only a default factor, both in-sample and out-of-sample, particularly for low credit rating CDS spreads. This improvement is robust to both credit rating and maturity. Our findings support the idea that non-default risk is priced in CDS spreads and help explain CDS valuation.

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On the Number of State Variables in Options Pricing

Cited by 34 publications

References 44 publications

Asymptotic Expansion Formula of Option Price Under Multifactor Heston Model

Asymptotic Expansion Formula of Option Price Under Multifactor Heston Model

Realizing smiles: Options pricing with realized volatility

How Important is a Non‐Default Factor for CDS Valuation?

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