When Long Memory Meets the Kalman Filter: A Comparative Study
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- Grassi, Stefano & Santucci de Magistris, Paolo, 2014. "When long memory meets the Kalman filter: A comparative study," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 301-319.
References listed on IDEAS
- Diebold, Francis X & Husted, Steven & Rush, Mark, 1991.
"Real Exchange Rates under the Gold Standard,"
Journal of Political Economy, University of Chicago Press, vol. 99(6), pages 1252-1271, December.
- Francis X. Diebold & Steven Husted & Mark Rush, 1990. "Real exchange rates under the gold standard," Discussion Paper / Institute for Empirical Macroeconomics 32, Federal Reserve Bank of Minneapolis.
- Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
- Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
- Bisaglia, Luisa & Guegan, Dominique, 1998. "A comparison of techniques of estimation in long-memory processes," Computational Statistics & Data Analysis, Elsevier, vol. 27(1), pages 61-81, March.
- Giot, Pierre & Laurent, Sebastien, 2004.
"Modelling daily Value-at-Risk using realized volatility and ARCH type models,"
Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
- Giot, P. & Laurent, S.F.J.A., 2001. "Modelling daily value-at-risk using realized volatility and arch type models," Research Memorandum 026, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
- GIOT, Pierre & LAURENT, Sébastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," LIDAM Reprints CORE 1708, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Pierre Giot & Sébastien Laurent, 2002. "Modelling Daily Value-at-Risk Using Realized Volatility and ARCH Type Models," Computing in Economics and Finance 2002 52, Society for Computational Economics.
- Shimotsu, Katsumi, 2010.
"Exact Local Whittle Estimation Of Fractional Integration With Unknown Mean And Time Trend,"
Econometric Theory, Cambridge University Press, vol. 26(2), pages 501-540, April.
- Katsumi Shimotsu, 2006. "Exact Local Whittle Estimation of Fractional Integration with Unknown Mean and Time Trend," Working Paper 1061, Economics Department, Queen's University.
- Perron, Pierre & Qu, Zhongjun, 2010.
"Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 275-290.
- Pierre Perron & Zhongjun Qu, 2008. "Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices," Boston University - Department of Economics - Working Papers Series wp2008-004, Boston University - Department of Economics.
- Harvey, Andrew & Proietti, Tommaso (ed.), 2005. "Readings in Unobserved Components Models," OUP Catalogue, Oxford University Press, number 9780199278695, Decembrie.
- Qu, Zhongjun, 2011.
"A Test Against Spurious Long Memory,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 29(3), pages 423-438.
- Zhongjun Qu, 2011. "A Test Against Spurious Long Memory," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(3), pages 423-438, July.
- Zhongjun Qu, 2010. "A Test Against Spurious Long Memory," Boston University - Department of Economics - Working Papers Series WP2010-051, Boston University - Department of Economics.
- Ohanissian, Arek & Russell, Jeffrey R. & Tsay, Ruey S., 2008. "True or Spurious Long Memory? A New Test," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 161-175, April.
- Andrew Harvey & Esther Ruiz & Neil Shephard, 1994. "Multivariate Stochastic Variance Models," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(2), pages 247-264.
- Zaffaroni, Paolo, 2004. "Contemporaneous aggregation of linear dynamic models in large economies," Journal of Econometrics, Elsevier, vol. 120(1), pages 75-102, May.
- James H. Stock & Mark W. Watson, 2007.
"Why Has U.S. Inflation Become Harder to Forecast?,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
- James H. Stock & Mark W. Watson, 2006. "Why Has U.S. Inflation Become Harder to Forecast?," NBER Working Papers 12324, National Bureau of Economic Research, Inc.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003.
"Modeling and Forecasting Realized Volatility,"
Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," Center for Financial Institutions Working Papers 01-01, Wharton School Center for Financial Institutions, University of Pennsylvania.
- Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers 02-12, Duke University, Department of Economics.
- Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2001. "Modeling and Forecasting Realized Volatility," NBER Working Papers 8160, National Bureau of Economic Research, Inc.
- María Dolores Gadea & Laura Mayoral, 2006.
"The Persistence of Inflation in OECD Countries: A Fractionally Integrated Approach,"
International Journal of Central Banking, International Journal of Central Banking, vol. 2(1), March.
- Gadea, Maria & Mayoral, Laura, 2005. "The Persistence of Inflation in OECD Countries: A Fractionally Integrated Approach," MPRA Paper 815, University Library of Munich, Germany.
- Laura Mayoral, 2005. "The persistence of inflation in OECD countries: A fractionally integrated approach," Economics Working Papers 958, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2005.
- Laura Mayoral, 2005. "The Persistence of Inflation in OECD Countries:a Fractionally Integrated Approach," Working Papers 259, Barcelona School of Economics.
- Philipp Sibbertsen & Robinson Kruse, 2009.
"Testing for a break in persistence under long‐range dependencies,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 263-285, May.
- Sibbertsen, Philipp & Kruse, Robinson, 2007. "Testing for a break in persistence under long-range dependencies," Hannover Economic Papers (HEP) dp-381, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
- Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
- Raggi, Davide & Bordignon, Silvano, 2012.
"Long memory and nonlinearities in realized volatility: A Markov switching approach,"
Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3730-3742.
- S. Bordignon & D. Raggi, 2010. "Long memory and nonlinearities in realized volatility: a Markov switching approach," Working Papers 694, Dipartimento Scienze Economiche, Universita' di Bologna.
- Iglesias, Pilar & Jorquera, Hector & Palma, Wilfredo, 2006. "Data analysis using regression models with missing observations and long-memory: an application study," Computational Statistics & Data Analysis, Elsevier, vol. 50(8), pages 2028-2043, April.
- Clifford M. Hurvich & Eric Moulines & Philippe Soulier, 2005.
"Estimating Long Memory in Volatility,"
Econometrica, Econometric Society, vol. 73(4), pages 1283-1328, July.
- Clifford Hurvich & Eric Moulines & Philippe Soulier, 2004. "Estimating Long Memory in Volatility," Econometrics 0412006, University Library of Munich, Germany.
- Lu, Yang K. & Perron, Pierre, 2010.
"Modeling and forecasting stock return volatility using a random level shift model,"
Journal of Empirical Finance, Elsevier, vol. 17(1), pages 138-156, January.
- Yang K. Lu & Pierre Perron, 2008. "Modeling and Forecasting Stock Return Volatility Using a Random Level Shift Model," Boston University - Department of Economics - Working Papers Series wp2008-012, Boston University - Department of Economics.
- Haldrup, Niels & Nielsen, Morten Orregaard, 2007.
"Estimation of fractional integration in the presence of data noise,"
Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3100-3114, March.
- Haldrup, Niels & Nielsen, Morten Oe., "undated". "Estimation of Fractional Integration in the Presence of Data Noise," Economics Working Papers 2003-10, Department of Economics and Business Economics, Aarhus University.
- Deo, Rohit S. & Hurvich, Clifford M., 2001. "On The Log Periodogram Regression Estimator Of The Memory Parameter In Long Memory Stochastic Volatility Models," Econometric Theory, Cambridge University Press, vol. 17(4), pages 686-710, August.
- Breidt, F. Jay & Crato, Nuno & de Lima, Pedro, 1998. "The detection and estimation of long memory in stochastic volatility," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 325-348.
- Jushan Bai & Pierre Perron, 2003.
"Computation and analysis of multiple structural change models,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
- BAI, Jushan & PERRON, Pierre, 1998. "Computation and Analysis of Multiple Structural-Change Models," Cahiers de recherche 9807, Universite de Montreal, Departement de sciences economiques.
- Tom Doan, "undated". "MULTIPLEBREAKS: RATS procedure to perform multiple structural change analysis," Statistical Software Components RTS00138, Boston College Department of Economics.
- Tom Doan, "undated". "RATS programs to replicate examples of Bai-Perron procedure," Statistical Software Components RTZ00008, Boston College Department of Economics.
- Tom Doan, "undated". "BAIPERRON: RATS procedure to perform Bai-Perron Test for Multiple Structural Changes," Statistical Software Components RTS00013, Boston College Department of Economics.
- Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
- Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, vol. 61(1), pages 43-76, July.
- Morten Ørregaard Nielsen & Per Houmann Frederiksen, 2005.
"Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration,"
Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 405-443.
- Morten Ø. Nielsen & Per Houmann Frederiksen, 2005. "Finite Sample Comparison Of Parametric, Semiparametric, And Wavelet Estimators Of Fractional Integration," Working Paper 1189, Economics Department, Queen's University.
- Arteche, J., 2006.
"Semiparametric estimation in perturbed long memory series,"
Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2118-2141, December.
- Arteche González, Jesús María, 2005. "Semiparametric estimation in perturbed long memory series," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
- Josu Arteche, 2006. "Semiparametric estimation in perturbed long memory series," Computing in Economics and Finance 2006 22, Society for Computational Economics.
- Granger, Clive W. J. & Hyung, Namwon, 2004. "Occasional structural breaks and long memory with an application to the S&P 500 absolute stock returns," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 399-421, June.
- Juan J. Dolado & Jesús Gonzalo & Laura Mayoral, 2005.
"What is What? A Simple Time-Domain Test of Long-memory vs. Structural Breaks,"
Working Papers
258, Barcelona School of Economics.
- Juan J. Dolado & Jesús Gonzalo & Laura Mayoral, 2005. "What is what?: A simple time-domain test of long-memory vs. structural breaks," Economics Working Papers 954, Department of Economics and Business, Universitat Pompeu Fabra.
- Pipiras, Vladas & Taqqu, Murad S. & Abry, Patrice, 2003. "Can continuous-time stationary stable processes have discrete linear representations?," Statistics & Probability Letters, Elsevier, vol. 64(2), pages 147-157, August.
- Clifford M. Hurvich & Bonnie K. Ray, 2003. "The Local Whittle Estimator of Long-Memory Stochastic Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 1(3), pages 445-470.
- Katsumi Shimotsu, 2006. "Simple (but Effective) Tests Of Long Memory Versus Structural Breaks," Working Paper 1101, Economics Department, Queen's University.
- Baillie, Richard T & Chung, Ching-Fan & Tieslau, Margie A, 1996. "Analysing Inflation by the Fractionally Integrated ARFIMA-GARCH Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(1), pages 23-40, Jan.-Feb..
- C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
- Luisa Bisaglia & Dominique Guegan, 1998. "A comparison of techniques of estimation in long-memory processes," Post-Print halshs-00194462, HAL.
- 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.
- Durbin, James & Koopman, Siem Jan, 2012.
"Time Series Analysis by State Space Methods,"
OUP Catalogue,
Oxford University Press,
edition 2, number 9780199641178, Decembrie.
- Durbin, James & Koopman, Siem Jan, 2001. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, number 9780198523543, Decembrie.
- Tom Doan, "undated". "SEASONALDLM: RATS procedure to create the matrices for the seasonal component of a DLM," Statistical Software Components RTS00251, Boston College Department of Economics.
- Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
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- Pierre Perron & Rasmus T. Varneskov, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2011-050, Boston University - Department of Economics.
- Rasmus T. Varneskov & Pierre Perron, 2017. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series WP2017-006, Boston University - Department of Economics.
- Rasmus T. Varneskov & Pierre Perron, 2015. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," Boston University - Department of Economics - Working Papers Series wp2015-015, Boston University - Department of Economics.
- Rasmus Tangsgaard Varneskov & Pierre Perron, 2011. "Combining Long Memory and Level Shifts in Modeling and Forecasting the Volatility of Asset Returns," CREATES Research Papers 2011-26, Department of Economics and Business Economics, Aarhus University.
- Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
- Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2015.
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- Davide Delle Monache & Stefano Grassi & Paolo Santucci, 2015. "Testing for Level Shifts in Fractionally Integrated Processes: a State Space Approach," Studies in Economics 1511, School of Economics, University of Kent.
- Andersson, Fredrik N.G. & Li, Yushu, 2013. "How Flexible are the Inflation Targets? A Bayesian MCMC Estimator of the Long Memory Parameter in a State Space Model," Working Papers 2013:38, Lund University, Department of Economics.
- Cuestas Juan Carlos & Gil-Alana Luis Alberiko, 2016. "Testing for long memory in the presence of non-linear deterministic trends with Chebyshev polynomials," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(1), pages 57-74, February.
- Davide Delle Monache & Stefano Grassi & Paolo Santucci de Magistris, 2017. "Does the ARFIMA really shift?," CREATES Research Papers 2017-16, Department of Economics and Business Economics, Aarhus University.
- Salman Huseynov, 2021. "Long and short memory in dynamic term structure models," CREATES Research Papers 2021-15, Department of Economics and Business Economics, Aarhus University.
- Kruse, Robinson, 2015. "A modified test against spurious long memory," Economics Letters, Elsevier, vol. 135(C), pages 34-38.
- Andersson, Fredrik N. G. & Li, Yushu, 2014. "Are Central Bankers Inflation Nutters? - A Bayesian MCMC Estimator of the Long Memory Parameter in a State Space Model," Discussion Papers 2014/38, Norwegian School of Economics, Department of Business and Management Science.
- Tobias Hartl & Roland Jucknewitz, 2022.
"Approximate state space modelling of unobserved fractional components,"
Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 75-98, January.
- Tobias Hartl & Roland Weigand, 2018. "Approximate State Space Modelling of Unobserved Fractional Components," Papers 1812.09142, arXiv.org, revised May 2020.
- Dissanayake, G.S. & Peiris, M.S. & Proietti, T., 2016. "State space modeling of Gegenbauer processes with long memory," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 115-130.
- Fredrik N. G. Andersson & Yushu Li, 2020. "Are Central Bankers Inflation Nutters? An MCMC Estimator of the Long-Memory Parameter in a State Space Model," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 529-549, February.
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More about this item
Keywords
ARFIMA models; Kalman Filter; Missing Observations; Measurement Error; Level Shifts.;All these keywords.
JEL classification:
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2011-05-24 (Econometrics)
- NEP-ETS-2011-05-24 (Econometric Time Series)
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