Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/108898
Authors: 
Avdulaj, Krenar
Barunik, Jozef
Year of Publication: 
2015
Series/Report no.: 
FinMaP-Working Paper 32
Abstract: 
Oil is perceived as a good diversification tool for stock markets. To fully understand this potential, we propose a new empirical methodology that combines generalized autoregressive score copula functions with high frequency data and allows us to capture and forecast the conditional time-varying joint distribution of the oil-stocks pair accurately. Our realized GARCH with time-varying copula yields statistically better forecasts of the dependence and quantiles of the distribution relative to competing models. Employing a recently proposed conditional diversification benefits measure that considers higher-order moments and nonlinear dependence from tail events, we document decreasing benefits from diversification over the past ten years. The diversification benefits implied by our empirical model are, moreover, strongly varied over time. These findings have important implications for asset allocation, as the benefits of including oil in stock portfolios may not be as large as perceived.
Subjects: 
portfolio diversification
dynamic correlations
high frequency data time-varying copulas
commodities
JEL: 
C14
C32
C51
F37
G11
Document Type: 
Working Paper
Appears in Collections:

Files in This Item:
File
Size
815.15 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.