題 目：Hidden Markov Models and Copulae
主講人：Ms. Weining Wang
時 間：101年3月15日(星期四)下午15:10-16:00
地 點：交大綜合一館427室
Abstract
Understanding the dynamics of high dimensional non-normal dependency
structure is a challenging task. This research aims at attacking this
problem by building up a hidden Markov model (HMM) for Hierarchical
Archimedean Copulae (HAC), where the HAC represent a wide class of
models for high dimensional dependency, and HMM is a statistical technique
to describe time varying dynamics. HMM applied to HAC provide flexible
modeling for high dimensional non Gaussian time series. Consistency results
for both parameters and HAC structures are established in an HMM framework.
The model is calibrated to exchange rate data with a VaR application, where
the model’s performance is compared with other dynamic models, and in the
second application we simulate rainfall process.
※ 編輯: cilar 來自: 122.117.193.35 (03/12 01:38)