統計学輪講（第27回） 日時 2013年01月29日(火) 15時40分～16時30分 場所 経済学部新棟３階第３教室 講演者 朴 海香 (経済M1) 演題 Cholesky Stochastic Volatility Models for High-Dimensional Times Series.. 概要 Multivariate time-varying bolatility has many important applications in finance. Estimating multivariate volatility, however, is not easy because of two major difficulties. The first difficulty is the curse of dimensionality. The second difficulty is that the conditional covariance matrix must be positive definite for all time points. In ordet to simply maintain positive definiteness, Cholesky root of the time-varying covariance matrix model was proposed by H.F.Lopes, R.E.McCulloch and R.S.Tsay(2012). We will mainly talk about Cholesky Stochastic Volatility Models for High-Dimensional Times Series. We will also discuss the model's sensitiveness to the prior distribution and talk about the future works regarding this problem.