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跳躍風險下狀態轉換模型下SEM演算法及Gibbs Sampling之參數...

國立高雄大學統計學研究所

跳躍風險下狀態轉換模型下SEM演算法及Gibbs Sampling之參數變異數估計 = Estimating Variance of parameters by Supplemented Expectation Maximization Algorithm and Gibbs Sampling in Regime-Switching Model with Jump Risks

Record Type:	Language materials, printed : monographic
Paralel Title:	Estimating Variance of parameters by Supplemented Expectation Maximization Algorithm and Gibbs Sampling in Regime-Switching Model with Jump Risks
Author:	徐于琇,
Secondary Intellectual Responsibility:	國立高雄大學
Place of Publication:	[高雄市]
Published:	撰者;
Year of Publication:	2009[民98]
Description:	71面圖、表 : 30公分;
Subject:	EM演算法
Subject:	EM algorithm
Online resource:	http://handle.ncl.edu.tw/11296/ndltd/96282640043616899508
Notes:	參考書目：面
Notes:	指導教授：林士貴
Summary:	Hamilton (1989) 提出馬可夫轉換模型 (Markov Switching Model)，此模型以馬可夫鏈來描述在不同的景氣下狀態轉移的情況。然而，考慮到股價會受到突發事件的衝擊而造成股價不正常跳躍，便延生出兩種跳躍風險下狀態轉換模型(Regime-Switching model with jump risks )，一個是與狀態獨立的跳躍過程；另一個是與狀態相依的跳躍過程。在此論文中，我們將國際指數套用在跳躍風險下狀態轉換模型，基於Expectation-Maximization演算法以及Gibbs sampling進行參數估計以及使用Supplemented EM演算法估計參數變異數。 Hamilton (1989) proposed Markov switching model, which is based on Markov chain to describe the situation of state switching in different economy circumstances. However, taking into account that the stock price will occur abnormal jumps due to the impact of unexpected events, so Wong (2008) extended Markov switching model to two kinds of the regime-switching model with jump risks. One is a jump process independent on the states, the other is a jump process dependent on the states. In this paper, we will fit the regime-switching model with jump risks to the international indices, and proceed parameter estimation based on the Expectation-Maximization algorithm and Gibbs sampling and use Supplemented EM algorithm to estimate variance of parameter estimators.

跳躍風險下狀態轉換模型下SEM演算法及Gibbs Sampling之參數變異數估計 = Estimating Variance of parameters by Supplemented Expectation Maximization Algorithm and Gibbs Sampling in Regime-Switching Model with Jump Risks
徐, 于琇

跳躍風險下狀態轉換模型下SEM演算法及Gibbs Sampling之參數變異數估計 = Estimating Variance of parameters by Supplemented Expectation Maximization Algorithm and Gibbs Sampling in Regime-Switching Model with Jump Risks / 徐于琇撰 - [高雄市] : 撰者, 2009[民98]. - 71面 ; 圖、表 ; 30公分.
參考書目：面指導教授：林士貴.
EM演算法EM algorithm

跳躍風險下狀態轉換模型下SEM演算法及Gibbs Sampling之參數變異數估計 = Estimating Variance of parameters by Supplemented Expectation Maximization Algorithm and Gibbs Sampling in Regime-Switching Model with Jump Risks
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