Stochastic volatility Markov-functional models: calibra-
Markov functional and stochastic volatility modelling
... benchmark models we considered in this chapter are the SABR model and the DD-SABR ...implied volatility curves provided that maturity is not too ...both models to achieve similar ...
206
The stochastic volatility Markov functional model
... implied volatility has no effect on the auto-correlations of the driver and therefore the swap rates at their setting dates, which is inconsistent with what we observed in the ...non-stochastic ...
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Particle Filters for Markov Switching Stochastic Volatility Models
... of volatility per- sistence, include Chou (1988), French, Schwert and Stambaugh (1987), Poon and Taylor (1992) and So, Lam and Li ...the volatility may shifts ...in volatility, while Kalimipalli and ...
21
Multifractional Stochastic volatility models
... Keywords: Hull & White model, functional quantization, vector quantization, Karhunen-Loève, Gaussian process, fractional Brownian motion, multifractional Brownian motion, white noise[r] ...
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Bayesian Analysis of a Markov Switching Stochastic Volatility Model
... 6. Conclusions This article estimates the SV and MSSV models using a Bayesian MCMC method. Our estimation result confirms the finding by previous researchers that the estimate of the persistence parameter drops and ...
15
Alternative Asymmetric Stochastic Volatility Models
... Bayesian Markov Chain Monte Carlo (MCMC) technique proposed by Jacquier, Polson and Rossi (1994) (see, among others, Chib, Nardari and Shephard (2002) and Shephard and Pitt ...
26
On Gegenbauer long memory stochastic volatility models: A Bayesian Markov chain Monte Carlo approach with applications
... SV models include the Threshold Stochastic Volatility Model (So, Lam, and Li, 2002), SV models with fat-tails and correlated errors (Jacquier, Polson, and Rossi, 2004), SV models with ...
238
Estimation of stochastic volatility models by nonparametric filtering
... the volatility process to be a Markov di¤usion (as imposed in ...and volatility processes, t and 2 t , satisfy certain moment conditions, and that the volatility process is su¢ ciently ...
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Maximum Likelihood Approach for Stochastic Volatility Models
... finance, volatility is a hidden quantity because it is not directly ...that volatility is a time-dependent diffusions coefficient of the random walk of the price return and that it is a Markov ...
8
Stylized Facts and Discrete Stochastic Volatility Models
... The stochastic volatility models were estimated in this paper using a Bayesian ...the models estimated here involve high-dimensional probability distributions, the integration can be done only ...
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Maximum Likelihood Estimation of Stochastic Volatility Models
... of stochastic volatility models of asset ...a Markov process, usually a geometric Brownian ...relative volatility of the equity price is then ...implied volatility of options ...
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Bayesian techniques for discrete stochastic volatility models
... SV models were estimated using Markov chain Monte Carlo ...realized volatility cal- ...SV models aug- mented with lagged trading volume and evaluation of their forecasting power by comparison ...
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Bayesian Testing for Asset Volatility Persistence on Multivariate Stochastic Volatility Models
... Asset Volatility Persistency; Bayes Factor; Decision Theory; Markov Chain Monte Carlo; Unit Root Testing; Multivariate Stochastic Volatility Models ...the volatility of asset ...
7
An introduction to stochastic volatility models
... incorporate stochastic volatility, particularly in the setting of Heston’s stochastic volatility ...model. Stochastic volatility models are one of the many extensions of ...
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Accelerating the calibration of stochastic volatility models
... Our second numerical experiment compares the speed of the calibration directly. We have selected 100 random business days from January, 2000 to November, 2006. For each of these days we have used historical market data ...
20
Asymptotics for rough stochastic volatility models
... Gatheral et al.[25] provide strong empirical justification for such models; in particular they argue that log-volatility in practice behaves essentially as fBM with Hurst exponent H ≈ 0.1, at any reasonable ...
29
Accelerating the calibration of stochastic volatility models
... these models the grid for the fractional FFT method must be at least seven times finer than the grid for the direct integration method to obtain the same accuracy in both ...
20
Valuation equations for stochastic volatility models
... Our main result is a necessary and sufficient condition on the uniqueness of classical solutions to the valuation equation: the value function is the unique nonnegative classical solution [r] ...
25
Testing for volatility co-movement in bivariate stochastic volatility models
... when volatility is large, the null hypothesis of volatility co- movement was rejected in every case in Table ...same volatility factor during the low volatility period; the accepted rate of ...
31
Ranking and Combining Volatility Proxies for Garch and Stochastic Volatility Models
... Daily volatility proxies based on intraday data, such as the high-low range and the realized volatility, are important to the specification of discrete time volatility models, and to the ...
31