Additive modeling of realized variance: tests for parametric specifications and structural breaks
AbstractFor 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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Bibliographic InfoPaper provided by University of St. Gallen, School of Economics and Political Science in its series Economics Working Paper Series with number 1332.
Length: 52 pages
Date of creation: Nov 2013
Date of revision:
Additive models; Backfitting; Nonparametric time series analysis; Specification tests; Realized variance; Heterogeneous autoregressive model.;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-11-16 (All new papers)
- NEP-ECM-2013-11-16 (Econometrics)
- NEP-ETS-2013-11-16 (Econometric Time Series)
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