Modeling oil price–US stock nexus: A VARMA–BEKK–AGARCH approach

By Afees A. Salisu, Tirimisiyu F. Oloko. 2015

202 citations recorded by the source corpus.

This study adds to the existing literature on oil price–US stock nexus in three ways. First, it employs the VARMA–AGARCH model developed by McAleer et al. (2009) within the context of BEKK framework using West Texas Intermediate (WTI) and Brent as proxies for oil market and S&P stocks as a proxy for US stock market. Secondly, it modifies the model to include endogenously determined structural break using the general structure for analyzing breaks with unit roots in Perron (2006). Third, it uses the adopted model to compute optimal portfolio weight and hedge ratios between oil price and US stocks using different sample data based on the break date. On average, our empirical evidence suggests a significant positive return spillover from US stock market to oil market and bi-directional shock spillovers between the two markets. In addition, there is significant own asymmetric shock effect in both markets while volatility spillover from oil market to stock market became pronounced after the break which coincides with the period of global economic slowdown. Similarly, the results of portfolio management differ across the sample data. More importantly, we find that ignoring structural break when it exists may exaggerate hedging effectiveness.

Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/3cbe5e129051f1f2be54d78042348bfa2a279e21

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Citations in the corpus

Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets (2017, background): “1 Many studies have researched the oil–stock nexus (e.g. Hammoudeh et al., 2004; Filis et al., 2011; Arouri et al., 2012; Sadorsky, 2012, 2014; Mensi et al., 2014; Salisu and Oloko, 2015) and the gold–stock nexus (e.g. Baur and McDermott, 2010; Hood and Malik, 2013; Arouri et al., 2015).”
Modelling oil price-inflation nexus: The role of asymmetries (2017, methodology): “Ignoring these breaks when they exist may bias regression results [see Salisu and Oloko, 2015]. The breaks are determined endogenously using the Bai-Perron (2003) test which allows”