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Computational Aspects of Maximum Likelihood Estimation of Autoregressive Fractionally Integrated Moving Average Models Author info | Abstract | Publisher info | Download info | Related research | Statistics Jurgen A. Doornik (Nuffield College, Oxford University)
Marius Ooms (Dept of Economics, Free University of Amsterdam)
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We discuss computational aspects of likelihood-based estimation of univariate ARFIMA (p,d,q) models. We show how efficient computation and simulation is feasible, even for large samples. We also discuss the implementation of analytical bias corrections.
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Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number
2001-W27.
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Length: 14 pages
Date of creation: 29 Nov 2001Date of revision:
Handle: RePEc:nuf:econwp:0127Contact details of provider: Web page: http://www.nuff.ox.ac.uk/economics/
For technical questions regarding this item, or to correct its listing, contact: (Catherine McNeill).
Keywords: Long memory Bias Modified profile likelihood Restricted maximum likelihood estimator Time-series regression model likelihood Other versions of this item:
Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques
This paper has been announced in the following NEP Reports :
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.: Sowell, Fallaw, 1992.
"Maximum likelihood estimation of stationary univariate fractionally integrated time series models ,"
Journal of Econometrics ,
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[Downloadable!] (restricted)
Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999.
"Statistical algorithms for models in state space using SsfPack 2.2 ,"
Econometrics Journal ,
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Other versions: Smith, Anthony A, Jr & Sowell, Fallaw & Zin, Stanley E, 1997.
"Fractional Integration with Drift: Estimation in Small Samples ,"
Empirical Economics ,
Springer, vol. 22(1), pages 103-16.
Other versions: M. Ooms & J.A. Doornik, 1999.
"Inference and forecasting for fractional autoregressive integrated moving average models; with an application to US and UK inflation ,"
Econometric Institute Report
171, Erasmus University Rotterdam, Econometric Institute.
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Beveridge, Steve & Oickle, Cyril, 1993.
"Estimating fractionally integrated time series models ,"
Economics Letters ,
Elsevier, vol. 43(2), pages 137-142.
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Chung, Ching-Fan & Baillie, Richard T, 1993.
"Small Sample Bias in Conditional Sum-of-Squares Estimators of Fractionally Integrated ARMA Models ,"
Empirical Economics ,
Springer, vol. 18(4), pages 791-806.
Bollerslev, Tim & Jubinski, Dan, 1999.
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
Marius Ooms & M. Angeles Carnero & Siem Jan Koopman, 2004.
"Periodic Heteroskedastic RegARFIMA models for daily electricity spot prices ,"
Econometric Society 2004 Australasian Meetings
158, Econometric Society.
[Downloadable!]
Other versions: Jurgen Doornik & Marius Ooms, 2004.
"Inference and Forecasting for ARFIMA Models With an Application to US and UK Inflation ,"
Studies in Nonlinear Dynamics & Econometrics ,
Berkeley Electronic Press, vol. 8(2), pages 1218-1218.
[Downloadable!] (restricted)
Sandrine Lardic & Valerie Mignon, 2004.
"The exact maximum likelihood estimation of ARFIMA processes and model selection criteria: A Monte Carlo study ,"
Economics Bulletin ,
Economics Bulletin, vol. 3(21), pages 1-16.
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Other versions: E. Dubois & S. Lardic & V. Mignon, 2003.
"The exact maximum likelihood-based test for fractional cointegration: critical values, power and size ,"
THEMA Working Papers
2003-26, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
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Other versions: Charles S. Bos, 2003.
"Time Series Modelling using TSMod 3.24 ,"
Tinbergen Institute Discussion Papers
03-091/4, Tinbergen Institute.
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Other versions: Siem Jan Koopman & Borus Jungbacker & Eugenie Hol, 2004.
"Forecasting Daily Variability of the S&P 100 Stock Index using Historical, Realised and Implied Volatility Measurements ,"
Tinbergen Institute Discussion Papers
04-016/4, Tinbergen Institute.
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Eugenie Hol & Siem Jan Koopman & Borus Jungbacker, 2004.
"Forecasting daily variability of the S\&P 100 stock index using historical, realised and implied volatility measurements ,"
Computing in Economics and Finance 2004
342, Society for Computational Economics.
Koopman, Siem Jan & Jungbacker, Borus & Hol, Eugenie, 2005.
"Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements ,"
Journal of Empirical Finance ,
Elsevier, vol. 12(3), pages 445-475, June.
[Downloadable!] (restricted) Ole E. Barndorff-Nielsen & Neil Shephard, 2003.
"Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes ,"
Economics Papers
2003-W12, Economics Group, Nuffield College, University of Oxford.
[Downloadable!]
Other versions: Siem Jan Koopman & Marius Ooms & M. Angeles Carnero, 2005.
"Periodic Seasonal Reg-ARFIMA-GARCH Models for Daily Electricity Spot Prices ,"
Tinbergen Institute Discussion Papers
05-091/4, Tinbergen Institute.
[Downloadable!]
Other versions: Geetesh Bhardwaj & Norman Swanson, 2004.
"An Empirical Investigation of the Usefulness of ARFIMA Models for Predicting Macroeconomic and Financial Time Series ,"
Departmental Working Papers
200422, Rutgers University, Department of Economics.
[Downloadable!]
Other versions: Fulvio Corsi & Uta Kretschmer & Stefan Mittnik & Christian Pigorsch, 2005.
"The Volatility of Realized Volatility ,"
CFS Working Paper Series
2005/33, Center for Financial Studies.
[Downloadable!]
Charles S. Bos & Siem Jan Koopman & Marius Ooms, 2007.
"Long memory modelling of inflation with stochastic variance and structural breaks ,"
CREATES Research Papers
2007-44, School of Economics and Management, University of Aarhus.
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