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In this paper, we extend the research on the effect of corporate social responsibility (CSR) on firm risk by analyzing the CSR–idiosyncratic risk nexus and how CSR can be integrated as insurance in a global risk management strategy. First, the causality between CSR and risk was tested. Second, copulas were estimated to strengthen the existing results on the structure of the dependence between the different dimensions of CSR activities and idiosyncratic risk levels. The empirical analysis was conducted on a sample of 254 European-listed firms over the 2018–2020 period. The main results showed a directional causality effect between CSR and idiosyncratic risk, and the dependences were modeled between CSR and realized idiosyncratic risk. This allows a better understanding of the risk implications of CSR for investors, corporate managers, and policy makers. [ABSTRACT FROM AUTHOR]

This paper studies the dynamic interactions of the ethanol, crude oil and corn market prices in the United States from January 2005 up to December 2014. The empirical analysis, for the shake of robustness, employs alternative time series methodologies based on single equation and system estimation approaches to cointegration and more specifically, the autoregressive distributed lags and the Johansen ML cointegration methodologies were applied complementary. The findings reveal a statistically significant long-run causal effect running from crude oil and corn prices to ethanol price as well as from ethanol and corn prices to crude oil price. Additionally, a positive relationship between crude oil price and ethanol price was revealed. [ABSTRACT FROM AUTHOR]

Owing to the uncertainty around the coupling and decoupling of oil and gas prices, this study re-examines the relationship between oil and gas markets by modeling the price of one energy source based on the price of the other, both linearly and nonlinearly. We present an autoregressive exogenous model and three nonlinear frameworks with different patterns of asymmetry. Based on daily data from January 7, 1997, to December 29, 2017, our analysis reaches two main findings. First, the nonlinear frameworks outperform the linear model (i.e., the autoregressive exogenous model) in modeling the relationship between oil and gas prices. Second, the nature of asymmetry varies based on market direction. We show that when oil prices exhibit an extreme movement (i.e., beyond a threshold value in absolute value), gas prices react nonlinearly, and that there is no relationship otherwise. Our results are robust for other frequencies, mainly weekly and monthly. These findings explain the conflicting results in the literature on the complex relationship between these markets. The results might serve investors in term of hedging, portfolio diversification, and asset allocation as we show that in the calm period, there is no relationship between oil and gas prices; however, the interaction between markets is more pronounced during periods of extreme movement. Similarly, policymakers' awareness of the nonlinear dynamic under extreme movements could inform the regulation policy and/or adjustment in case oil (gas) prices increase or decrease. [ABSTRACT FROM AUTHOR]