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Statistical models for financial volatility

Publisher
Elsevier Science
Year
1992
Tongue
English
Weight
304 KB
Volume
52
Category
Article
ISSN
0304-4076

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๐Ÿ“œ SIMILAR VOLUMES

Multifactor implied volatility functions
Multifactor implied volatility functions for HJM models
โœ I-Doun Kuo; Dean A. Paxson ๐Ÿ“‚ Article ๐Ÿ“… 2006 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 489 KB

This study evaluates two one-factor, two two-factor, and two three-factor implied volatility functions in the HJM class, with the use of eurodollar futures options across both strike prices and maturities. The primary contributions of this article are (a) to propose and test three implied volatility

Numerical treatment of stochastic models
Numerical treatment of stochastic models used in statistical systems and financial markets
โœ Ameen Alawneh; Kamel Al-Khaled ๐Ÿ“‚ Article ๐Ÿ“… 2008 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 1021 KB

In this paper, by means of the variational iteration method, numerical solutions are computed for some stochastic models, without any linearization or weak assumptions. Two stochastic models, the Fokker-Planck equation for non-equilibrium statistical systems and the Black-Scholes model for pricing s

Recursive estimation for continuous time
Recursive estimation for continuous time stochastic volatility models
โœ H. Gong; A. Thavaneswaran ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 401 KB

Volatility plays an important role in portfolio management and option pricing. Recently, there has been a growing interest in modeling volatility of the observed process by nonlinear stochastic process [S.J. Taylor, Asset Price Dynamics, Volatility, and Prediction, Princeton University Press, 2005;

Testing for jumps in the stochastic vola
Testing for jumps in the stochastic volatility models
โœ Masahito Kobayashi ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 255 KB

This paper proposes the Lagrange multiplier (LM) test, or the score test, for jumps in the stochastic volatility (SV) model in the cases where the innovation term follows the normal and Student t-distributions. The tested null hypothesis is that the jump density has zero variance, which is expressed