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Second Order Multiscale Stochastic Volatility Asymptotics: Stochastic Terminal Layer Analysis & Calibration
Second Order Multiscale Stochastic Volatility Asymptotics Stochastic Terminal Layer Analysis Calibration
2012/9/14
Multiscale stochastic volatility models have been developed as an efficient way to capture the principle effects on derivative pricing and portfolio optimization ofrandomly varying volatility. The rec...
The Exact Smile of some Local Stochastic Volatility Models
CEV local volatility stochastic volatility implied volatility.
2012/9/14
We introduce a class of local stochastic volatility models.Within our framework, we obtain an expression for both (i) the price of any European option and (ii) the induced implied volatility smile. To...
Pricing joint claims on an asset and its realized variance under stochastic volatility models
Volatility derivatives stochastic volatility models partial differential equations parabolic equations target volatility option.
2012/9/14
In a stochastic volatility framework, we find a general pricing equation for the class of payoffs depending on the terminal value of a market asset and its final quadratic variation. This allows a pri...
Stochastic Volatility with Heterogeneous Time Scales
Stochastic Volatility Long Memory Generalized Methods of Moments Econo-physics
2012/9/13
Agents' heterogeneity has been recognized as a driver mechanism for the persistence of nancial volatility. We focus on the multiplicity of investment strategies' horizons;we embed this concept in a c...
Approximating stochastic volatility by recombinant trees
American options stochastic volatility Heston model correlated random walk
2012/6/5
A general method to construct recombinant tree approximations for stochastic volatility models is developed and applied to the Heston model for stock price dynamics. In this application, the resulting...
Maximum likelihood approach for several stochastic volatility models
Maximum likelihood approach several stochastic volatility models Computational Finance
2012/4/28
Volatility measures the amplitude of price fluctuations. Despite it is one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method...
Bayesian Inference of Stochastic Volatility Model by Hybrid Monte Carlo
Hybrid Monte Carlo Algorithm Stochastic Volatility Model
2010/10/18
The hybrid Monte Carlo (HMC) algorithm is applied for the Bayesian inference of the stochastic volatility (SV) model. We use the HMC algorithm for the Markov chain Monte Carlo updates of volatility va...
First-passage and risk evaluation under stochastic volatility
First-passage risk evaluation
2010/10/29
We solve the first-passage problem for the Heston random diffusion model. We obtain exact
analytical expressions for the survival and hitting probabilities to a given level of return. We study severa...
Regime Switching Stochastic Volatility with Perturbation Based Option Pricing
Stochastic volatility option pricing perturbation theory
2010/10/29
Volatility modelling has become a significant area of research within Financial Mathematics. Wiener process driven stochastic volatility models have become popular due their consistency with theoretic...
Maximum likelihood estimation of stochastic volatility models
Closed-form likelihood expansions Volatility proxies Heston model GARCH model CEV model
2014/3/13
We develop and implement a method for maximum likelihood estimation in closed-form of stochastic volatility models. Using Monte Carlo simulations, we compare a full likelihood procedure,where an optio...