Markov Regime Switching of Stochastic Volatility Lévy Model on Approximation Mode

Markov Regime Switching Stochastic Volatility

This is a project on modeling time-varying volatility of S&P 500 weely return for the years 1990 to 2012 using Bayesian methods. First, MCMC on the log-stochastic volatility (SV) model is implemented with simulation results analyzed. Second, I generalize the SV model to encompass regime-switching properties with the markov switching log-stochastic volatility (MSSV) model, under which, high-vola...

Time delay model for the stochastic volatility with regime switching

Bayesian Analysis of a Markov Switching Stochastic Volatility Model

This article analyzes a Markov switching stochastic volatility (MSSV) model to accommodate the shift in the mean of log-volatility. Since it is difficult to estimate the parameters in this model based on the maximum likelihood method, a Bayesian Markov-chain Monte Carlo (MCMC) approach is adopted. A particle filter for the MSSV model, which is used for model comparison and diagnostics, is const...

Pricing Volatility Swaps Under Heston’s Stochastic Volatility Model with Regime Switching

We develop a model for pricing volatility derivatives, such as variance swaps and volatility swaps under a continuous-time Markov-modulated version of the stochastic ∗The Corresponding Author: RBC Financial Group Professor of Finance, Haskayne School of Business, University of Calgary, Calgary, Alberta, Canada, T2N 1N4; Email: [email protected]; Fax: 403-770-8104; Tel: 403-220-5540 †Lecturer...

Regime Switching Stochastic Volatility with Perturbation Based Option Pricing

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 theoretical arguments and empirical observations. However such models lack the ability to take into account long term and fundamental economic factors e.g. credit crunch. Regime switching models with mean r...