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A Stochastic Volatility Model With L...

Jiang, Hong.

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A Stochastic Volatility Model With Leverage Effect and Regime Switching.

Record Type:	Electronic resources : Monograph/item
Title/Author:	A Stochastic Volatility Model With Leverage Effect and Regime Switching./
Author:	Jiang, Hong.
Description:	131 p.
Notes:	Source: Dissertation Abstracts International, Volume: 76-04(E), Section: A.
Contained By:	Dissertation Abstracts International76-04A(E).
Subject:	Economics, General. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3645781
ISBN:	9781321351798

A Stochastic Volatility Model With Leverage Effect and Regime Switching.
Jiang, Hong.

A Stochastic Volatility Model With Leverage Effect and Regime Switching. - 131 p.

Source: Dissertation Abstracts International, Volume: 76-04(E), Section: A.

Thesis (Ph.D.)--State University of New York at Albany, 2014.

This item must not be sold to any third party vendors.

Modeling the volatility of asset returns is a very important study in financial economics. Among the time-varying volatility models, the Stochastic Volatility (SV) models are argued to have advantages over the autoregressive conditional heteroskedasticity (ARCH) models. The purpose of this article is to put forward a generalized and flexible Stochastic Volatility model, the Stochastic Volatility Model with Leverage Effect and Regime Switching (SVLR model), which could capture the complex features of financial time series to the most extent.

ISBN: 9781321351798Subjects--Topical Terms:

1017424
Economics, General.

A Stochastic Volatility Model With Leverage Effect and Regime Switching.
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020 $a 9781321351798
035 $a (MiAaPQ)AAI3645781
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100 1 $a Jiang, Hong. $3 1019090
245 1 2 $a A Stochastic Volatility Model With Leverage Effect and Regime Switching.
300 $a 131 p.
500 $a Source: Dissertation Abstracts International, Volume: 76-04(E), Section: A.
500 $a Advisers: Bruce C. Dieffenbach; George Monokroussos.
502 $a Thesis (Ph.D.)--State University of New York at Albany, 2014.
506 $a This item must not be sold to any third party vendors.
520 $a Modeling the volatility of asset returns is a very important study in financial economics. Among the time-varying volatility models, the Stochastic Volatility (SV) models are argued to have advantages over the autoregressive conditional heteroskedasticity (ARCH) models. The purpose of this article is to put forward a generalized and flexible Stochastic Volatility model, the Stochastic Volatility Model with Leverage Effect and Regime Switching (SVLR model), which could capture the complex features of financial time series to the most extent.
520 $a Even though the estimation to this SVLR model is a hard problem, a Bayesian Markov Chain Monte Carlo (MCMC) estimation method based on the Gibbs sampling algorithm is developed in the article. The SVLR model is applied to the S&P 500 index data and the relevant evolution of volatility process is studied.
520 $a In order to evaluate the likelihood of the SVLR model, a specific particle filter for the SVLR model is proposed, the diagnostic tests and the model comparison between the SVLR model and other existing time-varying volatility models under the Bayesian framework are conducted. The proposed SVLR model proves to outperform existing models in terms of its flexibility of describing the features of stock volatilities and better fitting the financial data.
520 $a The out-of-sample forecasting performance of SVLR model can be proved good enough, which suggests the promising application of the SVLR model in financial risk management areas. A new perspective to study the connection between stock market volatility and business cycle is proposed through combing the SVLR model with the regime switching autoregressive industrial production model in this article either.
590 $a School code: 0668.
650 4 $a Economics, General. $3 1017424
650 4 $a Economics, Finance. $3 626650
650 4 $a Statistics. $3 517247
690 $a 0501
690 $a 0508
690 $a 0463
710 2 $a State University of New York at Albany. $b Economics. $3 1024072
773 0 $t Dissertation Abstracts International $g 76-04A(E).
790 $a 0668
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3645781