Modeling volatility dynamics using non-Gaussian stochastic volatility model based on band matrix routine

DOI10.1016/j.chaos.2018.07.010zbMath1415.91228OpenAlexW2883497411WikidataQ129557112 ScholiaQ129557112MaRDI QIDQ2000331

Xi-Hua Liu, Xin-Tian Zhuang, Xiong Xiong, Xiao-Li Gong

Publication date: 28 June 2019

Published in: Chaos, Solitons and Fractals (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.chaos.2018.07.010

zbMATH Keywords

stochastic volatilitycross-entropydeviance information criterionadaptive importance samplingband matrixnon-Gaussian distribution

Mathematics Subject Classification ID

Economic time series analysis (91B84)

Related Items

Bayesian estimation for stochastic volatility model with jumps, leverage effect and generalized hyperbolic skew Student's t-distribution ⋮ Non-Gaussian VARMA model with stochastic volatility and applications in stock market bubbles

Cites Work

• On leverage in a stochastic volatility model
• Analysis of high dimensional multivariate stochastic volatility models
• Stochastic volatility with leverage: fast and efficient likelihood inference
• Simulation smoothing for state-space models: a computational efficiency analysis
• The transform likelihood ratio method for rare event simulation with heavy tails
• Econometric analysis of jump-driven stochastic volatility models
• Volatility forecast comparison using imperfect volatility proxies
• Estimating the degree of activity of jumps in high frequency data
• Optimization of computer simulation models with rare events
• Fast computation of the deviance information criterion for latent variable models
• The valuation of equity warrants under the fractional Vasicek process of the short-term interest rate
• Option pricing using the fast Fourier transform under the double exponential jump model with stochastic volatility and stochastic intensity
• Efficient simulation and integrated likelihood estimation in state space models
• Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
• Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models
• A simple and efficient simulation smoother for state space time series analysis
• Bayesian Measures of Model Complexity and Fit
• Deviance information criteria for missing data models