Properties of nonlinear transformations of fractionally integrated processes
AbstractThis paper shows that the properties of nonlinear transformations of a fractionally integrated process depend strongly on whether the initial series is stationary or not. Transforming a stationary Gaussian I(d) process with d > 0 leads to a long-memory process with the same or a smaller long-memory parameter depending on the Hermite rank of the transformation. Any nonlinear transformation of an antipersistent Gaussian I(d) process is I(0). For non-stationary I(d) processes, every integer power transformation is non-stationary and exhibits a deterministic trend in mean and in variance. In particular, the square of a non-stationary Gaussian I(d) process still has long memory with parameter d, whereas the square of a stationary Gaussian I(d) process shows less dependence than the initial process. Simulation results for other transformations are also discussed. --
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen in its series Technical Reports with number 2000,25.
Date of creation: 2000
Date of revision:
Contact details of provider:
Postal: Vogelpothsweg 78, D-44221 Dortmund
Phone: (0231) 755-3125
Fax: (0231) 755-5284
Web page: http://www.statistik.tu-dortmund.de/sfb475.html
More information through EDIRC
Other versions of this item:
- Dittmann, Ingolf & Granger, Clive W. J., 2002. "Properties of nonlinear transformations of fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 110(2), pages 113-133, October.
- Dittmann, Ingolf & Granger, Clive W.J., 2000. "Properties of Nonlinear Transformations of Fractionally Integrated Processes," University of California at San Diego, Economics Working Paper Series qt0kk9x0mc, Department of Economics, UC San Diego.
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.:
- Diebold, Francis X. & Inoue, Atsushi, 2001.
"Long memory and regime switching,"
Journal of Econometrics,
Elsevier, vol. 105(1), pages 131-159, November.
- Granger, Clive W J, 1995. "Modelling Nonlinear Relationships between Extended-Memory Variables," Econometrica, Econometric Society, vol. 63(2), pages 265-79, March.
- Marzio Galeotti & Matteo Manera & Alessandro Lanza, 2009. "On the Robustness of Robustness Checks of the Environmental Kuznets Curve Hypothesis," Environmental & Resource Economics, European Association of Environmental and Resource Economists, vol. 42(4), pages 551-574, April.
- Marco Avarucci & Domenico Marinucci, 2005.
"Polynomial Cointegration Among Stationary Processes With Long Memory,"
Economics Working Papers
we055123, Universidad Carlos III, Departamento de Economía.
- Avarucci, Marco & Marinucci, Domenico, . "Polynomial cointegration among stationary processes with long memory," Open Access publications from Universidad Carlos III de Madrid info:hdl:10016/351, Universidad Carlos III de Madrid.
- Heejoon Han & Dennis Kristensen, 2012.
"Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates,"
CREATES Research Papers
2012-25, School of Economics and Management, University of Aarhus.
- Heejoon Han & Dennis Kristensen, 2013. "Asymptotic theory for the QMLE in GARCH-X models with stationary and non-stationary covariates," CeMMAP working papers CWP18/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004.
"Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies,"
CIRANO Working Papers
- Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
- Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," NBER Working Papers 10914, National Bureau of Economic Research, Inc.
- 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.
- 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.
- 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.
- Azamo, Baudouin Tameze & Krämer, Walter, 2006. "Structural Change and long memory in the GARCH(1,1)-model," Technical Reports 2006,33, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- 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., . "Estimation of Fractional Integration in the Presence of Data Noise," Economics Working Papers 2003-10, School of Economics and Management, University of Aarhus.
- Gabriele La Spada & Fabrizio Lillo, 2011. "The effect of round-off error on long memory processes," Papers 1107.4476, arXiv.org, revised Mar 2013.
- Wang, Yudong & Wu, Chongfeng, 2012. "Long memory in energy futures markets: Further evidence," Resources Policy, Elsevier, vol. 37(3), pages 261-272.
- Høg, Espen P. & Frederiksen, Per H., 2006. "The Fractional Ornstein-Uhlenbeck Process: Term Structure Theory and Application," Finance Research Group Working Papers F-2006-01, University of Aarhus, Aarhus School of Business, Department of Business Studies.
- Dominique Guegan, 2005. "How can we define the concept of long memory ? An econometric survey," Post-Print halshs-00179343, HAL.
- Yoon, Gawon, 2005. "Long-memory property of nonlinear transformations of break processes," Economics Letters, Elsevier, vol. 87(3), pages 373-377, June.
- Esben Hoeg & Per Frederiksen, 2006. "The Fractional OU Process: Term Structure Theory and Application," Computing in Economics and Finance 2006 194, Society for Computational Economics.
- OOMEN, Roel C. A., 2003. "Three essays on the econometric analysis of high frequency financial data," Economics Dissertations urn:hdl:1814/5025, European University Institute.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics).
If references are entirely missing, you can add them using this form.