On a Multinomial Logistic Mixture Autoregressive Processes

2014 ◽  
Author(s):  
Musen Wen ◽  
Keh-Shin Lii
Keyword(s):  
Autoregressive Processes ◽  
Logistic Mixture

Multiscale Autoregressive Processes. Part 2. Lattice Structures for Whitening and Modeling

1992 ◽  
Author(s):  
Michele Basseville ◽  
Albert Benveniste ◽  
Alan S. Willsky
Keyword(s):  
Lattice Structures ◽  
Autoregressive Processes

scholarly journals MIXED CAUSAL-NONCAUSAL AR PROCESSES AND THE MODELLING OF EXPLOSIVE BUBBLES

2019 ◽  
Vol 35 (6) ◽  
pp. 1234-1270 ◽  
Author(s):  
Sébastien Fries ◽  
Jean-Michel Zakoian
Keyword(s):  
Conditional Distribution ◽  
Stable Distribution ◽  
Financial Time Series ◽  
Domain Of Attraction ◽  
Real Data ◽  
Autoregressive Processes ◽  
Financial Time ◽  
Causal Representation ◽  
Heavy Tailed ◽  
Non Gaussian

Noncausal autoregressive models with heavy-tailed errors generate locally explosive processes and, therefore, provide a convenient framework for modelling bubbles in economic and financial time series. We investigate the probability properties of mixed causal-noncausal autoregressive processes, assuming the errors follow a stable non-Gaussian distribution. Extending the study of the noncausal AR(1) model by Gouriéroux and Zakoian (2017), we show that the conditional distribution in direct time is lighter-tailed than the errors distribution, and we emphasize the presence of ARCH effects in a causal representation of the process. Under the assumption that the errors belong to the domain of attraction of a stable distribution, we show that a causal AR representation with non-i.i.d. errors can be consistently estimated by classical least-squares. We derive a portmanteau test to check the validity of the estimated AR representation and propose a method based on extreme residuals clustering to determine whether the AR generating process is causal, noncausal, or mixed. An empirical study on simulated and real data illustrates the potential usefulness of the results.

scholarly journals LASSO estimation for spherical autoregressive processes

2021 ◽  
Vol 137 ◽  
pp. 167-199
Author(s):  
Alessia Caponera ◽  
Claudio Durastanti ◽  
Anna Vidotto
Keyword(s):  
Autoregressive Processes

COMPARISON OF SOME NON-LINEAR AUTOREGRESSIVE PROCESSES

1986 ◽  
Vol 7 (3) ◽  
pp. 205-211 ◽  
Author(s):  
Göran Högnäs
Keyword(s):  
Autoregressive Processes ◽  
Non Linear

scholarly journals Asymptotic behavior of the variance of the EWMA statistic for autoregressive processes

2008 ◽  
Vol 78 (12) ◽  
pp. 1673-1682 ◽  
Author(s):  
M.B. Vermaat ◽  
F.H. van der Meulen ◽  
R.J.M.M. Does
Keyword(s):  
Asymptotic Behavior ◽  
Autoregressive Processes

OPTIMALITY OF THE MAXIMUM LIKELIHOOD ESTIMATOR IN FIRST-ORDER AUTOREGRESSIVE PROCESSES

1991 ◽  
Vol 12 (3) ◽  
pp. 237-253 ◽  
Author(s):  
Piotr W. Mikulski ◽  
Michael J. Monsour
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimator ◽  
Autoregressive Processes ◽  
Likelihood Estimator ◽  
First Order
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