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This paper aims to model the relationship between oil price and stock returns for selected sectors in Nigeria using monthly data from January 2007 to December 2016.

The authors use both the linear (symmetric) autoregressive distributed lag (ARDL) by Pesaran et al. (2001) and non-linear (asymmetric) ARDL by Shin et al. (2014), and they also account for structural breaks using the Bai and Perron (2003) test that allows for multiple structural changes in regression models.

The results indicate that the strength of this relationship varies across sectors, albeit asymmetric and breaks. The authors identify two structural breaks that occur in 2008 and 2010/2011, which coincidentally correspond to the global financial crisis and the Arab spring (Libyan shutdowns), respectively. Moreover, the authors observe strong support for asymmetry and structural breaks for some sectors in the reaction of sector returns to movement in oil prices. These findings are robust and insensitive when considering different oil proxies. While further extensions can be pursued, the consideration of asymmetric effects as well as structural breaks should not be jettisoned when modelling this nexus.

This study is one of the very few studies that have investigated the sectoral behaviour of stocks to oil price shocks, particularly in Nigeria. This paper contributes to the oil stock literature using the recent technique of asymmetry and also considering the role structural breaks play in the relationship between oil price and stock returns.

This paper aims to assess the relationship between oil price and inflation in the Organization for Economic Co-operation and Development (OECD) countries. This paper contributes to knowledge in a number of ways.

First, we carry out a comparative analysis between the developed and developing countries of the OECD. Second, we check if the global financial crisis (GFC) of 2008 altered the oil price–inflation relationship. We further extend our analysis to capture asymmetries using the non-linear autoregressive distributed lag model. Lastly, we use the Campbell and Thompson (2008) forecast evaluation test to comparatively assess the predictive ability of the symmetric (restricted) and asymmetric (unrestricted) models.

Our results show that asymmetries matter in the oil price–inflation nexus. Also, the effect of the GFC of 2008 is stronger for the developed countries in the short run, and the developing countries in the long run. Lastly, accounting for asymmetries in oil price yields a better forecast for inflation in both groups.

The paper adds some interesting innovations to the oil price–inflation relationship in the OECD countries. It is the study with the widest scope for such country group under two classifications of developed and developing countries. It also inculcates the role of asymmetries, financial crisis, as well as the predictive ability of oil price on inflation.