Testing for a Single-Factor Stochastic Volatility in Bivariate Series

Testing for a Single-Factor Stochastic Volatility in Bivariate Series

This paper proposes the Lagrange multiplier test for the null hypothesis thatthe bivariate time series has only a single common stochastic volatility factor and noidiosyncratic volatility factor. The test statistic is derived by representing the model in alinear state-space form under the assumption...

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Main Authors: Masaru Chiba, Masahito Kobayashi
Format: Article
Language:English
Published: MDPI AG 2013-12-01
Series:Journal of Risk and Financial Management
Subjects:
stochastic volatility model
Kalman filter
Lagrange multiplier test
Online Access:http://www.mdpi.com/1911-8074/6/1/31
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spelling doaj-d39c212f1ad94cbe8cd1915ce082ca252020-11-24T23:15:13ZengMDPI AGJournal of Risk and Financial Management1911-80742013-12-0161316110.3390/jrfm6010031jrfm6010031Testing for a Single-Factor Stochastic Volatility in Bivariate SeriesMasaru Chiba0Masahito Kobayashi1Faculty of Engineering, Fukui University of Technology, 3-6-1 Gakuen, Fukui 910-8505, JapanFaculty of Economics, Yokohama National University, 79-4 Tokiwadai, Yokohama 240-8501, JapanThis paper proposes the Lagrange multiplier test for the null hypothesis thatthe bivariate time series has only a single common stochastic volatility factor and noidiosyncratic volatility factor. The test statistic is derived by representing the model in alinear state-space form under the assumption that the log of squared measurement error isnormally distributed. The empirical size and power of the test are examined in Monte Carloexperiments. We apply the test to the Asian stock market indices.http://www.mdpi.com/1911-8074/6/1/31stochastic volatility modelKalman filterLagrange multiplier test
collection DOAJ
language English
format Article
sources DOAJ
author Masaru Chiba
Masahito Kobayashi
spellingShingle Masaru Chiba
Masahito Kobayashi
Testing for a Single-Factor Stochastic Volatility in Bivariate Series
Journal of Risk and Financial Management
stochastic volatility model
Kalman filter
Lagrange multiplier test
author_facet Masaru Chiba
Masahito Kobayashi
author_sort Masaru Chiba
title Testing for a Single-Factor Stochastic Volatility in Bivariate Series
title_short Testing for a Single-Factor Stochastic Volatility in Bivariate Series
title_full Testing for a Single-Factor Stochastic Volatility in Bivariate Series
title_fullStr Testing for a Single-Factor Stochastic Volatility in Bivariate Series
title_full_unstemmed Testing for a Single-Factor Stochastic Volatility in Bivariate Series
title_sort testing for a single-factor stochastic volatility in bivariate series
publisher MDPI AG
series Journal of Risk and Financial Management
issn 1911-8074
publishDate 2013-12-01
description This paper proposes the Lagrange multiplier test for the null hypothesis thatthe bivariate time series has only a single common stochastic volatility factor and noidiosyncratic volatility factor. The test statistic is derived by representing the model in alinear state-space form under the assumption that the log of squared measurement error isnormally distributed. The empirical size and power of the test are examined in Monte Carloexperiments. We apply the test to the Asian stock market indices.
topic stochastic volatility model
Kalman filter
Lagrange multiplier test
url http://www.mdpi.com/1911-8074/6/1/31
work_keys_str_mv AT masaruchiba testingforasinglefactorstochasticvolatilityinbivariateseries
AT masahitokobayashi testingforasinglefactorstochasticvolatilityinbivariateseries
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