Are benefits from oil - stocks diversification gone? New evidence from a dynamic copula and high frequency data

TL;DR

This paper introduces a new empirical approach using high frequency data and dynamic copulas to assess the changing diversification benefits of oil stocks in stock portfolios, revealing a decline over the past decade.

Contribution

It develops a novel methodology combining generalized autoregressive score copula functions with high frequency data to accurately model and forecast oil-stock dependence.

Findings

Diversification benefits from oil stocks have decreased over the last ten years.

Dependence between oil and stocks is highly time-varying and nonlinear.

The empirical model outperforms competitors in forecasting joint distribution and tail risks.

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.