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This study presents evidence of a statistically significant negative correlation between crude oil and equities over the past 20 years. Including proper proportions of negatively correlated assets in a diversified portfolio can improve the ratio of reward relative to risk, and therefore, adding crude oil with equities into a diversified portfolio can provide superior portfolio performance, compared with equities alone. Because crude oil prices held stable for nearly a century before the oil crisis of 1973, and oil derivatives did not begin trading actively on public markets until the 1980s, the diversification value of oil is a relatively new phenomenon. Also contributing to the phenomenon, the majority of oil reserves and the majority of crude oil production capacity worldwide are held by entities that are not traded in public equity markets, and therefore, the diversification benefits of oil cannot be fully realized by holding a portion of the global market portfolio of equities.

Purpose – Study the investment and risk management approach of sovereign wealth funds when national wealth including natural resources is accounted for rather than only financial asset.

Methodology/Approach – Using a range of widely used asset classes, we simulate sovereign wealth fund returns when considering only financial assets but also under varying levels of national wealth holdings in oil. We optimize two-asset financial portfolios and three-asset portfolios when including oil to maximize the risk-adjusted returns.

Findings – Sovereign wealth funds by failing to invest for the national wealth portfolio are overlooking a major source of volatility. To reduce the level of volatility associated with yearly national wealth returns, allocating a higher percentage of fixed assets to high-quality fixed income and low-risk equities will maximize the risk-adjusted returns of national wealth for sovereign wealth fund states.

Social implications – By focusing solely on the financial assets managed by sovereign wealth funds, states are exposing themselves to significant national wealth risk.

Originality/Value of the paper – This is the first work to estimate the impact on national wealth of oil-dependent states by failing to account for volatile commodity prices through the investment strategies of sovereign wealth funds.

This study aims to investigate the response of green investments of emerging countries to own-market uncertainty, oil-market uncertainty and COVID-19 effect/geo-political risks (GPRs), using the tail risks of corresponding markets as measures of uncertainty.

This study employs Westerlund and Narayan (2015) (WN)-type distributed lag model that simultaneously accounts for persistence, endogeneity and conditional heteroscedasticity, within a single model framework. The tail risks are obtained using conditional standard deviation of the residuals from an asymmetric autoregressive moving average – ARMA(1,1) – generalized autoregressive conditional heteroscedasticity – GARCH(1,1) model framework with Gaussian innovation. For out-of-sample forecast evaluation, the study employs root mean square error (RMSE), and Clark and West (2007) (CW) test for pairwise comparison of nested models, under three forecast horizons; providing statistical justification for incorporating oil tail risks and COVID-19 effects or GPRs in the predictive model.

Green returns responds significantly to own-market uncertainty (mostly positively), oil-market uncertainty (mostly positively) as well as the COVID-19 effect (mostly negatively), with some evidence of hedging potential against uncertainties that are external to the green investments market. Also, incorporating external uncertainties improves the in-sample predictability and out-of-sample forecasts, and yields some economic gains.

This study contributes originally to the green market-uncertainty literature in four ways. First, it generates daily tail risks (a more realistic measure of uncertainty) for emerging countries’ green returns and global oil prices. Second, it employs WN-type distributed lag model that is well suited to account for conditional heteroscedasticity, endogeneity and persistence effects; which characterizes financial series. Third, it presents both in-sample predictability and out-of-sample forecast performances. Fourth, it provides the economic gains of incorporating own-market, oil-market and COVID-19 uncertainty.

This study aims to investigate the relationship between oil prices and stock returns of renewable energy firms in India under different market conditions.

The authors use the panel quantile framework with Fama–French–Carhart’s (1997) four-factor asset pricing model. All renewable energy firms listed in the National Stock Exchange of India are considered in this study. Three oil prices, such as West Texas Intermediate spot price, Europe Brent oil price and Indian basket oil price, are used in the regression. The analysis is done for the whole sample and its subgroups.

In the whole sample, stock returns of renewable energy firms respond positively to oil price changes in extreme market conditions only. In the subgroups of the renewable energy firms, the relationship between stock returns and oil price is positive and more robust in higher quantiles across all subgroup firms.

The contribution of the study is explained as follows. First, this study helps to explore the relationship between oil and stock returns of the renewable energy sector under different market conditions in the Indian context. Second, existing studies explore the effect of oil prices on stock returns of the renewable energy sector at the industry level, and most of the studies are in developed countries. To the best of the authors’ knowledge, this is the first study in the context of India. Third, this is a firm-level study

The purpose of this paper is to empirically investigate the volatility spillover between the Chinese stock market, investor’s sentiment and oil market, specifically during the 2014‒2016 turmoil period.

This study used the daily and monthly China market price index, oil-price index and composite index of Chinese investor’s sentiment. The authors first use the DCC GARCH model in order to study the correlation between variables. Second, the authors use a continuous wavelet decomposition technique so as to capture both time- and frequency-varying features of co-movement variables. Finally, the authors examine the spillover effects by estimating the BEKK GARCH model.

The wavelet coherency results indicate a substantial co-movement between oil and Chinese stock markets in the periods of high volatility. BEKK GARCH model outcomes confirm this relation and report the noteworthy bidirectional transmission of volatility between oil market shocks and the Chinese investor’s sentiment, chiefly in the crisis period. These results support the behavioral theory of contagion and highlight that the Chinese investor’s sentiment is a channel through which shocks are transmitted between the oil and Chinese equity markets. Thus, these results are important for Chinese authorities that should monitor the investor’s sentiment to better control the interaction between financial and real markets.

This study makes three major contributions to the existing literature. First, it pays attention to the recent 2015 Chinese stock market bumble. Second, it has gone some way toward enhancing our understanding of the volatility spillover between the investor’s sentiment, investor’s sentiment variation, oil prices and stock market returns (variables of interest) during oil and stock market crises. Third, it uses the continuous wavelet decomposition technique since it reveals the linkage between variables of interest at different time horizons.

The purpose of this paper is to examine whether oil price risk is a significant determinant of stock returns.

Using monthly data on a sample of Islamic stocks listed on the New York Stock Exchanges and National Association of Securities Dealers Automated Quotations System (NASDAQ) over the period from January 1990 to December 2017, the study examines whether oil price risk is a significant determinant of stock returns using Fama–French–Carhart’s four-factor asset pricing model amplified with Brent oil price factor.

The results from the cross-sectional regression analysis indicate that the extent of the exposure is significantly positive using a full sample period. Moreover, results from size and momentum factors are highly significant whereas book-to-market has no significant impact on Islamic stock returns.

The results support the concept for diversification in equity investment and are thus important for investors, analysts and policymakers.

This study is the first of its kind to establish whether oil price risk is a factor that can determine returns of Islamic listed stocks using the most developed stock market in the world (New York Stock Exchanges and NASDAQ).

This paper aims to investigate how the relation between stock returns of US firms and West Texas Intermediate (WTI) oil prices is affected by leverage from 1990 to 2020.

This paper examines how the relationship between stock returns of US firms and WTI oil prices is affected by leverage from 1990 to 2020 using a fixed-effect model estimation framework.

Results from the fixed-effect regression models suggest that leverage effects on stock returns are pervasive both in aggregate and cross-industry levels, while the mining industry is more sensitive. In addition to the positive oil price effects attenuated by leverage at the aggregate level, the authors observe stronger marginal effects of leverage only for the mining sector. Being more exposed to commodity prices, the positive effects of oil prices on stock returns in the mining sector are offset by large debt ratios. Asymmetries, effects of debt maturity structure and implications are also discussed.

This study is grounded on the contemporary cash flow claim of leverage NOT on the long-run effect of leverage considering cash flow constraints. The oil price increase is assumed to represent an advancement of the overall economy. This study does not capture the oil prices response to some other economic forces and vice-versa.

Mining companies should therefore reduce the stock of debt with respect to their assets to make possible the “pass-through” from oil prices to the stock market.

Previously undocumented and the authors show that leverage reduces the total effect of oil prices on stock returns, consistent with the hypothesis. Asymmetric and debt maturity structures effects are also discussed.

This chapter examines the dynamic linkages between the returns of Bitcoin, gold, and oil by using daily closing price data between July 17, 2010 and January 8, 2021. This study applies the diagonal BEKK–GARCH model for the purpose of analyzing a volatility spillover of variables in positive or negative ways. The empirical results show that the lagged returns inversely affect their current returns in oil. Based on the return spillovers between Bitcoin and gold, the empirical results indicate a unidirectional return spillover from Bitcoin to gold. Moreover, the authors found a unidirectional return transmission is observed from oil to Bitcoin, implying that oil returns are useful in forecasting Bitcoin returns. These findings are not only valuable for understanding of the interrelationships between the returns of Bitcoin, gold, and oil, but they are also of great interest to portfolio managers, investors, and investment funds that are actively dealing in Bitcoin, gold, and oil.

This study examined the impact of; COVID-19 investor sentiment, COVID-19 cases, geopolitical risk (GPR), economic policy uncertainty (EPU), oil returns and Islamic banking on bank stock returns. In addition, it examined whether Islamic bank stock returns differed from conventional banks when interacting with selected variables.

This study consisted of 137 conventional and Islamic stock market listed banks in 16 Middle East and North Africa (MENA) countries from February 2020 to July 2021. Monthly data were used for bank stock returns, number of COVID-19 cases, COVID-19 investor sentiment, oil price and EPU, while GPR data were obtained annually. This paper used unconditional quantile regression (UQR) in its analysis.

COVID-19 investor sentiment and EPU negatively influenced bank stock returns. However, oil returns were only positive and significant in first quantile. Conversely, GPR negatively impacted bank returns up to the median quantile, while the impact was positive in upper quantiles. Islamic banks outperformed conventional banks in all quantiles. Additionally, GPR negatively influenced Islamic bank returns up to 75th quantile, while oil returns negatively impacted Islamic bank returns up to 95th quantile. Ultimately, COVID-19 investor sentiment and EPU positively influenced Islamic bank returns up to 95th quantile.

Market conditions must be considered when implementing investment decisions and policies, as the effects of market shocks are mostly asymmetrical. For example, it is important for international investors to take into consideration asymmetric factors, such as market uncertainty in oil market. Especially in bearish Islamic markets, bad news concerning uncertainty can be perceived as riskier than good news.

A change in health sentiment, such as COVID-19 cases and COVID-19 investor sentiment, can be used to determine future direction of conventional and Islamic stock markets. Asymmetric effects associated with market news can make portfolio management more effective. COVID-19 investor sentiment states can be used to predict Islamic market index dynamics in MENA region.

This paper offered insight into heterogeneity of market conditions and dependencies of Islamic banks' stock market returns on COVID-19 investor sentiment and uncertainty, among others that should be considered when implementing investment decisions and policies.

The purpose of this paper is to explore the dynamic influence of WTI crude oil returns on the stock returns of China’s traditional energy sectors, including oil and gas exploitation, coal mining and processing, petroleum processing and coking, electricity, heat production and supply and mining services.

Hong’s information spill-over test and the DP Granger causality test are applied to investigate the relationship between the two markets. Moreover, a rolling window is introduced into the above two tests to capture time-varying characteristics of the influence of WTI crude oil returns.

The empirical results indicate that, first, there exists significant bidirectional linear causality between WTI crude oil returns and China’s traditional energy sectoral stock returns, but the nonlinear causality appears weaker. Second, the influence of WTI crude oil returns on traditional energy sectoral stock returns has time-varying characteristics and industry heterogeneity both in the linear and nonlinear cases. Finally, the decline of WTI crude oil prices may strengthen its linear influence on the stock returns of traditional energy sectors, while the excessive rise of market values in traditional energy sectors may weaken the linear and nonlinear influence of WTI on them.

The general nexus between international crude oil market and China’s traditional energy stock market is explored both in the linear and nonlinear perspectives. In particular, the dynamic linear and nonlinear influence of WTI crude oil returns on China’s traditional energy sectoral stock returns and its industry heterogeneity are analysed in detail.