The Factor-Spline-GARCH Model for High- and Low-Frequency Correlations
Jose Gonzalo Rangel
Goldman Sachs Group, Inc. - Global Investment Research
Robert F. Engle
New York University - Leonard N. Stern School of Business - Department of Economics; National Bureau of Economic Research (NBER); New York University (NYU) - Department of Finance
January 31, 2011
Journal of Business and Economic Statistics, Vol. 30, No. 1, pp. 109-124, 2012
We propose a new approach to model high- and low-frequency components of equity correlations. Our framework combines a factor asset pricing structure with other specifications capturing dynamic properties of volatilities and covariances between a single common factor and idiosyncratic returns. High-frequency correlations mean revert to slowly varying functions that characterize long-term correlation patterns. We associate such term behavior with low-frequency economic variables, including determinants of market and idiosyncratic volatilities. Flexibility in the time-varying level of mean reversion improves both the empirical fit of equity correlations in the U.S. and correlation forecasts at long horizons.
Number of Pages in PDF File: 49
Keywords: Factor models, Dynamic correlation, Spline-GARCH, DCC, Idiosyncratic volatility, Time-varying betas, Long-term forecast evaluation.
JEL Classification: C32, C51, C53, G11, G12Accepted Paper Series
Date posted: February 7, 2011 ; Last revised: November 15, 2013
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