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Citations for "An empirical investigation of the usefulness of ARFIMA models for predicting macroeconomic and financial time series"

by Bhardwaj, Geetesh & Swanson, Norman R.

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  1. Slim Chaouachi & Zied Ftiti & Frederic Teulon, 2014. "Explaining the Tunisian Real Exchange: Long Memory versus Structural Breaks," Working Papers 2014-147, Department of Research, Ipag Business School.
  2. Florian Heinen & Philipp Sibbertsen & Robinson Kruse, 2009. "Forecasting long memory time series under a break in persistence," CREATES Research Papers 2009-53, Department of Economics and Business Economics, Aarhus University.
  3. Wolfgang Härdle & Julius Mungo, 2007. "Long Memory Persistence in the Factor of Implied Volatility Dynamics," SFB 649 Discussion Papers SFB649DP2007-027, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  4. Adnan Kasman & Erdost Torun, 2007. "Long Memory in the Turkish Stock Market Return and Volatility," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 7(2), pages 13-27.
  5. Rangan Gupta & Alain Kabundi & Stephen M. Miller & Josine Uwilingiye, 2011. "Using Large Data Sets to Forecast Sectoral Employment," Working papers 2011-02, University of Connecticut, Department of Economics, revised Aug 2012.
  6. Goodness C. Aye & Mehmet Balcilar & Rangan Gupta & Nicholas Kilimani & Amandine Nakumuryango & Siobhan Redford, 2012. "Predicting BRICS Stock Returns Using ARFIMA Models," Working Papers 201235, University of Pretoria, Department of Economics.
  7. 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.
  8. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2011. "Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes," Working Papers 1103, University of Nevada, Las Vegas , Department of Economics.
  9. Papailias, Fotis & Fruet Dias, Gustavo, 2015. "Forecasting long memory series subject to structural change: A two-stage approach," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1056-1066.
  10. Rangan Gupta & Alan Kabundi & Stephen M. Miller, 2010. "Forecasting the US Real House Price Index: Structural and Non-Structural Models with and without Fundamentals," Working Papers 1001, University of Nevada, Las Vegas , Department of Economics.
  11. Lahiani, A. & Scaillet, O., 2009. "Testing for threshold effect in ARFIMA models: Application to US unemployment rate data," International Journal of Forecasting, Elsevier, vol. 25(2), pages 418-428.
  12. Bisaglia, Luisa & Gerolimetto, Margherita, 2008. "Forecasting long memory time series when occasional breaks occur," Economics Letters, Elsevier, vol. 98(3), pages 253-258, March.
  13. Quoreshi, Shahiduzzaman, 2006. "LongMemory, Count Data, Time Series Modelling for Financial Application," Umeå Economic Studies 673, Umeå University, Department of Economics.
  14. Monticini, Andrea & Ravazzolo, Francesco, 2014. "Forecasting the intraday market price of money," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 304-315.
  15. Fernandes, Marcelo & Medeiros, Marcelo C. & Scharth, Marcel, 2014. "Modeling and predicting the CBOE market volatility index," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 1-10.
  16. Mohamed Boutahar & Gilles Dufrénot & Anne Peguin-Feissolle, 2008. "A simple fractionally integrated model with a time-varying long memory parameter dt," Post-Print halshs-00390136, HAL.
  17. Arouri, Mohamed El Hedi & Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong, 2012. "Long memory and structural breaks in modeling the return and volatility dynamics of precious metals," The Quarterly Review of Economics and Finance, Elsevier, vol. 52(2), pages 207-218.
  18. Axel Groß‐KlußMann & Nikolaus Hautsch, 2013. "Predicting Bid–Ask Spreads Using Long‐Memory Autoregressive Conditional Poisson Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(8), pages 724-742, December.
  19. repec:ctc:serie1:def10 is not listed on IDEAS
  20. Gilles Dufrenot & Dominique Guegan & Anne Peguin-Feissolle, 2008. "Changing-regime volatility: A fractionally integrated SETAR model," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00185369, HAL.
  21. Quoreshi, A.M.M. Shahiduzzaman, 2014. "Bivariate Integer-Valued Long Memory Model for High Frequency Financial Count Data," CITR Working Paper Series 2014/03, Center for Innovation and Technology Research, Blekinge Institute of Technology.
  22. repec:hal:journl:halshs-00185369 is not listed on IDEAS
  23. Roger Bowden & Jennifer Zhu, 2010. "Multi-scale variation, path risk and long-term portfolio management," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 783-796.
  24. Rangan Gupta & Rudi Steinbach, 2010. "Forecasting Key Macroeconomic Variables of the South African Economy: A Small Open Economy New Keynesian DSGE-VAR Model," Working Papers 201019, University of Pretoria, Department of Economics.
  25. Choi, Kyongwook & Zivot, Eric, 2007. "Long memory and structural changes in the forward discount: An empirical investigation," Journal of International Money and Finance, Elsevier, vol. 26(3), pages 342-363, April.
  26. Katsumi Shimotsu, 2006. "Simple (but effective) tests of long memory versus structural breaks," Working Papers 1101, Queen's University, Department of Economics.
  27. Kasai, Ndahiriwe & Naraidoo, Ruthira, 2011. "Evaluating the forecasting performance of linear and nonlinear monetary policy rules for South Africa," MPRA Paper 40699, University Library of Munich, Germany.
  28. Quoreshi, Shahiduzzaman, 2006. "Time Series Modelling Of High Frequency Stock Transaction Data," Umeå Economic Studies 675, Umeå University, Department of Economics.
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