Which Parametric Model for Conditional Skewness?
AbstractThis paper addresses an existing gap in the developing literature on conditional skewness. We develop a simple procedure to evaluate parametric conditional skewness models. This procedure is based on regressing the realized skewness measures on model-implied conditional skewness values. We find that an asymmetric GARCH-type specification on shape parameters with a skewed generalized error distribution provides the best in-sample fit for the data, as well as reasonable predictions of the realized skewness measure. Our empirical findings imply significant asymmetry with respect to positive and negative news in both conditional asymmetry and kurtosis processes.
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Bibliographic InfoPaper provided by Bank of Canada in its series Working Papers with number 13-32.
Length: 44 pages
Date of creation: 2013
Date of revision:
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Econometric and statistical methods;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-09-28 (All new papers)
- NEP-ECM-2013-09-28 (Econometrics)
- NEP-FOR-2013-09-28 (Forecasting)
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