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References (33)
-
R. Baillie (1996)
Long memory processes and fractional integration in econometricsJournal of Econometrics, 73
-
M. Beine, S. Laurent (2003)
Central bank interventions and jumps in double long memory models of daily exchange ratesJournal of Empirical Finance, 10
-
P. Zaffaroni (2004)
STATIONARITY AND MEMORY OF ARCH(∞) MODELSEconometric Theory, 20
-
L. Giraitis, P. Kokoszka, R. Leipus (2000)
STATIONARY ARCH MODELS: DEPENDENCE STRUCTURE AND CENTRAL LIMIT THEOREMEconometric Theory, 16
-
Celso Brunetti, C. Gilbert (1999)
Bivariate FIGARCH and Fractional CointegrationEuropean Finance eJournal
-
Tim Bollerslev, H. Mikkelsen (1996)
MODELING AND PRICING LONG- MEMORY IN STOCK MARKET VOLATILITYJournal of Econometrics, 73
-
L. Giraitis, R. Leipus, D. Surgailis (2007)
Recent Advances in ARCH Modelling -
R. Engle, Jeffrey Russell (1998)
Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction DataEconometrica, 66
-
Changli He, Timo Terasvirta (1999)
Properties of the Autocorrelation Function of Squared Observations for Second‐order Garch Processes Under Two Sets of Parameter ConstraintsJournal of Time Series Analysis, 20
-
S. Laurent, J. Peters (2001)
G@RCH 2.2: An Ox Package for Estimating and Forecasting Various ARCH ModelsJournal of Economic Surveys, 16
-
R. Baillie, Tim Bollerslev, H. Mikkelsen (1996)
Fractionally integrated generalized autoregressive conditional heteroskedasticityJournal of Econometrics, 74
-
Zhuanxin Ding, C. Granger, R. Engle (1993)
A long memory property of stock market returns and a new model -
Fallaw Sowell (1992)
Maximum likelihood estimation of stationary univariate fractionally integrated time series modelsJournal of Econometrics, 53
-
Christian Conrad, M. Karanasos (2006)
The impulse response function of the long memory GARCH processEconomics Letters, 90
-
M. Caporin (2003)
Identification of long memory in GARCH modelsStatistical Methods and Applications, 12
-
J. Doornik, Marius Ooms (2003)
Multimodality in the GARCH Regression Model -
P. Sephton (2000)
Financial analysis package for GAUSSJournal of Applied Econometrics, 15
-
J. Jasiak (1999)
Persistence in Intertrade DurationsCapital Markets: Market Microstructure
-
Zhuanxin Ding, C. Granger (1996)
Modeling volatility persistence of speculative returns: A new approachJournal of Econometrics, 73
-
R. Baillie, Y. Han, Tae Kwon (2002)
Further Long Memory Properties of Inflationary ShocksSouthern Economic Journal, 68
-
P. Doukhan, G. Oppenheim, M. Taqqu (2003)
Theory and applications of long-range dependence -
J. Davidson (2004)
Moment and Memory Properties of Linear Conditional Heteroscedasticity Models, and a New ModelJournal of Business & Economic Statistics, 22
-
L. Giraitis, D. Surgailis (2003)
Larch, Leverage and Long MemoryEconometrics: Mathematical Methods & Programming eJournal
-
K. Abadir (1999)
An Introduction to Hypergeometric Functions for EconomistsERN: Other Econometrics: Mathematical Methods & Programming (Topic)
-
Marc Henry, P. Zaffaroni (2002)
The Long Range Dependence Paradigm for Macroeconomics and FinanceERN: Time-Series Models (Single) (Topic)
-
Daniel Nelson (1991)
CONDITIONAL HETEROSKEDASTICITY IN ASSET RETURNS: A NEW APPROACHEconometrica, 59
-
M. Karanasos, Zacharias Psaradakis, M. Solá (2002)
On the Autocorrelation Properties of Long‐Memory GARCH ProcessesJournal of Time Series Analysis, 25
-
Christian Conrad, M. Karanasos (2005)
On the inflation-uncertainty hypothesis in the USA, Japan and the UK: a dual long memory approachJapan and the World Economy, 17
-
Christian Conrad, M. Karanasos (2005)
Dual Long Memory in Inflation Dynamics across Countries of the Euro Area and the Link between Inflation Uncertainty and Macroeconomic PerformanceStudies in Nonlinear Dynamics & Econometrics, 9
-
Tim Bollerslev (1986)
Generalized autoregressive conditional heteroskedasticityJournal of Econometrics, 31
-
P. Robinson (1991)
Testing for strong serial correlation and dynamic conditional heteroskedasticity in multiple regressionJournal of Econometrics, 47
-
Daniel Nelson, C. Cao (1992)
Inequality Constraints in the Univariate GARCH ModelJournal of Business & Economic Statistics, 10
-
(1999)
Estimating the Fractionally Integrated GARCH Model.’
- Publisher
- Oxford University Press
- Copyright
- © Published by Oxford University Press.
- ISSN
- 1479-8409
- eISSN
- 1479-8417
- DOI
- 10.1093/jjfinec/nbj015
- Publisher site
- See Article on Publisher Site
Abstract
In this article we derive necessary and sufficient conditions for the nonnegativity of the conditional variance in the fractionally integrated generalized autoregressive conditional heteroskedastic (p, d, q) (FIGARCH) model of the order p ≤ 2 and sufficient conditions for the general model. These conditions can be seen as being analogous to those derived by Nelson and Cao (1992, Journal of Business & Economic Statistics 10, 229–235) for the GARCH(p, q) model. However, the inequality constraints which we derive for the FIGARCH model illustrate two remarkable properties of the FIGARCH model which are in contrast to the GARCH model: (i) even if all parameters are nonnegative, the conditional variance can become negative and (ii) even if all parameters are negative (apart from d), the conditional variance can be nonnegative almost surely. In particular, the conditions for the (1, d, 1) model substantially enlarge the sufficient parameter set provided by Bollerslev and Mikkelsen (1996, Journal of Econometrics 73, 151–184). The importance of the result is illustrated in an empirical application of the FIGARCH(1, d, 1) model to Japanese yen versus U.S. dollar exchange rate data.
Journal
Journal of Financial Econometrics – Oxford University Press
Published: Jun 8, 2006