Oil price shocks and sectoral stocks in Nigeria: how relevant are asymmetry and structural breaks?

Purpose This paper aims to model the relationship between oil price and six major agricultural commodity prices using monthly data from January 1997 to December 2016. Design/methodology/approach The authors use both the linear autoregressive distributed lag by Pesaran et al. (2001) and the nonlinear autoregressive distributed lag 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. Findings These findings are discernible from the authors’ analyses. First, the linear analysis indicates a significant positive effect of oil prices on the agricultural commodity prices, which supports evidence on the non-neutrality hypothesis. Second, oil price asymmetries seem to matter more when dealing with agricultural commodity prices, except for groundnut. Third, it may be necessary to pre-test for structural breaks when modelling the relationship between oil price and agricultural prices regardless of the commodity being analysed. Fourth, the asymmetric effect for the agricultural commodity prices is non-neutral to oil prices, except for rice in the case of structural breaks. Originality/value This paper contributes to the on-going debate on the oil–agricultural commodity nexus using the recent technique of asymmetry and also considering the role structural breaks play in the relationship between oil price and agricultural commodity prices.

This special issue deals with problems related to unit roots and structural change, and the interplay between the two.[...]

This paper uses monthly data from 2000:05 to 2016:11 to investigate the relationship between oil price shocks and stock market returns of the nine economic sectors listed on Bursa Malaysia while incorporating oil price, interest rate, exchange rate, industrial production, and inflation into the regression. In order to avoid issue arising from the presence of the structural breaks, Narayan and Popp (J Appl Stat 37(9):1425–1438, 2010) unit root and autoregressive distributed lag (ARDL) with structural breaks were utilized. The ARDL bounds test results illustrate that all the sectors are cointegrated except trading/services and plantation sectors. The results further show that oil price has a significant negative impact on the property, mining, and technology sectors stock market returns.

It has been stated that the activities of the commercial banks on the Nigerian stock market exposed the economy to global economic crisis. This view is premised on the huge and disproportionate investment of the Nigerian commercial banks in the oil and gas sector, which was directly affected by the recession between 2007 and 2009. With falling oil price and asset value of the banks, the resulting mismatch in the balance sheets of these banks resulted in financial and economic crisis. The Central Bank of Nigeria (CBN) consequently responded by reconsolidating banking sector for effective monitoring. This study then examines the impact of global risk exposure on Nigerian economy by focusing on the connection between oil price and stock market activity. The study employs the method of Granger causality in risk. This method is used to infer the predictive information in risk of one variable from another. It makes use of the sample cross-correlation function (CCF) of the binary indicators for value at risk (VaR). The study successfully implements the method for the relationship between oil price and stock returns for Nigeria. This study uses daily data over the period January 2, 2003 through December 31, 2013. To clean the data of the holiday effects of daily data, we apply the Gallant-Rossi-Tauchen filter. The data were then transformed to obtain their daily returns by computing the first difference of their natural logarithm in percentage. The study finds that oil price return causes stock returns in extreme risk. This phenomenon is found absent prior to January 1, 2007 but present in the sub-sample between January, 2007 and December, 2013. The results indicate that the sudden and unprecedented fall in crude oil price during the global recession between 2007 and 2009 undermined the balance sheets of banks in Nigeria. The study further finds that the market participants not only care about the changes in the oil price and stock index but also in the rate of change in them. The study indicates the need to consolidate the financial sector for effective monitoring and to reduce the exposure to global risk in particular to oil price movement. The study suggests that the policymakers must avail themselves necessary forecasting tools to gauge the immediate and differed spillovers between the stock and the oil markets, and that the current bank consolidation policy should be made more effective to enhance monitoring.

Do exchange rate and inflation rate matter in the cyclicality of oil price and stock returns?

This paper employs the linear autoregressive distributed lag (ARDL) model, the asymmetric nonlinear ARDL (NARDL) model developed by Shin, et al (2014) to examine the asymmetric effect of oil price and exchange rates pass-through on inflation in Nigeria over a period of 1970 to 2020. The result of the asymmetric test revealed the existence of asymmetries among the variables of the study, suggesting that there is a nonlinear interaction among the variables used in the study. This validates the choice of a non-linear ARDL model for the study. Results of the long-run estimates show that rising (Positive) oil price shocks have a greater impact on inflation than falling (negative) oil price shocks. Furthermore, it is evident from the result that the depreciation of the exchange rate has a much and significant effect on inflation than the appreciation of the exchange rate in Nigeria. However, a rising interest rate increases inflation by 0.84 per cent while a falling interest rate increases inflation by 0.85 per cent. This implies that the effect of negative interest rate on inflation is higher than its positive effect on inflation, though, by a smaller amount of about 0.01 per cent. Again, the short-run dynamic model revealed a high speed of convergence of more than 90% from the short-run disequilibrium. During the study period, the oil price fluctuations showed a significant and incomplete pass-through to both exchange rates and inflation in Nigeria. Moreover, the results suggest that positive oil price changes have a larger impact than the negative ones, that the effect of an oil price shock on inflation and exchange rates is larger in the long-run than in the short-run, and that there is incomplete pass-through effect of oil price on domestic inflation and exchange rates. Based on the findings, the study recommends policies that set oil prices and exchange rates within reasonable limits to check inflation in Nigeria and should diversify its economy as well as withdraw the current subsidy regime completely.

This study investigates the asymmetric impact of oil price shocks and COVID-19 total deaths on Kenya, Morocco, Nigeria and South Africa stock market returns. To achieve this objective employing weekly time series data from March 13, 2020 to September 23, 2022, first, we apply the BDS test which confirm the nonlinearity of each series. Second, stationarity tests are used to investigate each series for unit root. The results show that series are stationary in level and in first difference. Third, the bounds test reveals that the series have a cointegration relationship and we apply the nonlinear autoregressive distributed lag (ARDL) ARDL framework to decompose oil price into positive and negative partial sum to investigate a possible asymmetric effect of oil price on stock market returns. The main findings of the asymmetric ARDL model reveal that, in the short-run dynamic, a positive shock in the oil price have a negative and positive effect on stock market returns in Morocco and South Africa respectively. The result is insignificant for Kenya and Nigeria. A negative shock in the oil price have a negative effect on the stock returns in Nigeria, South Africa and in Kenya, Morocco with one period lag. Furthermore, in the long-run, a positive shock in oil price exerts a negative effect on the stock market performance in Morocco and Nigeria while a negative shock in oil price leads to a negative effect also on the stock market returns. The total deaths present a counterintuitive result. Both in the long-run and short-run dynamic, the total number of deaths due to COVID-19 have a significant increasing effect on stock market returns in Kenya, Morocco and South Africa except for Nigeria.

The aim of this paper is an examination of the co-movement between OPEC oil price and Tehran Exchange Market returns. To analyze the relationship between two variables, applied the wavelet coherence approach and utilized daily data during 2009-2020. According to the wavelet approach, a dynamic causal relationship between oil price and the stock market return provides for the causality between the two variables and the type of causal relationship in the time-frequency analysis. Findings showed there is a positive correlation between oil price and stock market earnings. Comparison of the data in annual time-frequency scale indicated that the oil price and stock market returns are in phase from 2009 to 2011, and observed a positive relationship between them. From late 2011 to mid- 2015, both variables are in phase, and oil prices are the leading factor in the stock market. During the period 2015 to 2021, both variables are in phase, but co-movements of oil price and stock market returns not observed. The non-causal effect of oil price on stock market earnings at some times does not mean that oil prices do not affect the stock market. As mentioned, in most periods, oil price and stock market profits are in phase. Factors such as imposing economic sanctions on Iran such as oil sanctions, fluctuations in the value of the dollar, volatilities in oil prices, changes in global demand for exports and imports from Iran, privatization, increasing the gap between the official and the market exchange rate, financial markets shocks, Middle East price tensions and the financing process affected the relationship between the stock market and oil price.

Oil price shock can impose detrimental effects to an economy. In this study, we empirically study the spillover effects of oil price shock on determining volatilities of stock markets across the main oil importing and oil producing countries. In particular, we are interested to compare the relative impact of oil price shock on the volatilities of stock markets and how each stock market reacts to oil price shock for oil importing and oil producing countries. We focus the study in four main oil importer and four oil producers respectively using the daily data starting from January 2009 to December 2013. The multivariate GARCH(1,1) model is applied for the purpose of this study. The results of the study suggest that there exist spillover effect between crude oil price and stock returns for all the countries. The short run persistency of spillover effect in oil-exporting countries is lower than oil-importing countries but the long run persistency of spillover effect in oil-exporting countries is higher than oil-importing countries. In general the short run persistency is smaller and the long run persistency is very high. The results hold for volatility of oil price and stock returns and also spillover volatility in all countries.

This study aims to analyse the behaviour of crude oil prices and to determine the dynamic relationships between domestic crude oil prices and fundamental macroeconomic variables in Libya and Nigeria. The analysis in this study involves two stages. The first stage is to analyse and model oil price returns of the Libyan, Nigerian and OPEC markets. Unlike previous studies, this study examines the existence of a structural break in crude oil prices data. The empirical analysis uses the AR-GARCH, AR-EGARCH, AR-GJR-GARCH, AR-APARCH, AR-CGARCH and AR-ACGARCH models for modelling the conditional mean and conditional variance of the oil prices returns under three error distributions, namely the normal distribution, student-t distribution and generalized error distribution. The results show that the three return series exhibit no structural break in the mean and variance equations but we find evidence of volatility clustering and leverage effect response to good and bad news in the asymmetric models in the three markets. We also assess the out-of-sample forecasts of the class of GARCH models by using four loss functions. The results indicate that the AR-CGARCH-GED model is the best model for forecasting oil returns in Libya, whilst the best models for Nigeria and OPEC are the AR-GARCH-GED and AR-EGARCH-t models, respectively. The second stage is to examine the dynamic relationship between oil prices and GDP, exchange rate and inflation using annual data for the 1970-2017 periods in Libya and Nigeria. Both short-run and long-run relationships between these variables are explored by applying cointegration tests, the vector autoregressive model (VAR), and vector error correction (VECM) model, Granger causality tests, impulse response functions and forecast variance decompositions. The results show that there is a cointegrating relationship between domestic oil prices and macroeconomic variables in both Libya and Nigeria. Furthermore, the results show that there is a unidirectional Granger-causality relationship running from Libyan oil prices to Libya's GDP. Moreover, the results show a unidirectional causality running from Nigerian oil prices to GDP and exchange rate in Nigeria. The findings of the impulse response functions suggest significant impacts of domestic oil prices shocks on the macroeconomic variables in Libya and Nigeria in the short and long term. The results of the variance decompositions analysis indicate that the changes in Libyan oil prices can impact Libyan GDP. While, Nigerian oil price shocks could affect most of macroeconomic variables in Nigeria. The main policy implications from these findings are that policymakers should monitor and predict future oil prices and take these expectations into account when adopting a particular monetary policy.

The link between crude oil price and stock returns of the Group of Seven (G7) countries (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) was analyzed in this study using monthly data from January 1999 to March 2020. We adopt a similar approach to Kilian (Am Econ Rev 99(3):1053–1069, 2009) and construct a structural vector autoregression framework to decompose crude oil price shocks into oil supply shock, oil aggregate demand shock, and oil-specific demand shock. We then explore the distinct effects of different kinds of oil price shocks from various sources.Based on the decomposed oil price shocks, we apply the connectedness approach and QQ regression to find time-varying co-movements and tail dependence between oil price shocks and G7 stock returns.There is no general correlation between the decomposed oil prices and stock returns in these countries. The effects of oil price shocks on stock returns across different stock market conditions appear to be heterogeneous. Oil supply shock appears to be a net transmitter of spillover effects for all G7 countries within the sample period.

The paper examines the dependence between global crude oil price and stock indices in economies of fast emerging Asian nations, which are also termed to be major oil consumers. The paper employs quantile regression method (QRM) to analyse the relationship by using monthly data from April 2004 to April 2017. Since ordinary least squares (OLS) method estimates from data suffering from structural breaks, non-normality conditions and heterogeneous distribution may be biased and not much favourable, quantile regression method termed to a robust method is adopted to analyse the same. The analysis revealed the asymmetric effects of dependence between crude oil price and stock index returns. The observed positive relation between the given variables was quite contrary to the usual presumption of inverse relation relationship existing for the oil importing nations. The degree of significance for the positive dependence between the crude oil price and stock index returns also varied across the quantiles for economies under study.

Oil price and stock returns of consumers and producers of crude oil

The asymmetric effects of oil price changes on unemployment: Evidence from Canada and the U.S

Oil price and stock market behaviour in GCC countries: Do asymmetries and structural breaks matter?