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on Risk Management |
| By: | Osadchiy, Maksim |
| Abstract: | This paper proposes a small perturbation two-factor model designed to capture granularity risk, extending the classical Vasicek Asymptotic Single Risk Factor (ASRF) portfolio loss model. By applying the Lyapunov Central Limit Theorem, we demonstrate that, for small Herfindahl-Hirschman Index (HHI) values, granularity risk – conditional on market risk – is approximately proportional to a standard normal random variable. Instead of analyzing heterogeneous portfolios directly, we focus on a homogeneous portfolio subject to a small perturbation induced by granularity risk. We propose the Vasicek-Herfindahl portfolio loss distribution, which extends the Vasicek portfolio loss distribution to account for portfolio concentration. Utilizing this distribution, we derive closed-form granularity adjustments for the probability density function (PDF) and cumulative distribution function (CDF) of portfolio loss, as well as for Value at Risk (VaR) and Expected Shortfall (ES). We compare our primary results with existing findings and validate them through Monte Carlo simulations. |
| Keywords: | Credit portfolio model; Granularity adjustment; Value at Risk; Expected Shortfall |
| JEL: | C46 G21 G32 |
| Date: | 2025–03–31 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:125027 |
| By: | Sidharth J ((corresponding author) Madras School of Economics, Chennai, Tamil Nadu, India, 600025) |
| Abstract: | Liquidity is very important for the stock market as it effects the portfolio decisions of investors and influences future outlook of the economy. Liquidity is especially important to withstand economic shocks and to facilitate faster recovery. The study examines the impact of two significant market crises, the 2008 Global Financial Crisis and the COVID-19 pandemic, on liquidity in the Indian stock market. Data for 655 companies listed at the National Stock Exchange (NSE) is utilized over a time period of 17 years from 2005 to 2022 to analyze multiple dimensions of liquidity. Preliminary results suggest that both crises had a substantial effect on market liquidity. The 2008 financial crisis exhibits a more pronounced and prolonged impact compared to COVID-19 pandemic. The severity of 2008 financial crisis surpassed that of COVID-19 across all liquidity dimensions. Trading volumes saw an uptrend during COVID-19 crisis, contrasting with decline in all other liquidity measures. Conversely, the 2008 financial crisis witnessed reductions in trading volume alongside broader declines in liquidity measures. |
| Keywords: | Liquidity; 2008 Financial Crisis; COVID-19 pandemic; Indian Stock Market |
| JEL: | G01 G10 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:mad:wpaper:2025-283 |
| By: | Alessandro Ramponi; Sergio Scarlatti |
| Abstract: | We propose a credit risk model for portfolios composed of green and brown loans, extending the ASRF framework via a two-factor copula structure. Systematic risk is modeled using potentially skewed distributions, allowing for asymmetric creditworthiness effects, while idiosyncratic risk remains Gaussian. Under a non-uniform exposure setting, we establish convergence in quadratic mean of the portfolio loss to a limit reflecting the distinct characteristics of the two loan segments. Numerical results confirm the theoretical findings and illustrate how value-at-risk is affected by portfolio granularity, default probabilities, factor loadings, and skewness. Our model accommodates differential sensitivity to systematic shocks and offers a tractable basis for further developments in credit risk modeling, including granularity adjustments, CDO pricing, and empirical analysis of green loan portfolios. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.12510 |
| By: | Nan Guo; Ruodu Wang; Chenxi Xia; Jingping Yang |
| Abstract: | Credit ratings are widely used by investors as a screening device. We introduce and study several natural notions of risk consistency that promote prudent investment decisions in the framework of Choquet rating criteria. Three closely related notions of risk consistency are considered: with respect to risk aversion, the asset pooling effect, and the benefit of portfolio diversification. These notions are formulated either under a single probability measure or multiple probability measures. We show how these properties translate between rating criteria and the corresponding risk measures, and establish a hierarchical structure among them. These findings lead to a full characterization of Choquet risk measures and Choquet rating criteria satisfying risk consistency properties. Illustrated by case studies on collateralized loan obligations and catastrophe bonds, some classes of Choquet rating criteria serve as useful alternatives to the probability of default and expected loss criteria used in practice for rating financial products. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.13435 |
| By: | Yin Luo; Sheng Wang; Javed Jussa |
| Abstract: | By capturing outliers, volatility clustering, and tail dependence in the asset return distribution, we build a sophisticated model to predict the downside risk of the global financial market. We further develop a dynamic regime switching model that can forecast real-time risk regime of the market. Our GARCH-DCC-Copula risk model can significantly improve both risk- and alpha-based global tactical asset allocation strategies. Our risk regime has strong predictive power of quantitative equity factor performance, which can help equity investors to build better factor models and asset allocation managers to construct more efficient risk premia portfolios. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.12587 |
| By: | Jagdish Gnawali; Abootaleb Shirvani; Svetlozar T. Rachev |
| Abstract: | We explore credit risk pricing by modeling equity as a call option and debt as the difference between the firm's asset value and a put option, following the structural framework of the Merton model. Our approach proceeds in two stages: first, we calibrate the asset volatility using the Black-Scholes-Merton (BSM) formula; second, we recover implied mean return and probability surfaces under the physical measure. To achieve this, we construct a recombining binomial tree under the real-world (natural) measure, assuming a fixed initial asset value. The volatility input is taken from a specific region of the implied volatility surface - based on moneyness and maturity - which then informs the calibration of drift and probability. A novel mapping is established between risk-neutral and physical parameters, enabling construction of implied surfaces that reflect the market's credit expectations and offer practical tools for stress testing and credit risk analysis. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.12694 |
| By: | Jiawei Xu (School of Management and Engineering, Digital Finance Key Laboratory of Jiangsu Province, Nanjing University, 22 Hankou Road, Nanjing, Jiangsu 210093, China); Elie Bouri (School of Business, Lebanese American University, Lebanon); Libing Fang (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa) |
| Abstract: | The US and China maintain deep economic ties, yet geopolitical tensions, especially during events such as the trade war, exert significant influence on their financial markets. This study examines how US-China tensions, as captured by the US-China Tension Index (UCT), affect the correlation between US and Chinese stock markets and stock market volatility using a DCC-DAGARCH-MIDAS model. Unlike prior studies that consider geopolitical risk and trade war shocks separately or give the same weight to positive and negative shocks of UCT, our approach jointly models asymmetric short-term volatility, macro-driven long-term variance, dynamic inter-market correlations, and assigns different weights to positive and negative shocks of UCT. The findings show that heightened tensions lead to stronger co-movements in return volatility, with effects becoming more immediate during the trade war. Beyond aggregate indices, we analyze the multi-tiered structure of the Chinese stock market, covering small and medium-sized enterprises (SMEs), blue-chip stocks, and technology-focused stocks. The results show that sensitivities vary across China's stock market indices, where SME index displays the most sensitive to UCT. These results provide practical insights for investors and policymakers aiming to manage risks in an increasingly geopolitically sensitive environment. |
| Keywords: | US-China Tensions, Geopolitical Tensions, US and Chinese Stock Returns and Volatility, DCC-DA-GARCH-MIDAS |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:pre:wpaper:202522 |
| By: | Marcella Lucchetta (Ca' Foscari University of Venice) |
| Abstract: | In the wake of the 2023 Silicon Valley Bank collapse and the 2025 tariff shocks, systemic risk poses a serious threat to global financial stability. We propose a three-period general equilibrium (GE) model that accounts for bank heterogeneity and crisis-driven migration. Our model distinguishes between retail banks, with a marginal expected shortfall of -0.019, and investment banks at -0.045, successfully reducing systemic risk and lowering the overall expected shortfall from -0.032 to -0.029. Unlike complex DSGE frameworks, our model offers clear insights into the vulnerabilities of Silicon Valley Bank and the impact of tariffs. We recommend Basel III-aligned policies, including capital relief and targeted stress tests, and propose real-time crisis prediction tools. This model serves as a vital resource for policymakers and investors, helping them navigate systemic crises and address the challenges posed by "too big to fail" institutions. |
| Keywords: | Bank Heterogeneity, Systemic Risk, Crisis Migration, General Equilibrium, Marginal Expected Shortfall |
| JEL: | G21 G01 E44 G28 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ven:wpaper:2025:05 |
| By: | Timofei Belenko; Georgii Vosorov |
| Abstract: | In this paper, we propose an analytical method to compute the collateral liquidation probability in decentralized finance (DeFi) stablecoin single-collateral lending. Our approach models the collateral exchange rate as a zero-drift geometric Brownian motion, converts it into a regular zero-drift Brownian motion, and employs the reflection principle to derive the liquidation probability. Unlike most existing methods that rely on computationally intensive simulations such as Monte Carlo, our formula provides a lightweight, exact solution. This advancement offers a more efficient alternative for risk assessment in DeFi platforms. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.08100 |
| By: | Riccardo Manghi (LUISS Guido Carli University); Daniela Di Cagno (LUISS Guido Carli University) |
| Abstract: | This study investigates individual differences in catastrophic risk perception using Cumulative Prospect Theory (CPT) through a laboratory experiment. The choice of CPT allows us to introduce a basic "addendum" to traditional EUT evaluations of these kinds of risks. We analyze the drivers of risk perception through a laboratory measure of CPT based on experimental data, where possible drivers include sociodemographic factors, psychological characteristics, and psychometric variables such as past experience. We define in this setting an interesting aspect that is a peculiar characteristic of extreme risks: the so-called shared burden effect, where individuals perceive the same risks as less severe if they affect a larger share of the collectivity. External validity is provided by examining whether laboratory-elicited risk perception predicts real-world extreme risk assessments. |
| Keywords: | risk perception, catastrophic risk, prospect theory, experimental economics, shared burden effect |
| JEL: | D81 C91 |
| Date: | 2025–06–23 |
| URL: | https://d.repec.org/n?u=RePEc:rtv:ceisrp:605 |
| By: | Dylan Hogg; Hossein Jebeli |
| Abstract: | Assessing insolvency dynamics is essential for evaluating the financial health of non-financial corporations and mitigating macroeconomic and financial stability risks. This study leverages a newly created Statistics Canada dataset linking insolvency records with firm-level financial data to develop a robust framework for monitoring insolvency risk. We employ two complementary approaches: a univariate threshold method that establishes critical financial ratio benchmarks and a multivariate econometric model that accounts for interactions among financial indicators. These methods produce debt-at-risk measures that enhance risk assessment by combining simplicity with analytical depth. Finally, we apply these metrics to timely firm-level data, enabling continual monitoring of financial vulnerabilities. |
| Keywords: | Credit and credit aggregates; Econometric and statistical methods; Financial stability; Firm dynamics |
| JEL: | G33 L20 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:bca:bocadp:25-010 |
| By: | Marcella Lucchetta (Ca' Foscari University of Venice) |
| Abstract: | Recent financial crises have exposed the vulnerabilities of heterogeneous banking models, with investment banks facing greater risks than their retail counterparts due to volatile trading portfolios. This study introduces a three-period general equilibrium model that integrates bank heterogeneity with a novel crisis-induced adaptation mechanism, enabling banks to shift toward resilient retail models during economic distress. Unlike traditional frameworks that assume uniform bank behavior or rely on static analyses, this model captures the dynamic structural adjustments that mitigate systemic risk, offering a nuanced perspective on financial stability. Drawing on comprehensive U.S. and European banking data, the framework is validated across diverse shocks, including regional bank failures and global market disruptions. The findings inform regulatory strategies aligned with Basel III principles, addressing the unique challenges of mid-sized banks while tackling emerging risks from fintech innovations and climate exposures. By bridging micro-level bank dynamics with macro-level stability, the study provides a robust tool for regulators navigating the complexities of modern financial systems, with implications for both domestic and global banking landscapes. |
| Keywords: | Bank Heterogeneity, Systemic Risk, Crisis Adaptation Policy, Marginal Expected Shortfall, Financial Stability, Fintech, Climate Risk |
| JEL: | G21 G01 E44 G28 Q54 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ven:wpaper:2025:08 |
| By: | Erum Iftikhar; Wei Wei; John Cartlidge |
| Abstract: | Blockchain-based decentralised lending is a rapidly growing and evolving alternative to traditional lending, but it poses new risks. To mitigate these risks, lending protocols have integrated automated risk management tools into their smart contracts. However, the effectiveness of the latest risk management features introduced in the most recent versions of these lending protocols is understudied. To close this gap, we use a panel regression fixed effects model to empirically analyse the cross-version (v2 and v3) and cross-chain (L1 and L2) performance of the liquidation mechanisms of the two most popular lending protocols, Aave and Compound, during the period Jan 2021 to Dec 2024. Our analysis reveals that liquidation events in v3 of both protocols lead to an increase in total value locked and total revenue, with stronger impact on the L2 blockchain compared to L1. In contrast, liquidations in v2 have an insignificant impact, which indicates that the most recent v3 protocols have better risk management than the earlier v2 protocols. We also show that L1 blockchains are the preferred choice among large investors for their robust liquidity and ecosystem depth, while L2 blockchains are more popular among retail investors for their lower fees and faster execution. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.12855 |
| By: | Dhanashree Somani (Department of Statistics, University of Florida, 230 Newell Drive, Gainesville, FL, 32601, USA); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Sayar Karmakar (Department of Statistics, University of Florida, 230 Newell Drive, Gainesville, FL, 32601, USA); Vasilios Plakandaras (Department of Economics, Democritus University of Thrace, Komotini, Greece) |
| Abstract: | The objective of this paper is to forecast volatilities of the stock returns of China, France, Germany, Italy, Spain, the United Kingdom (UK), and the United States (US) over the daily period of January 2010 to February 2025 by utilizing the information content of newspapers articles-based indexes of supply bottlenecks. We measure volatility by employing the interquantile range, estimated via an asymmetric slope autoregressive quantile regression fitted on stock returns to derive the conditional quantiles. In the process, we are also able to obtain estimates of skewness, kurtosis, lower- and upper-tail risks, and incorporate them into our linear predictive model, alongside leverage. Based on the shrinkage estimation using the Lasso estimator to control for overparameterization, we find that the model with moments outperform the benchmark model that includes both own- and cross-country volatilities, but the performance of the former, is improved further when we incorporate the role of the metrics of supply constraints for all the 7 countries simultaneously. These findings carry significant implications for investors. |
| Keywords: | Supply Bottlenecks, Stock Market Volatility, Asymmetric Autoregressive Quantile Regression, Lasso Estimator, Forecasting |
| JEL: | C22 C53 E23 G15 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:pre:wpaper:202521 |
| By: | Stephen G. Cecchetti; Jeremy C. Kress; Kermit L. Schoenholtz |
| Abstract: | In 2023, US regulators proposed the “Basel Endgame, ” a long-awaited overhaul of bank capital requirements. The proposal aimed to bring the United States into compliance with international standards established by the Basel Committee on Banking Supervision in response to the 2008 Global Financial Crisis. However, fierce industry opposition to what banks viewed as a costly increase in capital requirements effectively killed the proposal. In this essay, we describe the purpose of bank capital and the history of international standard-setting in bank regulation. We then highlight the most important aspects of the Basel Endgame, as well as the arguments for and against adopting the rule. We show that the debate unnecessarily conflated two distinct questions: (1) whether the United States should comply with international regulatory standards, and (2) whether the United States should raise large banks’ capital requirements. While there are strong grounds to answer both questions in the affirmative, they need not be addressed together. That is, the United States can implement international standards in a capital-neutral manner to preserve global cooperation in bank regulation, leaving the separate question of raising capital requirements for another day. |
| JEL: | G21 G28 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33982 |
| By: | Koch, Melanie; Menkhoff, Lukas |
| Abstract: | Entrepreneurs tend to be risk tolerant but is higher risk tolerance always better? In a sample of about 2100 small businesses, we find an inverted U-shaped relation between risk tolerance and profitability. This relationship holds in a simple bilateral regression, and even after controlling for a large set of individual and business characteristics. Apparently, one major transmission goes from risk tolerance via investments to profits. This is quite robust as it applies for both past and planned investments. Considering business survival, we show, first, that less profitable businesses leave the market while moderately risk tolerant entrepreneurs survive more often. Second, the high risk-low profit part of the U-shaped relation seems to disappear among businesses being 4 years and older, indicating that such inferior risk-profit combinations disappear over time. These findings are important for the concept of business readiness trainings as the motivation (and ability) to take risks should potentially be accompanied by some warning that taking too much risk can be detrimental to long-term business success. |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:ifwkie:319532 |
| By: | Luca Cappellina (Ca' Foscari University of Venice; Gruppo BCC Iccrea Banca); Domenico Sartore (Ca' Foscari University of Venice) |
| Abstract: | This paper proposes a novel approach to modeling the volumes of Non-Maturity Deposits (NMDs), a key component of interest rate and liquidity risk in the banking book. Using a multivariate logistic regression model with autocorrelated data, we estimate the probability of cash-out (PoC) from the stable portion of NMDs. Uniquely, our model relies solely on variables included in the six supervisory interest rate shock scenarios prescribed by the Basel Committee on Banking Supervision, ensuring consistency with regulatory stress testing frameworks and avoiding misalignment with macroeconomic scenario assumptions. Empirical results confirm that financial market conditions—particularly short-term interest rates and the yield curve slope—are significant drivers of withdrawal behavior, underlining the role of the interest rate channel in monetary policy transmission. Seasonal patterns and the impact of the COVID-19 crisis are also found to influence depositors' behavior. By isolating the contribution of supervisory variables, our approach supports both risk management practices and regulatory compliance, offering a practical and forwardlooking tool for banks in assessing core deposit stability under stressed conditions. |
| Keywords: | Non-Maturity Deposits (NMDs), Interest Rate Risk, Liquidity Risk, Core Deposits, Logistic Regression, Supervisory Scenarios, Yield Curve Slope, Probability of Cash-out (PoC), Basel Framework, Stress Testing |
| JEL: | C25 C33 E43 G21 G28 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:ven:wpaper:2025:06 |
| By: | Lu, Lanxin (Central Bank of Ireland); Fiedor, Pawel (Central Bank of Ireland) |
| Abstract: | In this note, we explore whether the way fund managers invest can lead to risks that affect the entire financial system. We found that managers of bond funds in Ireland tend to invest in riskier assets when interest rates drop, possibly to achieve higher returns. In contrast, managers of equity funds do the opposite. We also discovered that bond funds receive more money from investors when interest rates are higher. Furthermore, equity funds attract more investments when they take on more risk. Our analysis is based on how fund managers allocate their investments, revealing their willingness to take risks. When fund managers seek higher returns by taking more risks, it can make the financial system more vulnerable and increase the chance of severe economic downturns. These insights are crucial for monitoring financial stability and guiding policies for non-bank financial institutions, which have become more significant since more assets have shifted from banks to non-banks after 2008. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:cbi:fsnote:2/fs/25 |
| By: | Marco Rodrigues |
| Abstract: | We construct an aggregator for a family of Snell envelopes in a nondominated framework. We apply this construction to establish a robust hedging duality, along with the existence of a minimal hedging strategy, in a general semi-martingale setting for American-style options. Our results encompass continuous processes, or processes with jumps and non-vanishing diffusion. A key application is to financial market models, where uncertainty is quantified through the semi-martingale characteristics. |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.14553 |
| By: | Gene Amromin; Kenechukwu E. Anadu; Falk Bräuning; Amy Chapel; Rebecca Chmielewski; Meeoak Cho; Patricia K. Cowperthwait; Lorenzo Garza; Cindy E. Hull; Siobhan Sanders; Sam Schulhofer-Wohl; Brett Solimine; Emma Weiss |
| Abstract: | Technology-focused Third-Party Service Providers (TPSPs) have become important players in the operations of financial institutions and the financial markets. This paper summarizes micro- and macro-prudential regulatory frameworks in place to address risks that TPSPs pose to the financial system. The key takeaways are as follows: First, in the U.S., TPSPs operate under limited comprehensive prudential regulatory oversight, aimed primarily at ensuring that their products are safe and resilient on an ongoing basis. Second, while banks rely on multiple TPSPs and hundreds of their services daily for their core banking businesses, U.S. banking supervisors have limited direct visibility into these activities and risks they may pose. Third, although the existing U.S. regulatory framework has some systemic risk considerations, there is no macroprudential structure in place for TPSP risks. Official bodies in other jurisdictions have developed macroprudential frameworks or high-level guidance to address TPSP risks, but their implementation in major economies is nascent at best. Finally, TPSPs are likely an important source of systemic vulnerability for financial institutions and financial markets, although vulnerabilities may be difficult to discern due to a need to assess the criticality of each activity performed by TPSPs and the concentration of TPSPs within that activity. |
| Keywords: | financial stability; third-party service providers; cyber risks |
| JEL: | G10 G23 G28 |
| Date: | 2025–07–01 |
| URL: | https://d.repec.org/n?u=RePEc:fip:feddwp:101200 |
| By: | Antoine Jacquier; Adriano Oliveri Orioles; Zan Zuric |
| Abstract: | We propose a tractable extension of the rough Bergomi model, replacing the fractional Brownian motion with a generalised grey Brownian motion, which we show to be reminiscent of models with stochastic volatility of volatility. This extension breaks away from the log-Normal assumption of rough Bergomi, thereby making it a viable suggestion for the Equity Holy Grail -- the joint SPX/VIX options calibration. For this new (class of) model(s), we provide semi-closed and asymptotic formulae for SPX and VIX options and show numerically its potential advantages as well as calibration results. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.08623 |
| By: | Yu Awaya (University of Rochester); Jihwan Do (Yonsei University); Makoto Watanabe (Kyoto University) |
| Abstract: | We construct a model of bubbles where an asset can be used as collateral primarily due to higher-order uncertainty: while both a lender and a borrower know that the intrinsic value of the asset is low, they may still believe that a greater fool exists who will purchase it at a much higher price. We show that such bubbles can lead to inefficient overinvestment under certain conditions. Using this framework, we also examine the impacts of macroprudential policies, as well as other regulatory measures such as interest rate hikes and the resolution of uncertainty. |
| Keywords: | collateral; higher-order uncertainty; speculative bubbles |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:yon:wpaper:2025rwp-252 |
| By: | Serena Fatica (European Commission - Joint Research Centre and Mofir.); Tommaso Oliviero (Università di Napoli Federico II, CSEF, Mofir and Cefes); Michela Rancan (University of Milan) |
| Abstract: | Using a large sample of European enterprises, we document that companies’ default probability is significantly larger when they experience negative end-of- the year equity (zombie status) in the year prior to default. Zombie firms are more likely to default in the short run in countries with more efficient judicial insolvency procedures. To establish a causal link between judicial efficiency and the default probability of zombie firms, we exploit a reform of the court districts in Italy that generates exogenous variation in trial lengths. This country-level analysis corroborates the findings of a cleansing effect of judicial efficiency that limits the persistence of zombie firms in the economy. |
| Keywords: | default; zombie firms; SMEs; EU-27; judicial efficiency. |
| JEL: | G33 K22 L25 O52 |
| Date: | 2025–03–15 |
| URL: | https://d.repec.org/n?u=RePEc:sef:csefwp:747 |
| By: | Tim de Silva; Eugene Larsen-Hallock; Adam Rej; David Thesmar |
| Abstract: | This paper studies expectations formation when the underlying process has fat tails. Using a large sample of firm sales growth expectations, we document three facts: (i) the relationship between forecast revisions and future forecast errors is strongly non-linear, (ii) the distribution of sales growth has fat tails, and (iii) extreme values of sales growth tend to mean-revert. We formally show that these three facts are consistent with a model in which the underlying process is non-Gaussian, but forecasters fail to recognize this fully. We estimate this model and show it quantitatively explains our three facts. Finally, we show the model is consistent with evidence from an online forecasting experiment where the underlying process is non-Gaussian and the non-linearity in the momentum of stock returns. |
| JEL: | D84 D91 G41 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33808 |
| By: | Matteo Crosignani; Martin Hiti |
| Abstract: | We introduce the first comprehensive publicly available dataset on county-level damages, injuries, and fatalities from natural disasters in the U.S. and present a few facts on the economic and human costs of extreme climate events. Our source is the National Oceanic and Atmospheric Administration’s Storm Events Database, which reports losses for geographic areas largely defined based on meteorological science. We map these areas to counties using geographic tools together with the spatial distribution of population, housing stock, and economic activity. Our estimates are particularly accurate for severe disasters. The Losses from Natural Disasters dataset is regularly updated at https://newyorkfed.org/research/policy/n atural-disaster-losses. |
| Keywords: | natural disasters; physical risk |
| JEL: | H12 H71 Q54 |
| Date: | 2025–07–01 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fednsr:101189 |
| By: | Ryota IWAMOTO; Takunori ISHIHARA; Takanori IDA |
| Abstract: | This study empirically investigates the differences in risk preferences and loss aversion between humans and generative AI. We conduct a nationwide online survey of 4, 838 individuals and generate AI responses under identical conditions by using personas constructed from demographic attributes. The results show that in gain domains, both humans and the AI select risk-averse options and exhibit similar preference patterns. However, in loss domains, AI shows a stronger risk-loving tendency and responds more sharply to individual attributes such as gender, age, and income. We retrain the AI by fine-tuning it based on human choice data. After fine-tuning, the AI’s preference distribution moves closer to that of humans, with loss-related decisions showing the greatest improvement. Using Wasserstein distance, we also confirm that fine-tuning reduces the behavioral gap between AI and humans. |
| Keywords: | bias, bias, loss aversion, risk preference, generative AI, persona, fine-tuning, Wasserstein distance |
| JEL: | D91 C91 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:kue:epaper:e-25-006 |