"... climate change exacerbates financial instability, but adaptation can build resilience to climate impacts."
"We here propose a novel XAI [eXplainable AI] technique for deep learning methods (DL) which preserves and exploits the natural time ordering of the data. Simple applications to financial data illustrate the potential of the new approach in the context of risk-management and fraud-detection."
" The global climate crisis and the economy’s green transition are giving rise to new types of risks for banks. This paper analyses some of the key international bank regulatory standards, namely disclosure, risk management, governance and regulatory capital. "
"Climate risk is positively associated with the environmental, social, and governance (ESG) performance of banks and negatively associated with the stakeholder ESG sentiment towards them. Negative sentiment due to such exposure is associated with worse financial performance and lower stock returns, but stronger ESG performance mitigates these adverse effects."
"Under the Single Supervisory Mechanism (SSM) introduced in 2014, the European Central Bank directly supervises significant euro area banks, which hold about 82% of total banking assets. We find that this important supervisory change has positive effects on the return on assets and the return on risk-weighted assets of SSM banks without increasing the risk weights used to calculate regulatory capital."
“Empirical results indicate that firms with higher analyst attention, institutional ownership, and information disclosure quality rating are less sensitive to GPR [#geopoliticalrisk].”
"We show that negative shocks to the selected indicators lead to economic slowdown, with a persistent drop in GDP growth and a short-lived but large increase in country risk."
"We connect variational preferences with the likelihood functions and prior probabilities over parameters that are building blocks of statistics and econometrics."
"As often in new regulatory domains, there is a tendency both of re-inventing the wheel – by disregarding insights from neighboring policy domains (e.g. nano-technology or aviation) – and of creating silos of research – by failing to link up and systematize existing accounts in a wider context of regulatory scholarship."
" In this paper, we use stochastic algorithms schemes in estimating MSRM [market data based systemic risk measure] and prove that the resulting estimators are consistent and asymptotically normal. We also test numerically the performance of these algorithms on several examples."