Reputation and Business Sustainability

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This study examines the relationship between reputational events and business sustainability by assessing the effects of such events on the share prices/market capitalisations of FTSE/JSE Top 40 Index entities. Using event study methodology and Tobin’s Q ratio, the study found that reputational events are associated with significant negative cumulative average abnormal returns on the day of the event announcement and for a period thereafter, highlighting the need for listed firms to include #reputationalrisk within their #riskmanagement management frameworks and for practitioners to implement reputation management strategies.

The uncharted territory of the Bank of England's human rights obligations

This working paper analyzes whether the #boe has a legal obligation to adjust #capitalrequirements for #financialinstitutions in response to the #climatecrisis. The paper argues that the BoE, as a public authority, must abide by the #humanrights obligations set out in the European Convention on Human Rights, which are deeply intertwined with climate concerns.

ESG Securities Fraud

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This article addresses the increasing concern of investors regarding corporate wrongdoing impacting a company's stock price, particularly regarding #esgrisk. The article argues that courts should not dismiss ESG securities #fraud cases as mere puffery, but instead focus on whether the corporation and its managers knew of a material #risk of an #esg problem but deceptively obscured that risk in its communications with investors.

Regulation Priorities for Artificial Intelligence Foundation Models

This article discusses the need for high-level frameworks to guide the #regulation of #artificialintelligence (#ai) technologies. It adapts a #fintechinnovation Trilemma framework to argue that regulators can prioritize only two of three aims when considering AI oversight: promoting #innovation, mitigating #systemicrisk, and providing clear #regulatoryrequirements.

A Disaster Risk Reduction and Resilience Scorecard for Climate Adaptation

This research presents a balance #scorecard tool for assessing #disasterriskreduction and #resilience (#dr3) in the context of #floods, #droughts and #heatwaves. It aims to support the integration and monitoring of #climateadaptation, #sustainability and #riskreduction into development planning in vulnerable communities. This approach contributes to strengthening #governance, resilience and #riskmanagement in disaster-prone areas.

Reasonable AI and Other Creatures: What Role for AI Standards in Liability Litigation?

This paper discusses the relationship between standards and private law in the context of #liability #litigation and #tortlaw for damage caused by #ai systems. The paper highlights the importance of #standards in supporting policies and legislation of the #eu, particularly in the #regulation of #artificialintelligence. The paper assesses the role of AI standards in private law and argues that they contribute to defining the duty of care expected from developers and professional operators of AI systems.

Reexamining Enron's Regulatory Consequences

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This article examines the downfall of #Enron Corporation, which is often seen as the epitome of corporate #fraud. Enron engaged in complex structured hedging transactions to achieve accounting results, which ultimately led to its collapse and the imprisonment of some of its #managers. The article aims to present the facts objectively and asks what advice should have been given to Enron's managers. It suggests that society can overreact to #businessfailure and #regulatory responses can miss the mark, and that corporate managers must take reasonable risks to remain competitive. The article concludes that failure should not automatically be judged as managerial misfeasance.

Particle MCMC in forecasting frailty correlated default models with expert opinion

This paper focuses on predicting #corporate #default #risk using frailty correlated default #models with subjective judgments. The study uses a #bayesian approach with the Particle Markov Chain #montecarlo algorithm to analyze data from #us public non-financial firms between 1980 and 2019. The findings suggest that the volatility and mean reversion of the hidden factor have a significant impact on the default intensities of the firms.