Stochastic Volatility Models
Pricing and hedging exotic options in stochastic volatility models
... In the first part of the thesis, we propose an extension of the put-call symmetry theorem (PCS) to cover the case of continuous stochastic volatility models when there is correlation between the ...
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Recursive Estimation for Continuous Time Stochastic Volatility Models Using the Milstein Approximation
... modelling volatility of the observed process by nonlinear stochastic processes ...time stochastic volatility models using the Milstein ...proposed stochastic volatility ...
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Consistent nonparametric specification tests for stochastic volatility models based on the return distribution
... the stochastic volatility is not convergent if the commutative condition is not satisfied, which is the case for most of the stochastic volatility models with leverage ...with ...
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Nonparametric specification tests for stochastic volatility models based on volatility density
... error models, Holzmann et ...of stochastic volatility models would be an interesting yet challenging task, I thus leave this for future ...
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Nonparametric specification tests for stochastic volatility models based on volatility density
... error models, Holzmann et ...of stochastic volatility models would be an interesting yet challenging task, I thus leave this for future ...
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Bayesian Inference of Stochastic Volatility Models and Applications in Risk Management.
... Multivariate stochastic volatility models (MSV) are more often used in risk management. During the recent subprime crisis, bankruptcies and bailouts of several systemically important firms adversely ...
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Ranking and Combining Volatility Proxies for Garch and Stochastic Volatility Models
... and stochastic volatility models are standard tools for the time series analysis of daily ...time models. It addresses the problem of optimizing volatility proxies when intraday high- ...
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The Calibration of Some Stochastic Volatility Models Used in Mathematical Finance
... Stochastic volatility models are used in mathematical finance to describe the dynamics of asset ...these models, the asset price is modeled as a stochastic process depending on time im- ...
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Bayesian Estimation of Non Gaussian Stochastic Volatility Models
... The Stochastic Volatility models have been widely used to model a changing variance of time series Financial data ...These models usually assume Gaussian distribution for asset returns ...
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Frequentist and Bayesian Unit Root Tests in Stochastic Volatility Models
... In addition to the frequentist testing procedures, Bayesian unit root tests can be used to test for a unit root in stochastic volatility models as well. A Bayesian test based on the Bayes factor has ...
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Testing for one factor models versus stochastic volatility models
... If the null hypothesis is not rejected, then one can use the different testing and modeling pro- cedures mentioned above, based on the maintained hypothesis of a one-factor diffusion generating process. Conversely, if ...
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A Simple Control Variate Method for Options Pricing with Stochastic Volatility Models
... under stochastic volatility ...constant volatility model, like Hull and White(1987)[8], John and Shanno(1987)[9], (b) the martingale control variate method proposed by Fouque and Han(2007)[4], (c) ...
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A non iterative (trivial) method for posterior inference in stochastic volatility models
... the stochastic volatility ...in stochastic volatility models with leverage (Omori et al, 2007) and multivariate stochastic volatility models (Harvey et al, 1994 and ...
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Accelerating the calibration of stochastic volatility models
... in models with known characteristic function: (1) Direct integration, (2) Fast Fourier Transform (FFT), (3) Fractional ...of stochastic volatility models, ...Barndorff-Nielsen-Shephard ...
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Estimation of stochastic volatility models via Monte Carlo maximum likelihood
... This paper discusses the Monte Carlo maximum likelihood method of estimating stochastic volatility (SV) models. The basic SV model can be expressed as a linear state space model with log chi-square ...
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Revealing the arcane: an introduction to the art of stochastic volatility models
... There are many different ways to estimate SV models. Below we focus on several methods of approximating the likelihood function. Given an estimate of the likelihood function one can use well-known optimization ...
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Robust Inference with Quantile Regression in Stochastic Volatility Models with application to Value at Risk calculation
... Stochastic Volatility (SV) models play an integral role in modeling time varying volatility, with widespread application in ...parsimonious models in lieu of full conditional ...
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Unit Root Tests in Time Series and Stochastic Volatility Models
... Fuller (1976), and Dickey and Fuller (1979) introduced the Dickey-Fuller t test (DF test) and the augmented DF (ADF) test for testing the unit root hypothesis in the autoregressive moving average (ARMA) representation of ...
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Estimating and testing stochastic volatility models using realized measures
... Again, the provided limit theory holds over a finite time span. As one can immediately see from comparing (27) and (28), robustness to rare and large jumps is achieved at the expense of some loss in efficiency. The ...
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Embedding Stochastic Correlation into the Pricing of FX Quanto Options under Stochastic Volatility Models
... the stochastic processes (namely the initial value and the long term mean level) because of the conditions implied by the Cho- lesky decomposition, see Equation ...
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