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Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility

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Author Info

  • ERIC HILLEBRAND

    ()
    (DEPARTMENT OF ECONOMICS, LOUISIANA STATE UNIVERSITY,)

  • MArcelo Cunha Medeiros

    (DEPARTMENT OF Economics, PUC-rio Author- mcm@econ.puc-rio.br)

Abstract

We study the simultaneous occurrence of long memory and nonlinear effects, such as structural breaks and thresholds, in autoregressive moving average (ARMA) time series models and apply our modeling framework to series of daily realized volatility. Asymptotic theory for the quasi-maximum likelihood estimator is developed and a sequence of model specification tests is described. Our framework allows for general nonlinear functions, including smoothly changing intercepts. The theoretical results in the paper can be applied to any series with long memory and nonlinearity. We apply the methodology to realized volatility of individual stocks of the Dow Jones Industrial Average during the period 1995 to 2005. We find strong evidence of nonlinear effects and explore different specifications of the model framework. A forecasting exercise demonstrates that allowing for nonlinearities in long memory models yields significant performance gains.

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Bibliographic Info

Paper provided by Department of Economics PUC-Rio (Brazil) in its series Textos para discussão with number 578.

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Length: 37p
Date of creation: Oct 2010
Date of revision:
Handle: RePEc:rio:texdis:578

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Keywords: Realized volatility; structural breaks; smooth transitions; nonlinear models; long memory; persistence.;

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Cited by:
  1. Manuabu Asai & Michael McAleer & Marcelo C. Medeiros, 2010. "Modelling and Forecasting Noisy Realized Volatility," Working Papers in Economics 10/21, University of Canterbury, Department of Economics and Finance.
  2. 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.
  3. Nima Nonejad, 2013. "Long Memory and Structural Breaks in Realized Volatility: An Irreversible Markov Switching Approach," CREATES Research Papers 2013-26, School of Economics and Management, University of Aarhus.

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