Knowledge that Transforms

This study analyzes the evolution of climate-risk discourse in banking using 4,887 news articles (2008–2024) collected from ProQuest. We apply Natural Language Processing and add two novel layers: (i) an event-alignment analysis that links coverage dynamics to dated policy and supervisory milestones, and (ii) a discourse-network analysis connecting banks and regulators. We document a marked post-2020 shift, with ESG emerging as the dominant framing (7,860 mentions) alongside persistent geographic asymmetries (U.S.-led coverage) and uneven sectoral engagement (Risk Management highest salience; Fintech lowest). Sentiment skews positive (≈4,000 positive vs. ≈1,500 negative), and topic modeling identifies eight stable thematic clusters spanning operations, ratings, ESG assessment, disclosures, and market instruments. Event alignment shows media attention is typically anticipatory (median peak two months before an anchor), with COP26 producing a sustained level shift (+100% within a ±6-month window) and the Bank of England’s CBES results generating the largest single spike (210 articles), whereas some 2022 rule-making announcements (e.g., SEC climate-disclosure proposal) exhibit sharper but less durable attention. The discourse network centers on two regulatory hubs (the Federal Reserve and the ECB) with key banks (e.g., Citigroup, JPMorgan, UBS) bridging into supervisory narratives. Collectively, the findings show climate risk becoming embedded in core banking practice while revealing structural, regional, and functional asymmetries that matter for policy design and implementation. • Provides the first longitudinal NLP-based analysis of climate risk discourse in the banking sector • Reveals how climate risk integration in banking has evolved across regulatory, operational, and market dimensions • Identifies distinct thematic domains shaping climate risk narratives in banking over time • Shows that climate risk discourse is predominantly anticipatory around major policy and supervisory milestones • Maps the institutional structure of climate risk governance by linking banks and regulators within a discourse network

We address the challenge of dynamic option hedging using deep reinforcement learning (DRL). Unlike traditional model-based approaches, DRL is purely data-driven and does not require explicit modeling of the underlying market dynamics. Leveraging a comprehensive high-frequency dataset of SPX options, we train, validate, and test a DRL agent in a realistic market environment that incorporates actual transaction costs. The study highlights three key contributions. First, we analyze the hedging of 0DTE (zero days-to-expiration) options, which now dominate market trading volume, and show that DRL outperforms Black–Scholes delta hedging at this horizon. Second, we evaluate robustness across regimes, finding that the DRL hedge remains effective in crises such as COVID-19, even when trained only on non-crisis periods. Third, we examine the determinants of the performance gap, the role of alternative reward specifications, and hedging behavior in the presence of price jumps.

We leverage differences in central bank independence and financial stability sentiment across countries to investigate the variability in banks’ stock market reactions to prudential policy announcements during the COVID-19 crisis. Our findings reveal that the relaxation of both macro- and micro-prudential policies leads to negative cumulative abnormal returns (CARs), the reaction being attenuated in countries where the central bank is more independent or communicates deteriorations in financial stability. The CARs around the announcement dates are 0.75 percentage points (pp) and 6.89 pp higher for macro- and micro-prudential policy announcements, respectively, in countries with greater central bank independence compared to those with lesser independence. The difference is approximately 3.73 pp and 5.65 pp between banks located in countries where the central bank communicates a negative sentiment about financial stability, compared to those where a positive sentiment is conveyed. The positive impact of higher degrees of central bank independence and deteriorations in financial stability sentiment on bank market valuation is enhanced for smaller banks, as well as for banks in countries with greater fiscal flexibility and a higher prevalence of privately owned banks. (181 words)

We study whether floods can affect financial stability through a credit risk channel. Our focus is onthe Netherlands, a country situated partly below sea level, where insurance policies exclude property damages caused by some types of floods. Using geocoded data for close to EUR 650 billion in real estate exposures, we consider possible implications of such floods for bank capital. For a set of 38 adverse scenarios, we estimate that flood-related property damages lead to capital declines that mostly range between 30 and 50 basis points. We highlight how starting-point loan-to-value ratios are one important driver of capital impacts. Our estimates focus on property damages as the main transmission channel and are also subject to a number of assumptions. If climate change continues, more frequent floods or flood-related macrofinancial disruptions may have stronger implications for financial stability than our estimates so far indicate.

This paper studies systemic-risk connectedness in the European insurance sector at three levels of granularity: across major segments of financial markets, across insurance subsectors, and across individual insurance companies. Using a common connectedness framework applied to returns, volatility, value-at-risk, and expected shortfall, we document that insurers are an important component of systemic-risk connectedness, especially during stress episodes. We also provide reduced-form evidence on economically relevant channels in the European institutional setting: aggregate insurer spillovers co-move with term spreads, sovereign spreads, and funding stress, and firm-level insurer-to-bank spillovers vary with sovereign risk and domestic sovereign-bond home bias in a way consistent with a balance-sheet channel. The analysis further reveals substantial heterogeneity across subsectors and identifies a stable core of systemically central insurers in firm-level networks.

Combining a rich database on natural hazards, granular flood hazard maps and detailed information on firm geolocalization, we study the dynamic effects of floods on European manufacturing firms over the period 2007-2018. We find that water damages significantly and persistently worsen firms’ performance, and may endanger their survival. An average flood deteriorates total assets by about 2% in the year after the event, and up to 5% seven years out. Repeated flooding has milder impacts, suggesting that adaptation measures are adopted in flood-prone areas. We show how reallocation of economic activity within flooded regions can reconcile our results with the “creative destruction” hypothesis for natural disasters.

We examine various implementation issues related to the calibration of output floors in setting minimum bank capital requirements under the finalized version of the Basel III capital accord. The main raison d’être of output floors is to limit the capital savings enjoyed by large banks due to regulatory arbitrage under the internal model paradigm. We consider regulatory arbitrage through the bank’s incentive to optimize its grading system in order to lower as much as possible the capital requirement given the structure of its asset portfolio in terms of internal ratings and default probabilities. Based on a fictional portfolio of SME loans observed over a full business cycle, we conduct a counterfactual analysis in order to compare the effect of the output floor implemented with respect to two benchmarks: ( i ) a standardized approach calibrated from credit ratings assigned by external rating agencies, as proposed in the finalized version of the Basel III capital accord; and ( ii ) an alternative, more granular, and comprehensive standardized approach benchmark, based on an external grading system that mimics the in-house credit assessment systems used by certain national central banks. Our results show that a more granular, risk-sensitive, benchmark is likely to reduce the effect of the output floor on the minimum capital requirement. We also reveal that output floors exhibit a countercyclical pattern, which is an interesting feature of the mechanism from a macroprudential point of view.

Stablecoins seek to address the high price fluctuations of unbacked cryptocurrencies, such as Bitcoin and Ether. However, recent studies as well as the collapse of stablecoin USTC (Terra) cast doubt on the stability of stablecoins. Using well-known Markowitz portfolio optimization methods, we combine five leading stablecoins into a global minimum variance portfolio that represents a stable aggregate stablecoin (SAS). We find that SAS is much more stable than its constituent stablecoins. Also, in a stress test adding USTC to the portfolio, SAS remains stable with a narrow price range over time. Importantly, the construction of SAS using modern diversification methods has practical implications for the ongoing development of central bank digital currencies (CBDCs).

We introduce digital currency into a macro model with a banking sector in which financial frictions generate endogenous systemic risk and instability. In the model, digital currency is fully integrated into the financial system . Stablecoin issuance significantly increases the probability of a banking-sector crisis because it depresses bank deposit spreads, particularly during crises, which limits banks’ ability to recapitalize following losses. While banking-sector stability suffers, household welfare can still improve significantly. Financial frictions nevertheless limit the potential benefits of digital currencies. The optimal level of digital currency could be below what would be issued in a competitive environment. In contrast to stablecoins, which are backed by debt, tokenized deposits backed by traditional bank assets improve welfare without harming financial stability . The scope for welfare gains from stablecoins or tokenized deposits depends on how households value the liquidity services of digital currency relative to traditional deposits and on the cost of issuing stablecoins.