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" The aim is to come up with a convex risk functional that incorporates a sefety margin with respect to nonparametric uncertainty and still can be approximated through parametrized models. The particular form of the parametrization allows us to develop a numerical method, based on neural networks, which gives both the value of the risk functional and the optimal perturbation of the reference measure."
"We present a framework for constructing multivariate risk measures that is inspired from univariate Optimized Certainty Equivalent (OCE) risk measures. We show that this new class of risk measures verifies the desirable properties such as convexity, monotonocity and cash invariance. We also address numerical aspects of their computations using stochastic algorithms instead of using Monte Carlo or Fourier methods that do not provide any error of the estimation."
"This article discusses the EFTA Court’s advisory opinion on the issue of whether real transactions, in the sense that they transfer expense and risk with full effect between independent parties, can constitute market manipulation. The aim of the article is to explore the reasoning by the court and then analyse and argue that such transactions (real ones) can indeed constitute market manipulation according to the 2014 Market Abuse Regulation (MAR) and MAD. The aim is also to analyse when real transactions constitute market manipulation."
"Even pioneering forward-looking stress tests cannot feasibly capture all possible tail risks. We propose supplementing the existing capital requirements regime by giving it a stronger precautionary and macroprudential focus, paying particular attention to the prevention of environmental tipping points to avoid systemic and catastrophic impacts on the financial system and macroeconomy."
"This paper reviews the use of AI in the ESG field: textual analysis to measure firms’ ESG incidents or verify the credibility of companies’ concrete commitments, satellite and sensor data to analyse companies’ environmental impact or estimate physical risk exposures, machine learning to fill missing corporate data (GHG emissions etc.)."
"We argue that datafication of insurer processes may fuel excessive data collection in the context of insurance contracts, generating a substantial risk of harm to consumers, especially in terms of discrimination, exclusion, and unaffordability of insurance. "
"Using a large sample of U.S. firms over the period 2007-2017, we find that when cybersecurity risk is higher, firms hold more cash."
"Our study contributes to the brainstorming literature by highlighting the importance of group composition. It suggests that firms can promote skeptical team judgments by leveraging individuals’ high trait skepticism in thoughtfully composed interacting groups."
" The study focused on evaluating and analysing the characteristics of literature and the themes investigated with a focus on four key aspects: governance, the effectiveness of IA, the relationship between internal auditors and other parties, and risk management to provide directions for future research."
"We find that bank capital and probability of default PD impact each other, where the total influence of the latter on the former is stronger. PD also affects capital via risk-taking but the opposite effect (i.e., from capital to PD via risk) is not identified, which challenges one of the main assumptions underlying capital regulation."