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Three essays on volatility measureme...

Gao, Rui.

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Three essays on volatility measurement and modeling with price limits: A Bayesian approach.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Three essays on volatility measurement and modeling with price limits: A Bayesian approach./
Author:	Gao, Rui.
Description:	124 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-07(E), Section: A.
Contained By:	Dissertation Abstracts International75-07A(E).
Subject:	Economics, General. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NS27926
ISBN:	9780499279262

Three essays on volatility measurement and modeling with price limits: A Bayesian approach.
Gao, Rui.

Three essays on volatility measurement and modeling with price limits: A Bayesian approach. - 124 p.

Source: Dissertation Abstracts International, Volume: 75-07(E), Section: A.

Thesis (Ph.D.)--Queen's University (Canada), 2014.

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

This dissertation studies volatility measurement and modeling issues when asset prices are subject to price limits based on Bayesian approaches. Two types of estimators are developed to consistently estimate integrated volatility in the presence of price limits. One is a realized volatility type estimator, but using both realized asset prices and simulated asset prices. The other is a discrete sample analogue of integrated volatility using posterior samples of the latent volatility states. These two types of estimators are first constructed based on the simple log-stochastic volatility model in Chapter 2. The simple log-stochastic volatility framework is extended in Chapter 3 to incorporate correlated innovations and further extended in Chapter 4 to accommodate jumps and fat-tailed innovations. For each framework, a MCMC algorithm is designed to simulate the unobserved asset prices, model parameters and latent states. Performances of both type estimators are also examined using simulations under each framework. Applications to Chinese stock markets are also provided.

ISBN: 9780499279262Subjects--Topical Terms:

1017424
Economics, General.

Three essays on volatility measurement and modeling with price limits: A Bayesian approach.
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100 1 $a Gao, Rui. $3 1946771
245 1 0 $a Three essays on volatility measurement and modeling with price limits: A Bayesian approach.
300 $a 124 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-07(E), Section: A.
500 $a Adviser: Morten Nielsen.
502 $a Thesis (Ph.D.)--Queen's University (Canada), 2014.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a This dissertation studies volatility measurement and modeling issues when asset prices are subject to price limits based on Bayesian approaches. Two types of estimators are developed to consistently estimate integrated volatility in the presence of price limits. One is a realized volatility type estimator, but using both realized asset prices and simulated asset prices. The other is a discrete sample analogue of integrated volatility using posterior samples of the latent volatility states. These two types of estimators are first constructed based on the simple log-stochastic volatility model in Chapter 2. The simple log-stochastic volatility framework is extended in Chapter 3 to incorporate correlated innovations and further extended in Chapter 4 to accommodate jumps and fat-tailed innovations. For each framework, a MCMC algorithm is designed to simulate the unobserved asset prices, model parameters and latent states. Performances of both type estimators are also examined using simulations under each framework. Applications to Chinese stock markets are also provided.
590 $a School code: 0283.
650 4 $a Economics, General. $3 1017424
690 $a 0501
710 2 $a Queen's University (Canada). $b Economics. $3 2098371
773 0 $t Dissertation Abstracts International $g 75-07A(E).
790 $a 0283
791 $a Ph.D.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=NS27926