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Simple diagnostic procedures for modeling financial time series

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  • Palm, Franz C.

    (Maastricht University)

  • Vlaar, Peter J.G.

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Bibliographic Info

Paper provided by Maastricht University in its series Open Access publications from Maastricht University with number urn:nbn:nl:ui:27-5772.

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Date of creation: 1997
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Publication status: Published in Allgemeines statistisches Archiv : Organ der Deutschen Statistischen Gesellschaft (1997) v.81, p.85-101
Handle: RePEc:ner:maastr:urn:nbn:nl:ui:27-5772

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Web page: http://www.maastrichtuniversity.nl/web/Home.htm

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Cited by:
  1. 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.
  2. Markus Haas & Stefan Mittnik & Bruce Mizrach, 2004. "Assessing Central Bank Credibility During the EMS Crises: Comparing Option and Spot Market-Based Forecasts," Departmental Working Papers 200424, Rutgers University, Department of Economics.
  3. Cifter, Atilla & Ozun, Alper, 2007. "The Predictive Performance of Asymmetric Normal Mixture GARCH in Risk Management: Evidence from Turkey," MPRA Paper 2489, University Library of Munich, Germany.
  4. Markku Lanne, 2006. "A Mixture Multiplicative Error Model for Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(4), pages 594-616.
  5. Yin-Wong Cheung & Sang-Kuck Chung, 2011. "A Long Memory Model with Normal Mixture GARCH," Computational Economics, Society for Computational Economics, vol. 38(4), pages 517-539, November.
  6. Cheung, Yin-Wong & Chung, Sang-Kuck, 2009. "A Long Memory Model with Mixed Normal GARCH for US Inflation Data," Santa Cruz Department of Economics, Working Paper Series qt94r403d2, Department of Economics, UC Santa Cruz.
  7. Mohammadi, Hassan & Su, Lixian, 2010. "International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models," Energy Economics, Elsevier, vol. 32(5), pages 1001-1008, September.
  8. Dinghai Xu, 2009. "The Applications of Mixtures of Normal Distributions in Empirical Finance: A Selected Survey," Working Papers 0904, University of Waterloo, Department of Economics, revised Sep 2009.
  9. Bertholon, H. & Monfort, A. & Pegoraro, F., 2007. "Pricing and Inference with Mixtures of Conditionally Normal Processes," Working papers 188, Banque de France.
  10. Nomikos, Nikos K. & Pouliasis, Panos K., 2011. "Forecasting petroleum futures markets volatility: The role of regimes and market conditions," Energy Economics, Elsevier, vol. 33(2), pages 321-337, March.
  11. Philip Kostov & Ziping Wu & Seamus McErlean, 2004. "Do Chinese stock markets share common information arrival processes?," Econometrics 0410001, EconWPA.
  12. Markus Haas & Stefan Mittnik & Marc Paolella, 2006. "Modelling and predicting market risk with Laplace-Gaussian mixture distributions," Applied Financial Economics, Taylor and Francis Journals, vol. 16(15), pages 1145-1162.
  13. Christelle Lecourt, 2000. "Dépendance de court et de long terme des rendements de taux de change," Économie et Prévision, Programme National Persée, vol. 146(5), pages 127-137.

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