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G. Schwert (1988)
Tests for Unit Roots: a Monte Carlo InvestigationEconometrics eJournal
Eric Jacquier, Nicholas Polson, Peter Rossi (1994)
Bayesian Analysis of Stochastic Volatility ModelsJournal of Business & Economic Statistics, 20
T. Andersen, Bent Sørensen (1996)
GMM Estimation of a Stochastic Volatility Model: A Monte Carlo StudyJournal of Business & Economic Statistics, 14
N. Shephard (1993)
Fitting Nonlinear Time-Series Models with Applications to Stochastic Variance ModelsJournal of Applied Econometrics, 8
A. Harvey, E. Ruiz, N. Shephard (1994)
Multivariate stochastic variance models
Jón Dańıelsson (1994)
Stochastic volatility in asset prices estimation with simulated maximum likelihoodJournal of Econometrics, 64
M. Dacorogna, Ulrich Müller, R. Nagler, R. Olsen, O. Pictet (1993)
A geographical model for the daily and weekly seasonal volatility in the foreign exchange marketJournal of International Money and Finance, 12
R. Engle (1999)
Arch Models "
(1982)
`Autoregressive conditional heteroskedasticity with estimates of the variance of UK in ̄ation
Pierre Perron, Serena Ng (1996)
Useful Modifications to some Unit Root Tests with Dependent Errors and their Local Asymptotic PropertiesThe Review of Economic Studies, 63
T. Bollerslev, R. Chou, Kenneth Kroner (1992)
ARCH modeling in finance: A review of the theory and empirical evidenceJournal of Econometrics, 52
Schwert Schwert (1989)
Tests for unit roots: a Monte‐Carlo investigationJournal of Business and Economic Statistics, 7
R. Engle (1982)
Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflationEconometrica, 50
T. Andersen, T. Bollerslev, F. Diebold, Paul Labys (1999)
The Distribution of Exchange Rate VolatilityEconometrics: Econometric & Statistical Methods - General eJournal
P. Phillips (1988)
Testing for a Unit Root in Time Series Regression
S. Pantula (1991)
Asymptotic Distributions of Unit-Root Tests When the Process Is Nearly StationaryJournal of Business & Economic Statistics, 9
F. Breidt, N. Crato, Pedro Lima (1998)
The detection and estimation of long memory in stochastic volatilityJournal of Econometrics, 83
E. Ruiz (1994)
Quasi-maximum likelihood estimation of stochastic volatility modelsJournal of Econometrics, 63
(1995)
`Regression with nonstationary stochastic volatility
R. Lumsdaine (1996)
Consistency and Asymptotic Normality of the Quasi-maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) ModelsEconometrica, 64
Angelo Melino, S. Turnbull (1990)
Pricing foreign currency options with stochastic volatilityJournal of Econometrics, 45
B. Hansen (1995)
REGRESSION WITH NONSTATIONARY VOLATILITYEconometrica, 63
(1992)
`ARCH models in ®nance: a selective review of the theory and empirical evidence
J. Stock (1986)
Unit roots, structural breaks and trendsHandbook of Econometrics, 4
It is now well established that the volatility of asset returns is time varying and highly persistent. One leading model that is used to represent these features of the data is the stochastic volatility model. The researcher may test for non‐stationarity of the volatility process by testing for a unit root in the log‐squared time series. This strategy for inference has many advantages, but is not followed in practice because these unit root tests are known to have very poor size properties. In this paper I show that new tests that are robust to negative MA roots allow a reliable test for a unit root in the volatility process to be conducted. In applying these tests to exchange rate and stock returns, strong rejections of non‐stationarity in volatility are obtained. Copyright © 1999 John Wiley & Sons, Ltd.
Journal of Applied Econometrics – Wiley
Published: May 1, 1999
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