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The study tests risk-taking and risk-aversion capabilities while distinguishing between business group firms and stand-alone firms and considering oil price volatility. Second, this attempt to study the linkage between risk-taking during market down movements and when the firms have established themselves as product market leaders. Third, this study analyses the “sentiment” state, where it explores the reaction of corporations when the market is in the negative direction, and lastly, it explores the linkage between product market competition and risk-aversion.

This study uses financial information for 1,273 non-financial companies and other required data from various sources. The study employs panel data and utilizes different empirical methodologies, including the generalized method of moments (GMM) estimator, to test the stated hypotheses.

We find that the business group firms have more risk-taking proficiencies compared with the stand-alone firms. Moreover, this study discovers that the corporates avoid taking risks when the market is not performing well. Also, when the market is down and crude prices are high, the management expects high earnings in the future, willingly takes risks and shows that product market leaders do not follow the risk-aversion strategy.

The empirical results indicate that oil price movement can restrict management’s behaviour when choosing a risky investment project. Management should develop a robust policy that follows the group of firms. In the policy, the management should describe the level of risk that may be taken by the firm and implement it when required.

Since we do not find any studies in this context, then there is a major and essential gap in the literature that this study should fill.

The purpose of this paper is to investigate the oil price–bank risk nexus by considering the heterogeneity of bank characters.

This paper empirically tests the effect of oil price movements on bank credit risk by using a sample of 279 banks in the Middle East and North Africa countries from 2011 to 2017.

Authors find robust evidence that the credit risk of bank loan portfolios is negatively associated with increased oil prices. The heterogeneity analysis indicates that the effect of asset quality improvement brought about by rising oil prices is more salient in conventional banks, and banks with small size, low liquidity and whose funding source relies on customers’ deposits.

The results favor the diversification of bank funding sources, the improvement of a country’s financial development, the adoption of explicit deposit insurance and macroprudential policies, such as countercyclical liquidity buffers, to weaken the adverse impact of oil prices declines.

The present paper enriches the literature of oil price–bank risk nexus by analyzing the heterogeneity of bank characters and advances our knowledge on the determined factors of bank riskiness and vulnerability.

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).

We examine the behavior of the Russian stock market as one of the leading indices of economic health, reflecting investors’ expectations about future returns. The sample period includes the global financial crisis, a recovering period, and the recent crisis in the Russian economy 2014–2015.

We assume that the Russian stock market strongly depends on the global market, but the market is not fully integrated. This chapter investigates whether specific risk factors such as high dependence of the Russian economy on oil prices and currency volatility are priced in the Russian stock market, using International CAPM with time-variant parameters and conditional heteroskedasticity. The results show that the global financial crisis has had a profound negative impact on the Russian market, and that the expected return and liquidity has declined. The risk of investing in the Russian market is estimated as higher than in the developed market and even in other emerging markets after the global recession. We find that oil price exposure and currency risk to be priced in the Russian stock market and indicate that international investors require higher compensation for bearing these risks. The price of the currency risk has decreased since the implementation of the floating exchange rate regime by the Central Bank of Russia in 2014, but still significant.

Some opportunities to overcome the present stagnation and drive for a sustainable development are discussed.

This paper aims to investigate the impact of oil price shocks on the Turkish sovereign yield curve factors.

To extract the latent factors (level, slope and curvature) of the Turkish sovereign yield curve, we estimate conventional Nelson and Siegel (1987) model with nonlinear least squares. Then, we decompose oil price shocks into supply, demand and risk shocks using structural VAR (structural VAR) models. After this separation, we apply Engle (2002) dynamic conditional correlation GARCH (DCC-GARCH (1,1)) method to investigate time-varying co-movements between yield curve factors and oil price shocks. Finally, using the LP (local projections) proposed by Jorda (2005), we estimate the impulse-response functions to examine the impact of different oil price shocks on yield curve factors.

Our results demonstrate that the various oil price shocks influence the yield curve factors quite differently. A supply shock leads to a statistically significant increase in the level factor. This result shows that elevated oil prices due to supply disruptions are interpreted as a signal of a surge in inflation expectations since the cost channel prevails. Besides, unanticipated demand shocks have a positive impact on the slope factor as a result of the central bank policy response for offsetting the elevated inflation expectations. Finally, a risk shock is associated with a decrease in the curvature factor indicating that risk shocks influence the medium-term bonds due to the deflationary pressure resulting from depressed economic conditions.

Our results provide new insights to understand the driving forces of yield curve movements induced by various oil shocks to formulate appropriate policy responses.

The study contributes to the literature by two main dimensions. First, the recent oil shock identification scheme of Ready (2018) is modified using the “geopolitical oil price risk index” to capture the changes in the risk perceptions of oil markets driven by geopolitical tensions such as terrorism and conflicts and sanctions. The modified identification scheme attributes more power to demand shocks in explaining the variation of the oil price compared to that of the baseline scheme. Second, it provides recent evidence that distinguishes the impact of oil demand and supply shocks on Turkey's yield curve.

In this paper we employ a GMM‐based approach to test the restrictions imposed by a two‐factor ‘market and oil’ pricing model when a risk‐free asset is assumed to exist. We examine the Australian market which has several interesting features including self‐sufficiency in relation to oil, a large concentration of natural resource companies, susceptibility to the ‘Dutch disease’ and a diverse industry base. We extend previous literature by examining industry sector equity returns as different industry groups are likely to have different exposures to an oil factor, particularly in Australia. In the formal tests, we find evidence in favour of the model, particularly for industrial sector industries. The preferred model includes a domestic portfolio proxy for market returns in addition to the oil price factor and we find evidence of a positive market risk premium as well as a significantly priced oil factor.

In his review of 30 years of research in Prospect Theory, Barberis (2013) notes that support for Prospect Theory had come mainly from the laboratory. In this paper, I write about a recurring phenomenon in real life that is consistent with Prospect Theory predictions in decision-making loss domain. The 60 cases noted in this paper are associated with specific risk seekers that had cost more than $140 billion (an average of $2.33 billion per case). Given space consider– ations, I provide synopses for 14 cases. A few of these cases have been discussed in the extant literature in connection with internal control, but were not considered from the perspective of Prospect Theory. It is striking that these cases are costly, all participants are young men, and almost all had followed the gambler’s martingale strategy – i.e., double down. While these cases are informative about risk-seeking behavior, they are not sufficiently systematic to be subjected to stylized archival research methods.

The aim of this study was to investigate the dynamic network connectedness between stock markets and commodity futures and its implications on hedging strategies. Specifically, the authors studied the impact of the 2014 oil price drop and coronavirus disease 2019 (COVID-19) pandemic on risk spillovers and portfolio allocation among stock markets (United States (SP500), China (SSEC), Japan (Nikkei 225), France (CAC40) and Germany (DAX)) and commodities (oil and gold).

In this study, the authors used the Baba, Engle, Kraft and Kroner–generalized autoregressive conditional heteroskedasticity (BEKK–GARCH) model to estimate shock transmission among the five financial markets and the two commodities. The authors rely on Diebold and Yılmaz (2014, 2015) methodology to construct network-associated measures.

Relying on the BEKK–GARCH, the authors found that the recent health crisis of COVID-19 intensified the volatility spillovers among stock markets and commodities. Using the dynamic network connectedness, the authors showed that at the 2014 oil price drop and the COVID-19 pandemic shock, the Nikkei225 moderated the transmission of volatility to the majority of markets. During the COVID-19 pandemic, the commodity markets are a net receiver of volatility shocks from stock markets. In addition, the SP500 stock market dominates the network connectedness dynamic during the COVID-19 pandemic, while DAX index is the weakest risk transmitter. Regarding the portfolio allocation and hedging strategies, the study showed that the oil market is the most vulnerable and risky as it was heavily affected by the two crises. The results show that gold is a hedging tool during turmoil periods.

This study contributes to knowledge in this area by improving our understanding of the influence of fluctuations in oil prices on the dynamics of the volatility connection between stock markets and commodities during the COVID-19 pandemic shock. The study’s findings provide more implications regarding portfolio management and hedging strategies that could help investors optimize their portfolios.