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Markov Chain Monte Carlo Methods
Simulation Techniques in Financial Risk Management
This paper is concerned with simulation-based inference in generalized models of stochastic volatility deÿned by heavy-tailed Student-t distributions (with unknown degrees of freedom) and exogenous variables in the observation and volatility equations and a jump component in the observation equation. By building on the work of Kim, Shephard and Chib (Rev. Econom. Stud. 65 (1998) 361), we develop e cient Markov chain Monte Carlo algorithms for estimating these models. The paper also discussesdoi:10.1002/9781118735954.ch12 fatcat:ekacyhjqord4jadvtsc4nudffy