Journal ArticleDOI
Analysing inflation by the fractionally integrated ARFIMA–GARCH model
TLDR
In this article, the authors apply long-memory processes to describe inflation for 10 countries, and find strong evidence of long memory with mean reverting behaviour for all countries except Japan, which appears stationary.Abstract:
This paper considers the application of long-memory processes to describing inflation for 10 countries. We implement a new procedure to obtain approximate maximum likelihood estimates of an ARFIMA-GARCH process; which is fractionally integrated I(d) with a superimposed stationary ARMA component in its conditional mean. Additionally, this long-memory process is allowed to have GARCH type conditional heteroscedasticity. On analysing monthly post-World War II CPI inflation for 10 different countries, we find strong evidence of long memory with mean reverting behaviour for all countries except Japan, which appears stationary. For three high inflation economies there is evidence that the mean and volatility of inflation interact in a way that is consistent with the Friedman hypothesis. Copyright 1996 by John Wiley & Sons, Ltd.read more
Citations
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Journal ArticleDOI
Long memory processes and fractional integration in econometrics
TL;DR: A survey and review of the major econometric work on long memory processes, fractional integration, and their applications in economics and finance and some of the definitions of long memory are reviewed.
Journal ArticleDOI
Modeling and pricing long- memory in stock market volatility
TL;DR: In this paper, a new class of fractionally integrated GARCH and EGARCH models for characterizing financial market volatility is discussed, and Monte Carlo simulations illustrate the reliability of quasi maximum likelihood estimation methods, standard model selection criteria, and residual-based portmanteau diagnostic tests in this context.
Journal ArticleDOI
Likelihood-based cointegration tests in heterogeneous panels
TL;DR: In this paper, a maximum likelihood panel test of the cointegrating rank in heterogeneous panel models based on the mean of the individual rank trace statistics is presented, and the existence of the first two moments of the asymptotic distribution of individual trace statistic is established.
Journal ArticleDOI
Physical approach to complex systems
TL;DR: This review advocate some of the computational methods which in this opinion are especially fruitful in extracting information on selected–but at the same time most representative–complex systems like human brain, financial markets and natural language, from the time series representing the observables associated with these systems.
Journal ArticleDOI
The Long Memory of the Efficient Market
Fabrizio Lillo,J. Doyne Farmer +1 more
TL;DR: For the London Stock Exchange, the autocorrelation function decays roughly as a power law with an exponent of 0.6, corresponding to a Hurst exponent H = 0.7 as discussed by the authors.
References
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Journal ArticleDOI
Distribution of the Estimators for Autoregressive Time Series with a Unit Root
David A. Dickey,Wayne A. Fuller +1 more
TL;DR: In this article, the limit distributions of the estimator of p and of the regression t test are derived under the assumption that p = ± 1, where p is a fixed constant and t is a sequence of independent normal random variables.
Journal ArticleDOI
Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation
TL;DR: In this article, a new class of stochastic processes called autoregressive conditional heteroscedastic (ARCH) processes are introduced, which are mean zero, serially uncorrelated processes with nonconstant variances conditional on the past, but constant unconditional variances.
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Time series analysis, forecasting and control
TL;DR: In this article, a complete revision of a classic, seminal, and authoritative book that has been the model for most books on the topic written since 1970 is presented, focusing on practical techniques throughout, rather than a rigorous mathematical treatment of the subject.
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A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix
Whitney K. Newey,Kenneth D. West +1 more
TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.
Journal ArticleDOI
Generalized autoregressive conditional heteroskedasticity
Tim Bollerslev,Tim Bollerslev +1 more
TL;DR: In this paper, a natural generalization of the ARCH (Autoregressive Conditional Heteroskedastic) process introduced in 1982 to allow for past conditional variances in the current conditional variance equation is proposed.
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