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Forecasting realized volatility models:the benefits of bagging and nonlinear specifications

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  • Eric Hillebrand

    ()
    (DEPARTMENT OF ECONOMICS, LOUISIANA STATE UNIVERSITY)

  • Marcelo Cunha Medeiros

    ()
    (Department of Economics, PUC-Rio)

Abstract

We forecast daily realized volatilities with linear and nonlinear models and evaluate the benefits of bootstrap aggregation (bagging) in producing more precise forecasts. We consider the linear autoregressive (AR) model, the Heterogeneous Autoregressive model (HAR), and a non-linear HAR model based on a neural network specification that allows for logistic transition effects (NNHAR). The models and the bagging schemes are applied to the realized volatility time series of the S&P500 index from 3-Jan-2000 through 30-Dec-2005. Our main findings are: (1) For the HAR model, bagging successfully averages over the randomness of variable selection; however, when the NN model is considered, there is no clear benefit from using bagging; (2) including past returns in the models improves the forecast precision; and (3) the NNHAR model outperforms the linear alternatives.

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Bibliographic Info

Paper provided by Department of Economics PUC-Rio (Brazil) in its series Textos para discussão with number 547.

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Length: 30p
Date of creation: Aug 2007
Date of revision:
Handle: RePEc:rio:texdis:547

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Cited by:
  1. David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," KIER Working Papers 753, Kyoto University, Institute of Economic Research.
  2. Francesco Audrino & Marcelo Cunha Medeiros, 2010. "Modeling and Forecasting Short-term Interest Rates: The Benefits of Smooth Regimes, Macroeconomic Variables, and Bagging," Textos para discussão 570, Department of Economics PUC-Rio (Brazil).
  3. Erik Hillebrand & Tae-Hwy Lee & Marcelo Cunha Medeiros, 2012. "Let´s do it again: bagging equity premium predictors," Textos para discussão 604, Department of Economics PUC-Rio (Brazil).
  4. Francesco Audrino & Marcelo C. Medeiros, 2008. "Smooth Regimes, Macroeconomic Variables, and Bagging for the Short-Term Interest Rate Process," University of St. Gallen Department of Economics working paper series 2008 2008-16, Department of Economics, University of St. Gallen.

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