Exploring the relationship between CSR performance and financial constraints: empirical evidence from European firms

This paper investigates the relationship between corporate social responsibility (CSR) activities and financial constraints. Our panel dataset consists of 397 European companies listed in the STOXX Europe 600 during 2009–2014. The findings reveal that firms with higher CSR performance exhibit lower degree of financial constraints. In addition, the link between CSR performance and financial constraints is a fully mediated relationship. The negative effect of CSR performance on financial constraints follows the path through mitigating agency conflicts of free cash flow and information asymmetry. The findings suggest that one mechanism linking CSR performance and financial constraints is a reduction of capital-market imperfections.     

Big data tools for Islamic financial analysis

Behavioural science states that emotions, principles and the manner of thinking can affect the behaviour of individuals and even investors in their decision making on financial markets. In this paper, we have tried to measure the investor sentiment by three means of big data. The first is based on a search query of a list of words related to Islamic context. The second is inferred from the engagement degree on social media. The last measure of sentiment is built, based on the Twitter API classified into positive and negative directions by a machine learning algorithm based on the naive Bayes method. Then, we investigate whether these sensations and emotions have an impact on the market sentiment and the price fluctuations by means of a vector autoregression model and Granger causality analysis. In the final step, we apply the agent‐based simulation by means of the sequential Monte Carlo method with the control of our Twitter measure on Islamic index returns. We show, then, that the three social media sentiment measures present a remarkable impact on the contemporaneous and lagged returns of the different Islamic assets studied. We also give an estimation of the parameters of the latent variables relative to the agent model studied.