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on Risk Management |
| By: | Hyeyoon Jung; Jaehoon (Kyle) Jung |
| Abstract: | Housing is the largest component of assets held by households in the United States, totaling $48 trillion in 2025. When natural disasters strike, the resulting damage to homes can be large relative to households’ liquid savings. Homeowner’s insurance is the primary financial tool households use to protect themselves against property risk. Despite the economic importance of homeowner’s insurance, we know surprisingly little about how insurance contracts are actually designed with respect to property risk. In this post, which is based on our new paper, “Economics of Property Insurance, ” we examine how homeowner’s insurance contracts are structured in practice. Using a new granular dataset covering millions of homeowner’s insurance policies, we document four striking patterns about coverage limits, deductibles, insurance pricing, and the distribution of property losses. |
| Keywords: | insurance; financial constraints; household finance; moral hazard; contracting |
| JEL: | C6 D8 G1 G2 G3 |
| Date: | 2026–04–13 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednls:103025 |
| By: | Ms. Ebru Sonbul Iskender; Katharine Seal; Ana Carvalho |
| Abstract: | The Basel capital framework has evolved since the introduction of Pillar 2 in Basel II. Basel III enhanced capital quality and quantity, adding macroprudential buffers such as the capital conservation buffer, the countercyclical capital buffer, and systemic risk buffers for global and domestic systemically important banks to strengthen banking resilience post-global financial crisis. Pillar 2 remains crucial for addressing bank-specific risks and vulnerabilities beyond Pillar 1, relying on supervisory judgment and banks’ internal capital adequacy assessments. Emerging and developing economies should adapt the Basel framework to local contexts, often maintaining higher capital requirements because of macroeconomic volatility and structural weaknesses. In developing the architecture of capital adequacy, jurisdictions need to focus on the appropriate mix and the sequencing of Pillar 2 add-ons and Basel III capital buffers tailored to their specific circumstances. Effective implementation requires strong supervisory powers, good data quality, and a tailored mix of Pillar 2 add-ons and Basel III buffers. |
| Keywords: | Basel Framework; Pillar 2 capital add-ons; capital buffers; risk-based supervision; emerging market and developing economies; credit cycle; capital requirement; bank capital; countercyclical capital buffer; establishing capital threshold; capital assessment; Countercyclical capital buffers; Capital adequacy requirements; Basel III; Global systemically important banks; Credit; Global |
| Date: | 2026–04–08 |
| URL: | https://d.repec.org/n?u=RePEc:imf:imftnm:2026/002 |
| By: | Anastasiia Zbandut; Carolina Goldstein |
| Abstract: | We derive five tractable credit risk metrics for DeFi lending vault depositors, grounded in a formal three level decomposition of vault risk into mechanical loss channels (Level 1), governance quality (Level 2) and smart contract code integrity (Level 3). For Level 1, we show that six structural features of onchain execution (oracle execution divergence, endogenous recovery, full information run dynamics, timelock constrained governance, oracle manipulation and congestion driven liquidation failure) break canonical TradFi analogies and generate depositor loss channels absent from standard credit frameworks. Vault credit risk metrics translate these channels into measurable risk components which are aggregated into a vault credit score. The empirical contribution is an implementable estimation architecture for credit risk metrics, including required onchain data, identification strategies for core parameters, partial identification bounds and a coherent stress scenario methodology. The results have direct implications for vault risk management and for minimum transparency standards necessary for depositor risk assessment. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.17579 |
| By: | Jorge Pozo (Banco Central de Reserva del Perú.) |
| Abstract: | This article studies the impact of deposit dollarization on credit dollarization through the natural hedging and the excessive risk-taking hannels. We develop a theoretical model that helps us to describe both channels and how these determine the direction in which deposit dollarization might affect credit dollarization. The model shows that through the natural hedging channel, deposit dollarization positively affects credit dollarization, while through the excessive bank risk-taking channel, deposit dollarization negatively affects credit dollarization. Using regional data of credits and deposits in Peru, we find evidence of these two channels, with the natural hedging channel being the dominant one. In addition, we reveal that les credit market competition and high FX uncertainty amplify the role of the excessive bank risk-taking channel. |
| Keywords: | Bank risk-taking, dollarization, foreign exchange rate risk, limited liability, deposit insurance, bank competition |
| JEL: | D41 D42 E44 G11 G21 |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:rbp:wpaper:2025-013 |
| By: | Ana Isabel Castillo Pereda |
| Abstract: | This study extends the Gai-Kapadia framework, originally developed for interbank contagion, to assess systemic risk and default cascades in global equity markets. We analyze a 30 asset network comprising Brazilian and developed market equities over the period 2015-2026, constructing exposure based financial networks from price co-movements. Threshold filtering (theta = 0.3 and theta = 0.5) is applied to isolate significant interconnections. Cascade dynamics are analyzed through a combination of deterministic propagation and stochastic Monte Carlo simulations (n = 1000) under varying shock intensities. The results show that the system exhibits strong global resilience, with a negligible probability of large scale failure, while maintaining localized vulnerability within highly clustered subnetworks. In particular, shocks lead to an average of 1.0 failed asset for single shocks and 2.0 for simultaneous shocks, indicating limited propagation below a critical threshold. Network analysis reveals a clear structural asymmetry: Brazilian assets display high clustering (Ci approx 0.8-1.0) and dense connectivity, which amplifies local shock propagation, whereas developed market assets exhibit lower connectivity (Ci approx 0.2-0.5), limiting systemic spread. Tail risk analysis, based on empirical CCDF and Hill estimators, confirms the presence of heavy tailed loss distributions, particularly in emerging markets, reinforcing their exposure to extreme events. These findings demonstrate that systemic risk arises from the interaction between network topology and tail behavior, rather than from isolated asset characteristics. The proposed framework provides a scalable and empirically grounded approach for stress testing and systemic risk assessment, offering relevant insights for regulators and portfolio managers in increasingly interconnected financial markets. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.19796 |
| By: | Asmerilda Hitaj; Elisa Mastrogiacomo; Ilaria Peri; Marcelo Righi |
| Abstract: | This paper develops an axiomatic framework for ranking metrics, a general class of functionals for evaluating and ordering financial or insurance positions. Unlike traditional risk-adjusted performance measures-such as the Sharpe ratio, RAROC, or Omega-that express reward per unit of risk, ranking metrics assign each position a performance level rather than a normalized return. Relying on monotonicity and a new property called cash-quasiconcavity, we derive representation results linking ranking metrics to families of acceptance sets and risk measures, extending the theory of acceptability indices. Classical ratios arise as special cases, while new examples-based on expected-loss, Lambda-quantile, and bibliometric indices-illustrate the framework's flexibility. Empirical applications to portfolio ranking and climate-risk insurance demonstrate its practical relevance. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.16438 |
| By: | Xia Han; Bin Li |
| Abstract: | This paper studies optimal insurance design under asymmetric information in a Stackelberg framework, where a monopolistic insurer faces uncertainty about both the insured's risk attitude, captured by a risk-aversion parameter, and the insured's risk type, characterized by the loss distribution. In particular, when the risk type is unobservable, we allow the risk-aversion parameter to depend on the risk type. We construct a menu of contracts that maximizes the mean-variance utilities of both parties under the expected-value premium principle, subject to a truth-telling constraint that ensures the truthful revelation of private information. We show that when risk attitude is private information, the optimal coverage takes the form of excess-of-loss insurance with linear pricing in terms of the risk loading (defined as the premium minus the expected loss), designed to screen risk preferences. In contrast, when risk type is unobserved, we restrict the coverage function to an excess-of-loss form and derive an ordinary differential equation that characterizes the optimal risk loading. Under mild conditions, we establish the existence and uniqueness of the solution. The results show that equilibrium contracts exhibit nonlinear pricing with decreasing risk loadings, implying that higher-risk individuals face lower risk loadings in order to induce self-selection. Finally, numerical illustrations demonstrate how parameter values and the distributions of unobserved heterogeneity affect the structure of optimal contracts and the resulting pricing schedule. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.15881 |
| By: | Inês Lindoso, Andreas Schrimpf, Vladyslav Sushko and Toma Tomov; Andreas Schrimpf; Vladyslav Sushko; Toma Tomov |
| Abstract: | The sensitivity of fund returns to exchange rates, once underlying asset returns are accounted for, provides a measure of funds' exposure to currency risk, ie their de facto hedge ratio. Bond funds have high and stable hedge ratios, though with some sensitivity to hedging costs. Equity funds' hedging is volatile and consistent with opportunistic currency speculation. In the run-up to April 2025, equity funds with low hedge ratios attracted most inflows and outperformed those with high hedge ratios, but this relation flipped following "Liberation Day". |
| Date: | 2026–04–22 |
| URL: | https://d.repec.org/n?u=RePEc:bis:bisblt:123 |
| By: | Valente Fernanda; Chen Yujia; Calabrese Raffaella; Cowling Marc; Alessi Lucia (European Commission - JRC) |
| Abstract: | Small and Medium-sized Enterprises (SMEs) are the backbone of the European economy. However, theimpact of nature-related risks on SME creditworthiness is still largely unexplored. To address this gap, we incorporate indicators of nature-related risks - namely the Biodiversity Intactness Index, the HumanFootprint Index, and ENCORE scores - into an Extreme Gradient Boosting (XGBoost) credit scoring modelestimated on millions of securitised SME loans. Our results show that both physical and transition riskindicators significantly improve the predictive performance of SME credit models, highlighting the impor-tance of integrating nature-related risk metrics into financial risk assessment frameworks. |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:jrs:wpaper:202601 |
| By: | Shintaro Mori |
| Abstract: | Can contagion be inferred from aggregated default data? We study this as a problem of identifiability, asking whether contagion generates components in default count distributions that remain distinct from those induced by macroeconomic fluctuations. We compare three dependence structures: cumulative contagion in the Lo-Davis model, threshold-type contagion in the Torri model, and common-factor dependence in the Vasicek model. Under an i.i.d. specification, the Vasicek model provides the best overall fit, especially in the tail, indicating that a smooth mixture structure captures annual default clustering more effectively than threshold-type contagion at the aggregate level. We then allow the default probability to vary across years through a hierarchical specification. Under this extension, most of the variation in annual default counts is explained by cross-year movements in default conditions rather than by within-year contagion. What remains, however, depends on the interaction mechanism. In the Torri model, threshold-type contagion does not leave a stable component that can be separated from macroeconomic heterogeneity after aggregation. In the Lo-Davis model, by contrast, a small but persistent component remains visible in both the variance decomposition and the tail behavior. These results clarify when contagion can still be inferred from coarse-grained data and when it is effectively absorbed into macroeconomic variation. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.18118 |
| By: | Arshia Ghasemi; Siqi Shao; R. A. Serota |
| Abstract: | We analyze historic S&P500 multi-day returns: from daily returns to those accumulated over up to ten days. Despite symmetry breaking between gains and losses in the distribution of returns, resulting in its positive mean and negative skew, realized variance (volatility squared) exhibits remarkably good linear dependence on the number of days of accumulation. Mean of the distribution also shows near perfect linear dependence as well. We analyze this phenomenon both analytically and numerically using a modified Jones-Faddy skew t-distribution. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.15519 |
| By: | Sebastien Lleo; Wolfgang Runggaldier |
| Abstract: | We study a benchmarked risk-sensitive portfolio problem in a factor-based setting to bring together three strands of the literature: benchmarked risk-sensitive investment management, the Kuroda-Nagai change-of-measure method, and the free energy-entropy duality of Dai Pra et al. (1996). We show that the duality yields a direct solution of the benchmarked problem by reformulating it as a linear-quadratic-Gaussian stochastic differential game under a suitable equivalent probability measure, with an entropic regularization. The resulting value function is quadratic, the optimal controls are explicit affine feedback maps, and the optimal allocation admits two complementary interpretations: as a fractional Kelly strategy and as a Kelly portfolio adjusted via the entropic regularization. This formulation, therefore, contributes both a direct analytical route to the solution and a clearer interpretation of risk sensitivity, thereby embedding the classical Kuroda-Nagai change-of-measure approach within a more general framework. An added benefit of this formulation is that it is suitable for implementation via an RL algorithm. A simple implementation on U.S. equity data illustrates the tractability of the framework and numerically confirms the equivalence of the two approaches. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.15463 |
| By: | Useong Shin |
| Abstract: | Put-call parity is a terminal-payoff identity; quoted residuals against traded futures are near zero. Yet enforcing parity is path-dependent, exposing arbitrageurs to daily settlement, margin, and finite capital. Using minute-level NBBO data on S&P 500 and Russell 2000 options, I extract option-implied discount factors, compare them with the OIS curve, and construct an annualized carry gap. A reduced-form specification centered on a volatility times sqrt(tau) path-risk term links the carry gap to implementation risk, trading frictions, and financial conditions, with coefficient signs stable across leave-one-year-out validation. The carry gap is an implementation wedge invisible in price space but systematic in carry space. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.19604 |
| By: | Nikeethan Selvaratnam; Dorinel Bastide; Cl\'ement Fernandes; Wojciech Pieczynski |
| Abstract: | Predicting future operational risk losses gives rise to a significant challenge due to the heterogeneous and time-dependent structures present in real-world data. Furthermore, stress test exercises require examining the relationship with operational losses. To capture such relationship, we propose to use an extension of Hidden Markov Models to multivariate observations. This model introduces a third auxiliary variable designed to accommodate the economic covariates in the time-series data. We detail the unique aspects of operational risk data and describe how model calibration is achieved via the Expectation-Maximization (EM) algorithm. Additionally, we provide the calibration results for the various risk-event types and analyze the relevance of the inclusion of the macroeconomic covariates. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.21734 |
| By: | Kundan Mukhia; Imran Ansari; Md. Nurujjaman |
| Abstract: | We identify a robust structural signature of stock markets during exogenous shock events by analyzing collective return dynamics across G5 countries. Using Random Matrix Theory, we introduce the complexity gap, defined as the difference between the normalized largest eigenvalue and the average pairwise correlation, to quantify changes in market structure. This measure reveals a consistent three-phase pattern across multiple shocks, including the 2025 U.S. tariff event, the COVID-19 crisis, and country-specific shocks in Japan and China during 2024. Before a shock, markets show a positive complexity gap, reflecting a rich structure with multiple interacting factors. During shocks, the gap collapses to near zero, signaling strong synchronization under a single dominant mode. Post-shock recovery follows a nonmonotonic path: an initial widening (a false recovery), a temporary recollapse, and final sustained restoration. This pattern holds at both market and sector levels and across global and local shocks. Ordinal entropy analysis confirms the same sequence of collapse and false recovery in directional diversity. We further demonstrate that lower complexity gap values predict higher future portfolio volatility, especially after shocks, establishing its value as a state-dependent risk indicator. For investors, initial gap widening may mislead, while sustained widening signals genuine structural stabilization. These findings reveal a robust structural signature governing financial market dynamics during crisis and recovery periods. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.19107 |
| By: | Sergio A. Correia; Stephan Luck; Emil Verner |
| Abstract: | Do banks fail because of runs or because they become insolvent? Answering this question is central to understanding financial crises and designing effective financial stability policies. Long-run historical evidence reveals that the root cause of bank failures is usually insolvency. The importance of bank runs is somewhat overstated. Runs matter, but in most cases they trigger or accelerate failure at already weak banks, rather than cause otherwise sound banks to fail. |
| Keywords: | bank runs; bank failures; deposit insurance; bank regulation; bank supervision |
| JEL: | H0 |
| Date: | 2026–04–16 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednls:103048 |
| By: | Kim Christensen; Wenjing Liu; Zhi Liu; Yoann Potiron |
| Abstract: | We study a new measure of codependency in the second moment of a continuous-time multivariate asset price process, which we name the realized copula of volatility. The statistic is based on local volatility estimates constructed from high-frequency asset returns and affords a nonparametric estimator of the empirical copula of the latent stochastic volatility. We show consistency of our estimator with in-fill asymptotic theory, either with a fixed or increasing time span. In the latter setting, we derive a functional central limit theorem for the empirical process associated with the measurement error of the time-invariant marginal copula of volatility. We also develop a goodness-of-fit test to evaluate hypotheses about the shape of the latter. In a simulation study, we demonstrate that our estimator is a good proxy of both the empirical and marginal copula of volatility, even with a moderate amount of high-frequency data recorded over a relatively short sample. The goodness-of-fit test is found to exhibit size control and excellent power. We implement our framework on high-frequency transaction data from futures contracts that track the U.S. equity and treasury bond market. A Gumbel copula is found to offer a near-perfect bind between the realized variance processes in these data. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.15811 |
| By: | Alexander Karaivanov (Simon Fraser University) |
| Abstract: | I analyze the role of prepayment in a dynamic risk-sharing setting with information and commitment frictions. An insurance platform contracts with a risk-averse agent with stochastic income. Part of the income can be withheld in escrow as a prepayment. I consider three endogenously incomplete markets settings with different obstacles to risk sharing: limited commitment, private information due to hidden income, and both. I show that prepayment alleviates the limited commitment problem and improves the degree of risk sharing, including possibly to full insurance depending on the model parameters; however, prepayment is ineffective in the private information settings. In the setting with both limited commitment and private information frictions, I show that private information is the binding constraint. |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:sfu:sfudps:dp26-06 |
| By: | Revant Nayar; Dnyanesh Kulkarni; El Mehdi Ainasse |
| Abstract: | We develop \emph{Topological Risk Parity} (TRP), a tree-based portfolio construction approach intended for long/short, market neutral, factor-aware portfolios. The method is motivated by the dominance of passive/factor flows that naturally create a tree-like structure in markets. We introduce two implementation variants: (i) a rooted minimum-spanning-tree allocator, and (ii) a market/sector-anchored variant referred to here as \emph{Semi-Supervised TRP}, which imposes SPY as the root node and the 11 sector ETFs as the second layer. In both cases, the key object is a sparse rooted topology extracted from a correlation-distance graph, together with a propagation law that maps signed signals into portfolio weights. Relative to classical Hierarchical Risk Parity (HRP), TRP is non-binary and designed for signed cross-sectional signals and hedged long-short portfolios: it preserves signal direction while using return-dependence geometry to shape exposures. It accounts for the fact that there is imperfect correlation between parent and child nodes, and thus does not propagate weights entirely to the children. We can also impose economically motivated hierarchy that involves industries, sub-industries or factors, etc. This makes it much more robust to macroeconomic shocks and crises, where within-cluster correlations might spike. These features make TRP well suited for market-neutral, equity stat-arb or L/S trend-type strategies, where enforcing neutrality or limiting exposures at the market, sector or factor level is extremely important. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.16773 |
| By: | Irene Aldridge; Jolie An; Riley Burke; Michael Cao; Chia-Yi Chien; Kexin Deng; Ruipeng Deng; Yichen Gao; Olivia Guo; Shunran He; Zheng Li; George Lin; Weihang Lin; Percy Lyu; Alex Ng; Qi Wang; Hanxi Xiao; Dora Xu; Yuanyuan Xue; Sheng Zhang; Sirui Zhang; Yun Zhang; Sirui Zhao; Xiaolong Zhao; Yihan Zhao; Waner Zheng |
| Abstract: | The emergence of agentic artificial intelligence (AI) represents a fundamental transformation in financial markets, characterized by autonomous systems capable of reasoning, planning, and adaptive decision-making with minimal human intervention. This comprehensive survey synthesizes recent advances in agentic AI across multiple dimensions of financial operations, including system architecture, market applications, regulatory frameworks, and systemic implications. We examine how agentic AI differs from traditional algorithmic trading and generative AI through its capacity for goal-oriented autonomy, continuous learning, and multi-agent coordination. Our analysis shows that while agentic AI offers substantial potential for enhanced market efficiency, liquidity provision, and risk management, it also introduces novel challenges related to market stability, regulatory compliance, interpretability, and systemic risk. Through a systematic review of foundational research, technical architectures, market applications, and governance frameworks, this survey provides scholars and practitioners with a structured understanding of how agentic AI is reshaping financial markets and identifies critical research directions for ensuring that these systems enhance both operational efficiency and market resilience. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.21672 |
| By: | Ruichao Jiang; Long Wen |
| Abstract: | Chitra et al. (2025) claim that Target Weight Mechanism (TWM) in Perpetual Demand Lending Pools (PDLPs) can lower the delta of the portfolio under certain condition. We prove that their condition is self-contradictory. Furthermore, we prove an impossibility result that no TWM can lower the delta uniformly. |
| Date: | 2026–04 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2604.16467 |