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Additive modeling of realized variance: tests for parametric specifications and structural breaks

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  • Fengler, Matthias R.

    ()

  • Mammen, Enno

    ()

  • Vogt, Michael

    ()

Abstract

For an additive autoregression model, we study two types of testing problems. First, a parametric specification of a component function is compared against a nonparametric fit. Second, two nonparametric fits of two different time periods are tested for equality. We apply the theory to a nonparametric extension of the linear heterogeneous autoregressive (HAR) model. The linear HAR model is widely employed to describe realized variance data. We find that the linearity assumption is often rejected, in particular on equity, fixed income, and currency futures data; in the presence of a structural break, nonlinearity appears to prevail on the sample before the outbreak of the financial crisis in mid-2007.

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File URL: http://www1.vwa.unisg.ch/RePEc/usg/econwp/EWP-1332.pdf
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Bibliographic Info

Paper provided by University of St. Gallen, School of Economics and Political Science in its series Economics Working Paper Series with number 1332.

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Length: 52 pages
Date of creation: Nov 2013
Date of revision:
Handle: RePEc:usg:econwp:2013:32

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Keywords: Additive models; Backfitting; Nonparametric time series analysis; Specification tests; Realized variance; Heterogeneous autoregressive model.;

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  1. Michael McAleer & Marcelo Cunha Medeiros, 2006. "Realized volatility: a review," Textos para discussão 531 Publication status: F, Department of Economics PUC-Rio (Brazil).
  2. Torben G. Andersen & Tim Bollerslev & Per Houmann Frederiksen & Morten Ørregaard Nielsen, 2007. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," CREATES Research Papers 2007-21, School of Economics and Management, University of Aarhus.
  3. Oliver Linton & Enno Mammen & N Nielsen, 2000. "The Existence and Asymptotic Properties of a Backfitting Projection Algorithm under Weak Conditions," STICERD - Econometrics Paper Series /2000/386, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  4. O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, vol. 12(3), pages C1-C32, November.
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  7. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2005. "Roughing it Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," NBER Working Papers 11775, National Bureau of Economic Research, Inc.
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  11. Audrino, Francesco & Knaus, Simon, 2012. "Lassoing the HAR model: A Model Selection Perspective on Realized Volatility Dynamics," Economics Working Paper Series 1224, University of St. Gallen, School of Economics and Political Science.
  12. Fulvio Corsi & Davide Pirino & Roberto Reno', 2010. "Threshold Bipower Variation and the Impact of Jumps on Volatility Forecasting," LEM Papers Series 2010/11, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  13. 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.
  14. W. González-Manteiga & R. Cao, 1993. "Testing the hypothesis of a general linear model using nonparametric regression estimation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 2(1), pages 161-188, December.
  15. Audrino, Francesco & Hu, Yujia, 2011. "Volatility Forecasting: Downside Risk, Jumps and Leverage Effect," Economics Working Paper Series 1138, University of St. Gallen, School of Economics and Political Science.
  16. Mihaela Craioveanu & Eric Hillebrand, 2012. "Why It Is Ok To Use The Har-Rv(1,5,21) Model," Working Papers 1201, University of Central Missouri, Department of Economics & Finance, revised Aug 2012.
  17. Berthold R. Haag, 2008. "Non-parametric Regression Tests Using Dimension Reduction Techniques," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics & Finnish Statistical Society & Norwegian Statistical Association & Swedish Statistical Association, vol. 35(4), pages 719-738.
  18. Michael McAller & Marcelo C. Medeiros, 2007. "A multiple regime smooth transition heterogeneous autoregressive model for long memory and asymmetries," Textos para discussão 544, Department of Economics PUC-Rio (Brazil).
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