Bayesian Analysis of a Stochastic Volatility Model with Leverage Effect and Fat Tails

2001 ◽  
Author(s):  
Eric Jacquier ◽  
Nick Polson ◽  
Peter E. Rossi
Keyword(s):  
Bayesian Analysis ◽  
Stochastic Volatility ◽  
Stochastic Volatility Model ◽  
Leverage Effect ◽  
Fat Tails ◽  
Volatility Model

scholarly journals Cross-Commodity Spot Price Modeling with Stochastic Volatility and Leverage For Energy Markets

2013 ◽  
Vol 45 (02) ◽  
pp. 545-571 ◽  
Author(s):  
F. E. Benth ◽  
L. Vos
Keyword(s):  
Stochastic Volatility ◽  
Simulation Method ◽  
Energy Markets ◽  
Stochastic Volatility Model ◽  
Spot Price ◽  
Leverage Effect ◽  
Order Structure ◽  
Spot Prices ◽  
Volatility Model ◽  
Multivariate Stochastic Volatility

Spot prices in energy markets exhibit special features, such as price spikes, mean reversion, stochastic volatility, inverse leverage effect, and dependencies between the commodities. In this paper a multivariate stochastic volatility model is introduced which captures these features. The second-order structure and stationarity of the model are analyzed in detail. A simulation method for Monte Carlo generation of price paths is introduced and a numerical example is presented.

scholarly journals MULTIVARIATE ECOGARCH PROCESSES

2010 ◽  
Vol 27 (2) ◽  
pp. 344-371 ◽  
Author(s):  
Stephan Haug ◽  
Robert Stelzer
Keyword(s):  
Stochastic Volatility ◽  
Continuous Time ◽  
Stochastic Volatility Model ◽  
Leverage Effect ◽  
Mixing Properties ◽  
Multivariate Extension ◽  
Volatility Model

A multivariate extension of the exponential continuous time GARCH (p, q) model (ECOGARCH) is introduced and studied. Stationarity and mixing properties of the new stochastic volatility model are investigated, and ways to model a component-wise leverage effect are presented.

Estimation of SV Model with Leverage Effect Based on MCMC Technique

2014 ◽  
Vol 530-531 ◽  
pp. 605-608
Author(s):  
Xiao Cui Yin
Keyword(s):  
Monte Carlo ◽  
Stochastic Volatility ◽  
Stochastic Volatility Model ◽  
Stock Index ◽  
Leverage Effect ◽  
Model Parameters ◽  
Convergence Diagnostics ◽  
Volatility Model ◽  
Mcmc Simulation ◽  
Series Convergence

This paper is to study the estimation of stochastic volatility model with leverage effect using Bayesian approach and Markov Chain Monte Carlo (MCMC) simulation technique. The data used is China's Shenzheng stock index. Estimations of model parameters are achieved by using MCMC technique in Openbugs Software, results show that there is leverage effect in Shenzheng stock series, convergence diagnostics suggest that parameters of the model are convergent.

scholarly journals A CORRELATED STOCHASTIC VOLATILITY MODEL MEASURING LEVERAGE AND OTHER STYLIZED FACTS

2002 ◽  
Vol 05 (05) ◽  
pp. 541-562 ◽  
Author(s):  
JAUME MASOLIVER ◽  
JOSEP PERELLÓ
Keyword(s):  
Stochastic Volatility ◽  
Heavy Tails ◽  
Stochastic Volatility Model ◽  
Market Model ◽  
Leverage Effect ◽  
Stylized Facts ◽  
Uhlenbeck Process ◽  
Volatility Model ◽  
Ornstein Uhlenbeck Process ◽  
Negative Skewness

We analyze a stochastic volatility market model in which volatility is correlated with return and is represented by an Ornstein-Uhlenbeck process. In the framework of this model we exactly calculate the leverage effect and other stylized facts, such as mean reversion, leptokurtosis and negative skewness. We also obtain a close analytical expression for the characteristic function and study the heavy tails of the probability distribution.

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