A flexible and automated likelihood based framework for inference in stochastic volatility models

• Main Authors: SKAUG, Hans J., YU, Jun
• 格式: text
• 語言: English
• 出版: Institutional Knowledge at Singapore Management University 2014
• 主題: Empirical Bayes; Laplace approximation; Automatic differentiation; AD Model Builder; Simulated maximum likelihood; Importance sampling; Econometrics; Economics
• 在線閱讀: https://ink.library.smu.edu.sg/soe_research/1615; https://ink.library.smu.edu.sg/context/soe_research/article/2614/viewcontent/FlexibleAutomatedLikelihoodStochasticVolatility_2014.pdf

The Laplace approximation is used to perform maximum likelihood estimation of univariate and multivariate stochastic volatility (SV) models. It is shown that the implementation of the Laplace approximation is greatly simplified by the use of a numerical technique known as automatic differentiation (...