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A Class of Nonlinear Stochastic Volatility Models and Its Implications on Pricing Currency Options

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Author Info
Jun Yu
Zhenlin Yang
Xibin Zhang ()

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Abstract

This paper proposes a class of stochastic volatility (SV) models which offers an alternative to the one introduced in Andersen (1994). The class encompasses all standard SV models that have appeared in the literature, including the well known lognormal model, and allows us to empirically test all standard specifications in a convenient way. We develop a likelihood-based technique for analyzing the class. Daily dollar/pound exchange rate data reject all the standard models and suggest evidence of nonlinear SV. An efficient algorithm is proposed to study the implications of this nonlinear SV on pricing currency options and it is found that the lognormal model overprices options.

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Paper provided by Monash University, Department of Econometrics and Business Statistics in its series Monash Econometrics and Business Statistics Working Papers with number 17/02.

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Length: 42 pages
Date of creation: Nov 2002
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Handle: RePEc:msh:ebswps:2002-17

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Related research
Keywords: Box-Cox transformations; Stochastic volatility; MCMC; Exchange rate volatility; Option pricing.;

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Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Carmen Broto & Esther Ruiz, 2002. "Estimation Methods For Stochastic Volatility Models: A Survey," Statistics and Econometrics Working Papers ws025414, Universidad Carlos III, Departamento de Estadística y Econometría. [Downloadable!]
    Other versions:
  2. Xibin Zhang & Maxwell L. King, 2004. "Box-Cox Stochastic Volatility Models with Heavy-Tails and Correlated Errors," Monash Econometrics and Business Statistics Working Papers 26/04, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
    Other versions:
  3. Xibin Zhang & Maxwell L. King, 2003. "Estimation of Asymmetric Box-Cox Stochastic Volatility Models Using MCMC Simulation," Monash Econometrics and Business Statistics Working Papers 10/03, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
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