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Computational Aspects of Maximum Likelihood Estimation of Autoregressive Fractionally Integrated Moving Average Models

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Cited by:

  1. M. Angeles Carnero & Siem Jan Koopman & Marius Ooms, 2003. "Periodic Heteroskedastic RegARFIMA Models for Daily Electricity Spot Prices," Tinbergen Institute Discussion Papers 03-071/4, Tinbergen Institute.
  2. McHale, I.G. & Peel, D.A., 2010. "Habit and long memory in UK lottery sales," Economics Letters, Elsevier, vol. 109(1), pages 7-10, October.
  3. Kubokawa, Tatsuya & Nagashima, Bui, 2012. "Parametric bootstrap methods for bias correction in linear mixed models," Journal of Multivariate Analysis, Elsevier, vol. 106(C), pages 1-16.
  4. Asai Manabu & Peiris Shelton & McAleer Michael & Allen David E., 2020. "Cointegrated Dynamics for a Generalized Long Memory Process: Application to Interest Rates," Journal of Time Series Econometrics, De Gruyter, vol. 12(1), pages 1-18, January.
  5. Neil Kellard & Denise Osborn & Jerry Coakley & Simone D. Grose & Gael M. Martin & Donald S. Poskitt, 2015. "Bias Correction of Persistence Measures in Fractionally Integrated Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 721-740, September.
  6. Blazej Mazur, 2015. "Density forecasts based on disaggregate data: nowcasting Polish inflation," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 71-87.
  7. Palma, Wilfredo & Bondon, Pascal & Tapia, José, 2008. "Assessing influence in Gaussian long-memory models," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4487-4501, May.
  8. N. H. Chan & A. E. Brockwell, 2006. "Long-memory dynamic Tobit models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(5), pages 351-367.
  9. Bhardwaj, Geetesh & Swanson, Norman R., 2006. "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 539-578.
  10. Shelton Peiris & Manabu Asai & Michael McAleer, 2017. "Estimating and Forecasting Generalized Fractional Long Memory Stochastic Volatility Models," JRFM, MDPI, vol. 10(4), pages 1-16, December.
  11. Martin, Gael M. & Nadarajah, K. & Poskitt, D.S., 2020. "Issues in the estimation of mis-specified models of fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 215(2), pages 559-573.
  12. Guglielmo Maria Caporale & Luis Alberiko Gil-Alana, 2024. "Persistence and long memory in monetary policy spreads," Applied Economics, Taylor & Francis Journals, vol. 56(20), pages 2422-2433, April.
  13. Jos'e Igor Morlanes, 2017. "Mixed Models as an Alternative to Farima," Papers 1712.03044, arXiv.org.
  14. Guglielmo Maria Caporale & Luis Alberiko Gil-Alana & Nicola Rubino & Inmaculada Vilchez, 2024. "Modelling Loans to Non-Financial Corporations in the Eurozone: A Long-Memory Approach," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 30(3), pages 231-254, August.
  15. Doornik Jurgen A & Ooms Marius, 2004. "Inference and Forecasting for ARFIMA Models With an Application to US and UK Inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(2), pages 1-25, May.
  16. Fraire, Francisco & Leatham, David J., 2006. "Decision Making Tool to Hedge Exchange Rate Risk," 2006 Agricultural and Rural Finance Markets in Transition, October 2-3, 2006, Washington, DC 133082, Regional Research Committee NC-1014: Agricultural and Rural Finance Markets in Transition.
  17. D.S. Poskitt & Gael M. Martin & Simone D. Grose, 2012. "Bias Reduction of Long Memory Parameter Estimators via the Pre-filtered Sieve Bootstrap," Monash Econometrics and Business Statistics Working Papers 8/12, Monash University, Department of Econometrics and Business Statistics.
  18. Barndorff-Nielsen, Ole E. & Shephard, Neil, 2006. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 217-252.
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