Veille réglementaire

BCE — communiqués

ECB President Lagarde to step down on 7 February 2027

EBA

The EBA advises on targeted simplifications to Taxonomy disclosures

The European Banking Authority (EBA) has published its response to the European Commission’s Call for Technical Advice on certain key performance indicators (KPIs) and other aspects of the Disclosures Delegated Act under Article 8 of the Taxonomy Regulation. The EBA advises on targeted changes to streamline disclosure requirements, reduce complexity and enhance the usability of information disclosed by credit institutions and investment firms.

BRI (Bâle)

CPMI publishes analysis on how central banks support payment system safety and efficiency and trust in money in the rapidly changing payments ecosystem

A new report by the BIS Committee on Payments and Market Infrastructures (CPMI) examines how technological innovation, changing user demand and the emergence of new types of payment service providers and arrangements are transforming payment systems.

arXiv — finance statistique

Contemporaneous Transmission Networks and Systemic Risk in European Banking

arXiv:2610.37487v1 Announce Type: new Abstract: We study how contemporaneous equity-return transmission shapes systemic exposure among 51 listed European banks. Using a recursive non-Gaussian network model on volatility-standardized returns, we construct two market-capitalization-weighted measures based on direct and indirect transmission effects: the Systemic Impact Score (SIS), capturing a bank's potential influence on other institutions, and the Systemic Vulnerability Score (SVS), capturing its exposure to disturbances originating elsewhere. The fitted network reveals distinct transmitting

arXiv — finance statistique

Event definition and the branching ratio: Hawkes estimates of price-change clustering in the consolidated quote feed

arXiv:2610.36317v1 Announce Type: new Abstract: Hawkes models of price changes in the consolidated US quote feed find a sub-millisecond kernel component and a branching ratio near criticality. We show that in large-tick stocks the first is the feed's construction: half of NBBO changes are locks or depleted quotes, resolved within a millisecond, which the model reads as excitation. Defining the event as a mid-price level persisting for one millisecond removes the component. Raw fits put three times the clean kernel mass within one second, which a simulation reproduces. Since the total branching

arXiv — gestion des risques

An Application of Geometric Riemannian Pricing Algorithm for Valuing Catastrophe Bonds in Incomplete Markets: Market-Consistent Financial Entropy and the Split of Frequency and Severity Risk Premia

arXiv:2610.37171v1 Announce Type: cross Abstract: This paper presents a framework for pricing catastrophe (CAT) bonds in incomplete markets through Riemannian geometric optimization of financial entropy. We formulate pricing-measure selection as a maximum financial entropy problem on a finite-dimensional manifold of equivalent measures, parameterized by the non-hedgeable market prices of catastrophe frequency and severity risk, with discounting fixed by the default-free term structure. Since unconstrained entropy maximization recovers the physical measure, we incorporate observed secondary-mar

arXiv — gestion des risques

Risk measures for infinite-server queues driven by a Cox-BESQ process

arXiv:2610.36473v1 Announce Type: cross Abstract: This paper introduces a model for infinite-server queues driven by a Cox process with stochastic intensity given by a squared Bessel (BESQ) process. Exploiting the affine structure of the underlying dynamics, we derive a closed-form expression for the joint moment-generating function (MGF) of the arrival intensity, the number of customers in the system, and the integral of the number of customers in the system over a time interval. This MGF can also be obtained at two (or more) dates, thereby allowing an analysis of the time evolution of infini

arXiv — finance statistique

Compiling and forecasting implied volatility surfaces via survey sampling, tempered inverse-probability sequence learning, and causal activity clocks

arXiv:2610.33438v1 Announce Type: cross Abstract: Compiling implied volatility (IV) surfaces and forecasting derivative risk from high-frequency equity and options feeds requires addressing contract heterogeneity, schema shifts, volatility clustering, and non-stationary trading activity. Using a split-adjusted NVIDIA (NVDA) equity and options panel (2018-2025), this study integrates finite-population survey sampling, tempered inverse-probability sequence learning, and causal activity clocks. Four findings emerge. First, cross-sectional surface accuracy depends on matching the sampling design t

arXiv — finance statistique

Weekend Crypto Volatility and Monday Market Risk

arXiv:2610.35702v1 Announce Type: new Abstract: Cryptocurrencies trade continuously while major traditional markets close over the weekend. We examine whether weekend cryptocurrency volatility predicts Monday variance in equity, commodity and fixed-income markets. Using daily range-based variance measures for Bitcoin, Ether, XRP, the S&P 500, gold and a US Treasury ETF over 2017-2026, we augment heterogeneous autoregressive models with a common weekend cryptocurrency factor. Predictive content is weak before 2024 but significant thereafter. In the post-2024 sample, a one-standard-deviation inc

arXiv — gestion des risques

Discrete-Time Survival Modelling with Dynamic Industrial Graphs for Mortgage Credit Risk

arXiv:2610.18795v2 Announce Type: replace-cross Abstract: Mortgage credit risk may exhibit dependence across economically connected areas, even when they are geographically distant. However, current models typically represent cross-area dependence through fixed geographical neighbourhoods, potentially overlooking economic connections that extend beyond physical proximity and evolve over time. These models may fail to capture shared risks among geographically distant but economically similar areas, and cannot describe a changing dependence of risk; it therefore risks retaining economically obso

arXiv — gestion des risques

A multistate approach to disability insurance reserving with information delays

arXiv:2312.14324v3 Announce Type: replace-cross Abstract: Disability insurance claims are often affected by lengthy reporting delays and adjudication processes. The classic multistate life insurance modeling framework is ill-suited to handle such information delays since the cash flow and available information can no longer be based on the biometric multistate process determining the contractual payments. We propose a new individual reserving model for disability insurance schemes which describes the claim evolution in real-time. Under suitable independence assumptions between the available in

arXiv — gestion des risques

LLM-Generated Counterfactual Stress Scenarios for Portfolio Risk Simulation via Hybrid Prompt-RAG Pipeline

arXiv:2512.07867v2 Announce Type: replace Abstract: We develop a transparent, auditable large language model (LLM) pipeline for macro-financial stress testing. Structured prompting, with optional retrieval of country fundamentals and news, emits G7 macroeconomic scenarios (GDP growth, inflation, policy rate), which are converted into deviations from an IMF World Economic Outlook baseline and translated into portfolio losses through a three-channel PCA factor model. The macro-to-factor mapping is stipulated rather than estimated, so every tail-risk multiple is conditional on stated assumptions.

arXiv — gestion des risques

Optimal portfolio choice under green transition timing risk

arXiv:2610.33597v1 Announce Type: cross Abstract: We study an investor's optimal portfolio choice problem when they account for the impact of a possible future green transition, whose timing is uncertain. We model the green transition as a discontinuity in the stock price processes, driven by a single jump process with constant intensity, in which 'green' stocks increase in value and 'brown' stocks decrease in value. The investor is ambiguous about the timing of the green transition and designs an investment strategy which is robust to this risk. The investor has constant relative risk aversio

BCE — communiqués

October 2026 euro area bank lending survey

arXiv — gestion des risques

Risk Adequacy and Anti-Discrimination in Insurance Pricing: Classification, Aggregation, and Transfers

arXiv:2610.32614v1 Announce Type: new Abstract: Insurance tariffs must reconcile risk-based pricing, portfolio coverage, and anti-discrimination requirements. We introduce a framework in which tariffs are constructed through classification, aggregation of benchmark risk prices within classes, and balanced transfers, and are evaluated by several distinct criteria. This yields a multi-objective tariff-design problem whose attainable objective set and Pareto frontier describe the resulting trade-offs. Risk adequacy is measured by the discrepancy between charged premiums and individual benchmark r

arXiv — finance statistique

Intraday Forecasting Ability and Liquidity Provision of Institutional Traders

arXiv:2610.31141v1 Announce Type: cross Abstract: This study uses a high-frequency dataset from a stock exchange to examine how forecasting ability and liquidity provision relate to institutional traders' proprietary intraday profitability. We discover persistent forecasting abilities among traders. Specifically, we demonstrate that hypothetical flow-following strategies based on the execution flows of these skillful traders yield annualized Sharpe ratios ranging from 16 to 63 across various trading frequencies. We match buy and sell executions into positions, linking realized profit and loss

arXiv — gestion des risques

A General Framework for Importance Sampling with Markov Random Walks

arXiv:2311.12330v3 Announce Type: replace-cross Abstract: Although stochastic models driven by latent Markov processes are widely used, the classical importance sampling methods based on the exponential tilting for these models suffer from difficulties in computing associated eigenvalues and eigenfunctions and the plausibility of the indirect asymptotic large deviation regime for the variance of the estimator. We propose an importance sampling framework that twists the observable and latent processes separately using a link function that directly minimizes the estimator's variance. An optimal

arXiv — gestion des risques

Multichoice Modeling: Exploring Decision Configuration Space under Uncertainty

arXiv:2610.31038v1 Announce Type: cross Abstract: Decision support has become sophisticated at exploring uncertainty, but much less so at representing the architecture of the decision itself. As a result, the decision space is often narrowed before uncertainty is analyzed, leaving interactions among choices and the effects of alternatives they imply largely invisible. This paper introduces multichoice modeling, a framework for making large decision configuration spaces explicit and computationally explorable under uncertainty. Drawing on the logic of rugged landscapes, we conceptualize such pr

arXiv — gestion des risques

General bounds on functionals of the lifetime under life table constraints in a joint actuarial-financial framework

arXiv:2603.06238v3 Announce Type: replace Abstract: In life insurance, life tables provide survival probabilities at integer ages but leave the distribution of deaths within each year unspecified. This incompleteness is particularly relevant for modern insurance products such as variable annuities, whose payoffs depend jointly on lifetime uncertainty and financial market performance. The valuation of such contracts must therefore be carried out in a joint actuarial-financial framework, as their values depend not only on the full information about mortality rates but also on the interaction bet

arXiv — gestion des risques

Distributions or Quantiles? A Convex Variational Theory of Worst-Case Risk

arXiv:2610.29652v1 Announce Type: new Abstract: Worst-case risk evaluation is central to finance and operations research, yet existing analytical results remain fragmented and largely confined to ambiguity sets with specific structures. Using spectral risk measures as the underlying class, we develop a convex variational theory that unifies these analyses and extends them to richer ambiguity models. The theory rests on a representation principle: use the quantile or distribution formulation that preserves convexity of the full ambiguity set. In both representations, the resulting optimality co

arXiv — gestion des risques

Deep catastrophic-risk-aware reinforcement learning

arXiv:2610.27214v1 Announce Type: cross Abstract: Estimating extreme risk in reinforcement learning becomes increasingly difficult as the confidence level increases, since only a small number of observations contribute to empirical estimates of Conditional Value-at-Risk (CVaR). In this paper, we extend an Extreme Value Theory (EVT) approach for CVaR optimization to high-dimensional neural-network policies. Using a peaks-over-threshold representation and method-of-moments estimation, we obtain a differentiable tail-risk objective and show that, conditional on the selected threshold, its finite-

arXiv — gestion des risques

Dynamic portfolio selection under range value-at-risk with logarithmic returns

arXiv:2610.26919v1 Announce Type: new Abstract: This paper studies continuous-time portfolio selection under Range Value-at-Risk (RVaR), with both portfolio performance and risk evaluated in terms of logarithmic returns. We formulate a mean--RVaR problem in a continuous-time financial market and reduce the dynamic optimization to a static quantile problem. Using quantile representation, Lagrangian optimization, and convexification, we characterize the optimal terminal wealth through the convex envelope of an RVaR-specific transformed weighting function. The RVaR-specific convex envelope exhibi

FSB

Innovation and resilience: managing the risks of a changing financial system

In this speech at RiskLive Asia 2026, John Schindler, FSB Secretary General, addresses the importance of international organisations in a shifting geopolitical landscape.

arXiv — finance statistique

Conditionally Identifiable Latent Representation for Multivariate Time Series with Structural Dynamics

arXiv:2603.22886v2 Announce Type: replace-cross Abstract: We propose the Identifiable Variational Dynamic Factor Model (iVDFM) for multivariate time series. The model combines variational inference with partial identifiability guarantees up to a known ambiguity class. Innovations follow a conditional exponential-family prior over observed auxiliary context and regime embeddings. Linear diagonal dynamics map innovations to factors and preserve that class, so factors are partially identifiable up to permutation and component-wise affine maps. We train by maximizing the ELBO and estimate uncertai

arXiv — finance statistique

Conflicting History in Foundation Model Return Forecasts

arXiv:2610.25822v1 Announce Type: new Abstract: Older observations can help a forecaster learn a predictive relationship while becoming misleading when that relationship changes. We study this tension using paired return histories that differ in older observations but share recent returns and the conditional distribution of the next return. Across five foundation-model forecasting procedures and three simulated processes, each evaluated on 1,024 independent replications, conflicting history reduces the probability of improving on zero in all 30 higher-signal comparisons. This loss of usefulnes

arXiv — finance statistique

More Mentions, Less Information? Diagnosing Identity and Alignment in Reddit Embeddings for Volatility Forecasting

arXiv:2610.25468v1 Announce Type: new Abstract: Since the 2021 GameStop short squeeze, r/WallStreetBets (WSB) has been associated with episodes of extreme volatility, and its text is increasingly used to forecast volatility. A model using only large language model (LLM) embeddings of WSB posts attains an out-of-sample $R^2$ of 0.13 for log realized variance. That number shows predictive power, but it does not reveal where the information comes from or how much the text adds beyond a firm's own volatility history. We answer these questions with a diagnostic protocol that nests embeddings on a h

arXiv — gestion des risques

Conformal Kelly: When Marginal Coverage Transfers and the Economics Do Not

arXiv:2608.01494v3 Announce Type: replace-cross Abstract: We size portfolio positions from conformal prediction intervals, reading the interval half-width as the scale in a capped fractional-Kelly rule (Conformal Kelly), and evaluate the rule under a pre-registered protocol. The development record is an autonomous LLM-agent search over roughly 200 configurations on a single six-year window (2016-2021) of eight US-listed ETFs. All later data was sealed before the search, and two final configurations, nine comparison books and the mapping from outcomes to conclusions were registered before unsea

arXiv — gestion des risques

Coherent risk from finite models

arXiv:2602.00784v3 Announce Type: replace Abstract: Coherent estimators at different sample sizes need not describe the same population risk. We prove that dyadic estimators do so exactly when duplicating every scenario leaves the estimate unchanged, and recover the population dual set from the finite models. The risk of a Bernoulli loss determines the exact Wasserstein, Kolmogorov and total-variation moduli on a common bounded support. It also characterises uniform estimability, with an impossibility bound for arbitrary randomised estimators. An intrinsic floor on tail levels gives an explici

arXiv — gestion des risques

Teacher Supervision, Fixed Representations and Calibration: Exact Risk Calculations for Candidate-Scoring Decision Models

arXiv:2610.26797v1 Announce Type: cross Abstract: Candidate-scoring decision models return a probability distribution over a presented set of answers. Public documentation of one such system, Jev, and of an open counterpart, JevAny, describes three training ingredients that determine what these probabilities estimate: soft targets from larger models, a frozen pretrained backbone and temperature calibration. We analyze each ingredient in Gaussian surrogates where the finite-sample risk can be computed exactly. A student trained on teacher targets inherits the teacher's bias, which more student

arXiv — gestion des risques

Probability-Weighting Functions for Normal Tempered-Stable Laws: Orthogonal Channels and Information-Theoretic Indices

arXiv:2610.26746v1 Announce Type: cross Abstract: A probability-weighting function (PWF) maps objective probabilities into decision weights. We construct PWFs from changes in the distribution of returns rather than from a parametric family: with prior and posterior return distributions $F_{prior}$ and $F_{post}$, the PWF is $w(p) = F_{post}(F_{prior}^{-1}(p))$. Both distributions are normal tempered-stable (NTS), and the posterior differs from the prior along one of three channels, each isolated with the variance held fixed: scale, skewness and tail thickness. Around a symmetric benchmark with

arXiv — gestion des risques

The Control Layer Behind Rule-Following Agents Trading Across Market Conditions

arXiv:2610.26324v1 Announce Type: cross Abstract: Trading discipline often fails people. Our study tested whether four AI trading agents followed their strategies and risk rules. Offering traders the evidence and an agent evaluation toolkit to separate luck from following the rules, before giving agents meaningful autonomy or capital. Our study analysed 2,627 closed positions from 12 February to 27 August 2026 across the same asset universe and execution conditions. Most positions were simulated against live prices with a 0.09% round-trip fee; 18% involved real Hyperliquid orders. Each positio

arXiv — gestion des risques

Amortized Neural Filtering for Calibrated Posteriors in Statistical Arbitrage

arXiv:2610.25802v1 Announce Type: cross Abstract: Statistical arbitrage trades on an estimate of the state of a residual spread, and conventional practice discards the uncertainty of that estimate. We keep the uncertainty and use it in the trading decision. A Neural Filter Estimator (NFE) is trained on simulated paths of a mean-reverting process whose innovation law is selected by testing candidates against real residuals; once trained, it returns the posterior over the latent state of every spread in a cross-section in one forward pass. Three results follow. On simulated paths with known trut

arXiv — gestion des risques

Conditional Weight of Evidence for Gradient-Boosted Credit Models: Estimation, Additivity and Its Relation to Adverse Action Reasons

arXiv:2610.24586v1 Announce Type: cross Abstract: Traditional weight of evidence assigns a credit characteristic a value based on its association with default across a population. Credit analysis also requires an assessment of that characteristic in the context of an individual applicant's record. We study conditional weight of evidence for this purpose. It measures the change in default log odds from observing a characteristic after the remaining credit information is known. Its sign identifies whether the characteristic adds adverse or favorable information for that applicant, and its magnit

arXiv — gestion des risques

Dynamic Programming for Value-at-risk Markov Decision Processes in Continuous Spaces

arXiv:2610.24439v1 Announce Type: cross Abstract: Value-at-Risk (VaR) is a widely adopted quantile-based risk measure in practice, yet incorporating VaR objectives into Markov decision processes (VaR MDPs) remains a longstanding challenge. Recent work has derived dynamic programming equations for VaR MDPs in finite state and action spaces but left the case of more general spaces unresolved. This paper establishes, for the first time, the validity of these equations in continuous spaces, for both finite- and infinite-horizon settings. Such cases naturally arise in many real-world dynamic decisi

arXiv — finance statistique

Reading the News Without Hindsight: NoLBERT Topics and the Cross-Section of Stock Returns

arXiv:2610.22745v1 Announce Type: new Abstract: Language models that read financial news are usually trained on text from the same years used to test them, so a backtest can reward hindsight. We build news topics from NoLBERT, an encoder pretrained only on text published between 1976 and 1995, adapted into a sentence encoder by contrastive fine-tuning on passages of the same article, with no labels or returns. We compare it with LDA, MiniLM and FinBERT readers on 1.26 million articles from 2012 to 2024, convert each reader's topics into attention shocks and stock exposures, and forecast the re

arXiv — gestion des risques

Requested, Executed and Recoverable Credit: Shared Action Ordering among LLM Borrowers in a Simulated Lending Market

arXiv:2610.15973v2 Announce Type: replace Abstract: We test whether shared action ordering changes executed credit in a simulated collateralized lending market. Three small open-weight language models face a borrowing cap that values collateral at the pool price; only two of the three model families traded. A validation campaign, hash-locked locally before its first model call, pairs 12 common-order markets with 12 balanced-order markets under a revised interface. An exact randomization test rejects the sharp null that common-market net debt is invariant to complete-order assignment (two-sided

arXiv — gestion des risques

Agentic AI in Automated Markets

arXiv:2610.22522v1 Announce Type: cross Abstract: Automated markets increasingly host autonomous, learning trading agents and are powered by formulaic automated market makers (AMMs). We study how heterogeneous agent behavior shapes stress, risk-adjusted performance, liquidity, and volatility in these types of markets. Three behavioral archetypes are modeled as agentic reinforcement learning (RL) systems: a rational arbitrageur, a manipulator, and a retail herd-follower. Each archetype is defined by its reward function within a common, asset-agnostic exposure-control environment, and each is tr

BCE — supervision bancaire

Frank Elderson: From climate and nature risks to economic resilience and competitiveness