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on Risk Management |
| By: | Sumedh Gupte; Prashanth L. A.; Sanjay P. Bhat |
| Abstract: | We consider the problems of estimation and optimization of two popular convex risk mea- sures: utility-based shortfall risk (UBSR) and Optimized Certainty Equivalent (OCE) risk. We extend these risk measures to cover possibly unbounded random variables. We cover prominent risk measures like the entropic risk, expectile risk, monotone mean-variance risk, Value-at-Risk, and Conditional Value-at-Risk as few special cases of either the UBSR or the OCE risk. In the context of estimation, we derive non-asymptotic bounds on the mean absolute error (MAE) and mean-squared error (MSE) of the classical sample average approximation (SAA) estimators of both, the UBSR and the OCE. Next, in the context of optimization, we derive expressions for the UBSR gradient and the OCE gradient under a smooth parameterization. Utilizing these expres- sions, we propose gradient estimators for both, the UBSR and the OCE. We use the SAA estimator of UBSR in both these gradient estimators, and derive non-asymptotic bounds on MAE and MSE for the proposed gradient estimation schemes. We incorporate the aforementioned gradient estima- tors into a stochastic gradient (SG) algorithm for optimization. Finally, we derive non-asymptotic bounds that quantify the rate of convergence of our SG algorithm for the optimization of the UBSR and the OCE risk measure |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2506.01101 |
| By: | NING, Donglai; YASUDA, Yukihiro |
| Abstract: | This study investigates whether biodiversity risk disclosures reduce stock price crash risk, exploiting the Taskforce on Nature-related Financial Disclosures’ (TNFD) early adopter announcement as a quasi-natural experiment. Using a difference-in-differences framework, we find that TNFD adoption significantly reduces crash risk among Japanese firms. Our findings highlight biodiversity risk disclosures’ unique and complementary role, underscoring their importance in enhancing market transparency and mitigating downside risk. |
| Keywords: | Biodiversity Risk, Difference-in-Differences, the Taskforce on Nature-related Financial Disclosures, Stock Price Crash Risk, Japan |
| JEL: | G14 G30 M40 Q50 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:hit:hcfrwp:g-1-28 |
| By: | Marín Díazaraque, Juan Miguel; Romero, Eva; Lopes Moreira Da Veiga, María Helena |
| Abstract: | This paper introduces a new asymmetric stochastic volatility model designed to capture how both the sign and magnitude of past shocks influence future volatility. The proposed Leverage Propagation Stochastic Volatility (LPSV) model extends traditional formulations by allowing the feedback mechanism to evolve over time, offering a more persistent and realistic representation of leverage effects than standard asymmetric stochastic volatility models. Based on the intuition that the impact of negative shocks on volatility unfolds gradually, rather than instantaneously, the model encodes this ``leverage propagation'' directly in its structure. Under Gaussian assumptions, we establish stationarity conditions and derive closed-form expressions for variance, kurtosis, and a novel leverage propagation function that quantifies delayed transmission of asymmetry. A Monte Carlo study confirms the robustness of Bayesian inference via Markov chain Monte Carlo (MCMC), even under heavy-tailed shocks. In empirical applications, the LPSV model captures volatility clustering and asymmetric persistence more effectively than competing alternatives, using daily financial returns from the German DAX and U.S. S&P 500. Moreover, the model captures prolonged volatility responses to non-financial shocks -illustrated through PM2.5 air pollution data from Madrid during Saharan dust events, demonstrating its broader relevance for environmental volatility modelling. These findings highlight the versatility of the model to trace the dynamics of delayed volatility sensitive to sign in different domains where understanding the persistence of risk is crucial. |
| Keywords: | Asymmetric volatility; Bayesian inference; Heavy tails; Leverage effect; Volatility feedback; Stochastic volatility |
| Date: | 2025–05–26 |
| URL: | https://d.repec.org/n?u=RePEc:cte:wsrepe:47005 |
| By: | Torben G. Andersen (Department of Finance, Northwestern University); Yi Ding (Faculty of Business Administration, University of Macau); Viktor Todorov (Department of Finance, Northwestern University); Seunghyeon Yu (Department of Finance, Northwestern University) |
| Abstract: | We develop nonparametric estimates for tail risk in the cross-section of asset prices at high frequencies. We show that the tail behavior of the crosssectional return distribution depends on whether the time interval contains a systematic jump event. If so, the cross-sectional return tail is governed by the assets’ exposures to the systematic event while, otherwise, it is determined by the idiosyncratic jump tails of the stocks. We develop an estimator for the tail shape of the cross-sectional return distribution that display distinct properties with and without systematic jumps. Empirically, we provide evidence for symmetric cross-sectional return tails at high-frequency that exhibit nontrivial and persistent time series variation. A hypothesis of equal cross-sectional return tail shapes during periods with and without systematic jump events is strongly rejected by the data. |
| Keywords: | Jumps, high-dimensional analysis, high-frequency data, infinitely divisible distribution, linear factor model |
| JEL: | C12 C13 C14 C58 |
| Date: | 2025–06 |
| URL: | https://d.repec.org/n?u=RePEc:boa:wpaper:202531 |
| By: | Josef Sveda |
| Abstract: | How much capital is truly enough to shield banks from default? Understanding this threshold is critical for designing regulatory frameworks that balance financial stability with economic growth. This paper develops a reverse stress testing framework to assess the resilience of the banking sector under extreme credit shocks. It focuses on the conditions under which banks facing distress transition from bail-ins to government bailouts, using the Czech banking sector as a case study. Our findings indicate that a capital ratio of 23.5% is sufficient to absorb losses comparable to the most severe stress experienced during the Global Financial Crisis (GFC), preventing the need for public intervention. Moreover, we show that regulatory capital buffers are well-calibrated, covering losses up to the second-largest stress event observed in the GFC. Unlike many reverse stress testing approaches, our model explicitly accounts for the dynamic effects of risk-weighted asset (RWA) adjustments, revealing that static RWA assumptions may overestimate capital resilience. These results provide critical insights for policymakers, suggesting that capital adequacy requirements remain well-calibrated but warrant further scrutiny regarding how risk weights evolve under stress conditions. |
| Keywords: | Bail-in, bailout, banking crisis, capital adequacy, capital ratio, resilience, reverse stress test |
| JEL: | E58 G01 G18 G21 G28 G32 G33 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:cnb:wpaper:2025/5 |
| By: | Arno Botha; Tanja Verster; Bernard Scheepers |
| Abstract: | In the pursuit of modelling a loan's probability of default (PD) over its lifetime, repeat default events are often ignored when using Cox Proportional Hazard (PH) models. Excluding such events may produce biased and inaccurate PD-estimates, which can compromise financial buffers against future losses. Accordingly, we investigate a few subtypes of Cox-models that can incorporate recurrent default events. Using South African mortgage data, we explore both the Andersen-Gill (AG) and the Prentice-Williams-Peterson (PWP) spell-time models. These models are compared against a baseline that deliberately ignores recurrent events, called the time to first default (TFD) model. Models are evaluated using Harrell's c-statistic, adjusted Cox-Sell residuals, and a novel extension of time-dependent receiver operating characteristic (ROC) analysis. From these Cox-models, we demonstrate how to derive a portfolio-level term-structure of default risk, which is a series of marginal PD-estimates at each point of the average loan's lifetime. While the TFD- and PWP-models do not differ significantly across all diagnostics, the AG-model underperformed expectations. Depending on the prevalence of recurrent defaults, one may therefore safely ignore them when estimating lifetime default risk. Accordingly, our work enhances the current practice of using Cox-modelling in producing timeous and accurate PD-estimates under IFRS 9. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.01044 |
| By: | Wilson Kang (California Polytechnic State University, San Luis Obispo, U.S.A); Russell Smyth (Department of Economics, Monash University, Clayton, Australia); Joaquin Vespignani (Tasmanian School of Business and Economics, University of Tasmania, Australia) |
| Abstract: | This paper applies and extends the macroeconomic fragility framework for studying the effects of supply chain disruptions, proposed by Acemoglu and Tahbaz-Salehi (2024), to incorporate the role of stockpiling, which stabilizes critical mineral markets and reduce macroeconomic fragility. A key prediction of the macroeconomic fragility framework is that equilibrium supply chains are inherently fragile, meaning that even small shocks can trigger cascading supply chain breakdowns that can significantly magnify the discontinuous response of aggregate supply to shocks, leading to higher volatility and prices of critical minerals. We highlight the important role that the non-technical risk premium plays in magnifying global supply chain shocks in the specific case of critical minerals. Using a mixed-frequency Structural VAR model with agnostic sign restrictions and newly constructed data on non-technical risk premiums, we estimate the impact of supply chain disruption, the non-technical risk premium and their interaction on the prices and volatility of six critical minerals. We find that global supply chain disruptions, magnified by non-technical risk premiums, significantly increase critical mineral prices and price volatility for all six critical minerals studied, indicating inefficient outcomes which we interpret as macroeconomic fragility in critical minerals markets. |
| Keywords: | Global Supply Chain Disruption, Critical Minerals, Non-technical Risk Premiums Macroeconomic Fragility |
| JEL: | F62 Q43 Q30 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:mos:moswps:2025-09 |
| By: | Martin Hodula; Lukas Pfeifer |
| Abstract: | The Czech Republic provides a unique setting to examine the effects of loan moratoria during the COVID-19 pandemic, as it combined broad-access legislative moratoria with stricter, eligibility-based bank moratoria. Using detailed loan-level data from the Czech mortgage market, we find that legislative moratoria were predominantly precautionary, addressing a wide range of borrowers, whereas bank moratoria were primarily utilized by higher-risk borrowers facing solvency challenges. Post-moratoria, we observe limited materialization of credit risk, which was nearly twice as high for bank moratoria compared to legislative moratoria. Stricter borrower-based regulations (LTV, DTI, and DSTI limits) implemented prior to the pandemic were associated with lower moratoria uptake and reduced post-moratoria arrears. These findings underscore the effectiveness of combining universal legislative moratoria with targeted bank measures to balance immediate economic relief and long-term financial stability. |
| Keywords: | Borrower-based measures, COVID-19 economic policy, credit risk mitigation, loan moratoria, mortgage arrears |
| JEL: | E44 G21 G28 G51 |
| Date: | 2025–01 |
| URL: | https://d.repec.org/n?u=RePEc:cnb:wpaper:2025/1 |
| By: | Cheung , Lydia (Auckland University of Technology); Galimberti , Jaqueson (Asian Development Bank); Vermeulen, Philip (University of Canterbury) |
| Abstract: | Using around 1 million repeat sales, we show idiosyncratic risk in real house price appreciation is time-varying, depends negatively on the initial house price, varies across locations, and decreases with the holding period. These systematic movements in idiosyncratic risk can be explained by time and regional variations in market thinness and differences in information quality across markets. We find borrowing costs and deposit requirements have offsetting effects on risk. Higher interest rates are associated with lower idiosyncratic pricing, while tighter deposit requirements are associated with shorter holding periods, which are subject to a higher risk. Finally, we find the systematic variations in idiosyncratic housing risk tend to be positively associated with excess capital returns. However, the risk–return trade-off emerges only through risk differences across house prices and holding periods, while idiosyncratic risk differences across time and regions are not rewarded in excess capital returns. |
| Keywords: | idiosyncratic risk; house prices; housing markets |
| JEL: | G10 R10 |
| Date: | 2025–05–30 |
| URL: | https://d.repec.org/n?u=RePEc:ris:adbewp:0783 |
| By: | Michiko Ogaku |
| Abstract: | This paper investigates whether an ex-ante welfare-maximising risk allocation rule can be implemented among many participants. Specifically, we investigate the applicability of the price and choose mechanism proposed by Echenique and N\'u\~nez(2025) to risk allocation problems. While their mechanism implements Pareto optimal allocations in finite choice sets, we consider extending it to an infinite choice set of feasible risk-sharing allocations. This paper asks whether an ex-ante welfare-maximising risk allocation rule can indeed be implemented for a large group. Specifically, we study the price and choose (P&C) mechanism of Echenique and N\'u\~nez(2025) in a risk-sharing setting. In P&C, players sequentially set prices for each possible alternative; the last player chooses an alternative, provided that all previous players receive the prices they set. Echenique and N\'u\~nez(2025) show that, for finite choice sets, the mechanism implements any Pareto optimal allocation in the subgame-perfect Nash equilibrium. Our setting differs in one crucial respect: the choice set is infinite. Each alternative is a feasible allocation of total risk, and each player sets a Lipschitz-continuous price function on this infinite set. We show that the P&C mechanism can still be extended to implement the allocation that maximises the sum of players' utilities, even with an infinite choice set. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.04122 |
| By: | Cappelen, Alexander W. (Dept. of Economics, Norwegian School of Economics and Business Administration); Sørensen, Erik Ø. (Dept. of Economics, Norwegian School of Economics and Business Administration); Tungodden, Bertil (Dept. of Economics, Norwegian School of Economics and Business Administration); Xu, Xiaogeng (Dept. of Finance and Economics, Hanken School of Economics) |
| Abstract: | Using a large, probability-based online panel representative of the general population in Norway, we examine how varying delays in the revelation of uncertainty affect risk-taking on behalf of others. We find a precisely estimated null effect of revelation delay on the average proportion choosing a lottery over a safe alternative. A hierarchical Bayesian model of rank-dependent utility also reveals no differences in underlying decision processes across conditions. However, we do observe a paternalistic tendency: participants place greater weight on their own risk preferences than on those they believe others to hold. |
| Keywords: | Risk-taking; decision-making; uncertainty |
| JEL: | C91 D63 D81 |
| Date: | 2025–05–23 |
| URL: | https://d.repec.org/n?u=RePEc:hhs:nhheco:2025_013 |
| By: | Ronald Heijmans; Ellen van der Woerd |
| Abstract: | This paper presents a methodology to detect potential failing participants in large value payment systems and measure the intraday impact of outages, considering Liquidity, Systemic, and Receiver Impacts. Medium and high risk thresholds are es- tablished to create a combined risk indicator. Outages of large banks can be detected within 10 minutes, while smaller banks may take over 30 minutes. Impact and risk levels vary by the size of the bank and the start time of the outage. Large banks can reach high-risk levels in 30 minutes, highlighting the need for timely detection, whereas smaller banks rarely reach high-risk levels. |
| Keywords: | Financial market infrastructures; TARGET2; liquidity risk; operational risk; systemic risk; financial stability |
| JEL: | E42 E50 E58 E59 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:dnb:dnbwpp:836 |
| By: | Alberto Isgut (Macroeconomic Policy and Financing for Development Division, United Nations Economic and Social Commission for Asia and the Pacific) |
| Abstract: | Managing currency risk is a serious challenge for developing countries that are not able to finance most of their financing needs in local currency. Currency risk can increase substantially the cost of servicing sovereign debts, potentially decreasing fiscal space for much needed investments in sustainable development, and lead to a higher default risk. This can make financing sustainable development and climate ambitions too expensive. Thus, given the urgency of scaling up finance for the achievement of the 2030 Agenda and the goals of the Paris Agreement, addressing the risk of foreign currency financing should be an urgent priority. To reduce exposure to foreign currency debt and associated currency risk, this policy brief discusses the importance of developing local currency bond markets and adopting sound macroeconomic policies. In addition, it highlights the importance of developing hedging tools to mitigate currency risk. |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:unt:pbmpdd:pb131 |
| By: | Shanyan Lai |
| Abstract: | This paper proposes an innovative Transformer model, Single-directional representative from Transformer (SERT), for US large capital stock pricing. It also innovatively applies the pre-trained Transformer models under the stock pricing and factor investment context. They are compared with standard Transformer models and encoder-only Transformer models in three periods covering the entire COVID-19 pandemic to examine the model adaptivity and suitability during the extreme market fluctuations. Namely, pre-COVID-19 period (mild up-trend), COVID-19 period (sharp up-trend with deep down shock) and 1-year post-COVID-19 (high fluctuation sideways movement). The best proposed SERT model achieves the highest out-of-sample R2, 11.2% and 10.91% respectively, when extreme market fluctuation takes place followed by pre-trained Transformer models (10.38% and 9.15%). Their Trend-following-based strategy wise performance also proves their excellent capability for hedging downside risks during market shocks. The proposed SERT model achieves a Sortino ratio 47% higher than the buy-and-hold benchmark in the equal-weighted portfolio and 28% higher in the value-weighted portfolio when the pandemic period is attended. It proves that Transformer models have a great capability to capture patterns of temporal sparsity data in the asset pricing factor model, especially with considerable volatilities. We also find the softmax signal filter as the common configuration of Transformer models in alternative contexts, which only eliminates differences between models, but does not improve strategy-wise performance, while increasing attention heads improve the model performance insignificantly and applying the 'layer norm first' method do not boost the model performance in our case. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.01575 |
| By: | Margaret M. Jacobson |
| Abstract: | Endogenously optimistic beliefs about future house prices can account for the increase, time-path, and volatility of house prices in the U.S. housing boom of the 2000s without shocks to housing preferences. In a general equilibrium model with incomplete markets and aggregate risk, heterogeneous agents endogenously form beliefs about future house prices in response to shocks to fundamentals. When fundamentals like credit conditions loosen, agents can only partially revise up their beliefs, resulting in increasingly optimistic beliefs that are consistent with both novel and existing empirical evidence. Because endogenous beliefs are sensitive to policy interventions, how beliefs are formed in housing booms has direct implications for prudential policy. |
| Keywords: | Housing boom; Aggregate risk; Heterogeneous agents; Incomplete information |
| JEL: | E20 E30 C68 R21 |
| Date: | 2025–01–31 |
| URL: | https://d.repec.org/n?u=RePEc:fip:fedgfe:100028 |
| By: | Amal, Nair; Sabyasachi, Tripathi |
| Abstract: | Geopolitical risks affect global economies, particularly the services trade, which makes up 20% of total trade. Understanding these risks is key because they can impact inflation, GDP growth, the financial sector, and supply chains. The aim of the research is to examine the worldwide pattern of geopolitical risk and its significance on the trade of services, to measure how much global disputes and risk, as explained in the GPR Index, impact service trade, and to know how strong a regulatory system helps to mitigate the impacts of such threats. The Pseudo-Poisson Maximum Likelihood is used in the study to assess the adverse impact of geopolitical risks on international service trade using a panel dataset comprising 44 countries from 2011 to 2021. The study finds a negative effect of geopolitical factors on service trade and further finds that an effective regulatory system can reduce the negative impact of such geopolitical disruptions. The results may assist policymakers in gauging the economic cost of geopolitical risk and in designing policies to neutralise its disruptive potential. |
| Keywords: | Geopolitical Risk, Service trade, PPML, Regulatory Quality |
| JEL: | F1 F13 F63 |
| Date: | 2025–04–10 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:124670 |
| By: | Alejandro Ferrer (BANCO DE ESPAÑA); Ana Molina (BANCO DE ESPAÑA) |
| Abstract: | In a liquidity stress scenario, banks may need to urgently monetise assets to meet deposit outflows. This can be done by either selling the assets or using them as collateral in financing operations. In a context of crisis, executing these financing transactions with private counterparties may be constrained, making the transactions with the central bank particularly relevant. The sale of assets classified at amortised cost will result in the materialisation of any accumulated unrealised losses, adversely affecting the banks’ profitability. Alternatively, central bank financing prevents the materialisation of unrealised losses, which, however, limit the amount of financing that can be obtained through this mechanism, as it is based on the market value of the collateral provided. In this case, the increase in interest expenses associated with the funds obtained from the central bank will also impact the bank’s profitability. All these negative effects on profitability ultimately affect solvency and can exacerbate the initial liquidity crisis. Thus, there is a link between liquidity stress and solvency deterioration in which unrealised losses play a significant role. Drawing on Spanish banking system data, we examine this connection in various simulation exercises, looking at its nature and strength under each mechanism (asset sale and pledge). The data show a growing weight of government debt classified at amortised cost on the balance sheets of Spanish banks in recent years, as well as an increase in the associated unrealised losses during the period of rising interest rates, especially in 2022, and in 2023. |
| Keywords: | government debt, debt held at amortised cost, unrealised losses, LCR, liquidity stress, central bank liquidity facilities |
| JEL: | E43 G17 G21 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:bde:opaper:2509e |
| By: | Anah\'i Rodr\'iguez-Mart\'inez; Silvia Bartolucci; Francesco Caravelli; Victoria Landaberry; Pierpaolo Vivo; Fabio Caccioli |
| Abstract: | Understanding how credit flows through inter-firm networks is critical for assessing financial stability and systemic risk. In this study, we introduce DebtStreamness, a novel metric inspired by trophic levels in ecological food webs, to quantify the position of firms within credit chains. By viewing credit as the ``primary energy source'' of the economy, we measure how far credit travels through inter-firm relationships before reaching its final borrowers. Applying this framework to Uruguay's inter-firm credit network, using survey data from the Central Bank, we find that credit chains are generally short, with a tiered structure in which some firms act as intermediaries, lending to others further along the chain. We also find that local network motifs such as loops can substantially increase a firm's DebtStreamness, even when its direct borrowing from banks remains the same. Comparing our results with standard economic classifications based on input-output linkages, we find that DebtStreamness captures distinct financial structures not visible through production data. We further validate our approach using two maximum-entropy network reconstruction methods, demonstrating the robustness of DebtStreamness in capturing systemic credit structures. These results suggest that DebtStreamness offers a complementary ecological perspective on systemic credit risk and highlights the role of hidden financial intermediation in firm networks. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.01326 |
| By: | Ted Berg; Neth Karunamuni; Daniel Stemp |
| Abstract: | The OFR Hedge Fund Monitor shows that hedge fund repurchase agreement (repo) borrowing in Q4 2024 declined after eight consecutive quarters of growth. |
| Date: | 2025–06–02 |
| URL: | https://d.repec.org/n?u=RePEc:ofr:ofrblg:25-04 |
| By: | Berg, Tobias; Haselmann, Rainer |
| Abstract: | The European financial system faces significant risks from excessive bank lending to the real estate sector. Historical trends show a strong link between real estate credit booms and banking crises. Current data indicate that real estate loans constitute a substantial share of banks' corporate loan portfolios, with varying risk levels across countries. Key drivers include expansionary ECB policies and regulatory incentives favouring mortgage lending. Strengthening oversight, improving data collection, and adjusting regulations are essential for financial stability. This document was provided/prepared by the Economic Governance and EMU Scrutiny Unit at the request of the ECON Committee. |
| Keywords: | Real Estate Landing, Banking Crisis, Financial Stability |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:safewh:319064 |
| By: | Collado Fernandez, Victor; Méndez, Fernando J.; Minguez Solana, Roberto |
| Abstract: | Engineering design must fulfill various requirements to guarantee the safety and functionality of structures. Often, critical conditions are associated with extreme events, such as floods or extreme winds. Therefore, a thorough analysis of these extreme conditions is essential to ensure structural reliability. Typically, designing structures involves generating sampled data based on historical records. However, it is frequent that this sampled data does not accurately represent the extreme-event regime observed historically. To address this issue, it is necessary to introduce an upper-tail sampling correction technique that effectively models extreme regimes, thereby reducing associated risks. This paper proposes a straightforward correction method and demonstrates its application through various examples, illustrating how the methodology aligns sampled extreme values more closely with historical data. |
| Keywords: | Extreme-value distribution; Sampling correction; Return period; Point-in-time distribution |
| Date: | 2025–05–20 |
| URL: | https://d.repec.org/n?u=RePEc:cte:wsrepe:46849 |
| By: | Shovon Sengupta (SUAD_SAFIR - SUAD - Sorbonne University Abu Dhabi, BITS Pilani - Birla Institute of Technology and Science, Fidelity Investments); Tanujit Chakraborty (SUAD_SAFIR - SUAD - Sorbonne University Abu Dhabi); Sunny Kumar Singh (BITS Pilani - Birla Institute of Technology and Science) |
| Abstract: | Forecasting consumer price index (CPI) inflation is of paramount importance for both academics and policymakers at central banks. This study introduces the filtered ensemble wavelet neural network (FEWNet) to forecast CPI inflation, tested in BRIC countries. FEWNet decomposes inflation data into high- and low-frequency components using wavelet transforms and incorporates additional economic factors, such as economic policy uncertainty and geopolitical risk, to enhance forecast accuracy. These wavelet-transformed series and filtered exogenous variables are input into downstream autoregressive neural networks, producing the final ensemble forecast. Theoretically, we demonstrate that FEWNet reduces empirical risk compared to fully connected autoregressive neural networks. Empirically, FEWNet outperforms other forecasting methods and effectively estimates prediction uncertainty due to its ability to capture non-linearities and long-range dependencies through its adaptable architecture. Consequently, FEWNet emerges as a valuable tool for central banks to manage inflation and enhance monetary policy decisions. |
| Keywords: | Inflation forecasting Wavelets Neural networks Empirical risk minimization Conformal prediction intervals |
| Date: | 2024–09 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05056934 |
| By: | Kim Kaivanto |
| Abstract: | In policy debates concerning the governance and regulation of Artificial Intelligence (AI), both the Precautionary Principle (PP) and the Innovation Principle (IP) are advocated by their respective interest groups. Do these principles offer wholly incompatible and contradictory guidance? Does one necessarily negate the other? I argue here that provided attention is restricted to weak-form PP and IP, the answer to both of these questions is “No.†The essence of these weak formulations is the requirement to fully account for type-I error costs arising from erroneously preventing the innovation’s diffusion through society (i.e. mistaken regulatory redlighting) as well as the type-II error costs arising from erroneously allowing the innovation to diffuse through society (i.e. mistaken regulatory green-lighting). Within the Signal Detection Theory (SDT) model developed here, weak-PP red-light (weak-IP green-light) determinations are optimal for sufficiently small (large) ratios of expected type-I to type-II error costs. For intermediate expected cost ratios, an amber-light ‘wait-and-monitor’ policy is optimal. Regulatory sandbox instruments allow AI testing and experimentation to take place within a structured environment of limited duration and societal scale, whereby the expected cost ratio falls within the ‘wait-and-monitor’ range. Through sandboxing regulators and innovating firms learn more about the expected cost ratio, and what respective adaptations — of regulation, of technical solution, of business model, or combination thereof, if any — are needed to keep the ratio out of the weak-PP red-light zone. |
| Keywords: | artificial intelligence, foundational AI, general-purpose AI systems, AI governance, precautionary principle, innovation principle, countervailing risk, scientific uncertainty, signal detection theory, misclassification costs, discriminability, ROC curve, de minimis risk, trust and polarization, protected values, non-comparable values, continuity axiom, regulatory sandboxes |
| JEL: | D81 O31 O33 O38 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:lan:wpaper:423283411 |
| By: | Grebe, Leonard Nils |
| Abstract: | The replication crisis in financial economics highlights significant challenges to the credibility of empirical research, particularly in the study of stock market anomalies. This dissertation aims to enhance the consistency of previous findings by revisiting event-driven and seasonal value effects. Across six individual studies, the findings suggest that conflicting results do not necessarily indicate biases or model misspecifications but rather reflect the influence of underlying factors such as dataset composition, methodological choices, and evolving market conditions. Using a combination of event studies, regression analyses, meta-analyses, and artificial intelligence (AI) modeling, this research explores the impact of study design on research outcomes. The first focus is on replicating investor risk adjustments through established event study methodologies applied to three recent edge case events. The first event study validates established financial theories regarding the systematic risks associated with regulatory institutions. The second challenges the evaluation of cyber risks in the context of unintended software outages. The third event study contributes new insights to the identification of sustainable companies. In summary, these studies reveal systematic patterns in market reactions to event-driven value effects while highlighting that individual edge cases may challenge prior findings, suggesting the presence of additional underlying factors. Unlike the widely standardized methodology used to examine event-driven value effects, seasonal stock market anomalies, such as the day-of-the-week effect, are characterized by heterogeneous study designs, which often result in inconsistent findings. A primary study and a meta-analysis confirm that methodological choices significantly influence the observed weekly patterns of day-dependent returns. The findings suggest that dynamic market conditions, as reflected in divergent study designs, contribute to these inconsistencies. As a result, the final study introduces the "Uncertainty Structure Hypothesis" (USH), identifying market uncertainty as a key factor shaping weekly patterns in daily returns and offering an additional explanation for the replication crisis. In conclusion, this research underscores the importance of data selection, methodological choices, and the integration of advanced techniques such as meta-analyses and AI-driven nonlinear models. By investigating the drivers of the replication crisis, the dissertation enhances the reliability of financial research. Importantly, the findings suggest extending theoretical frameworks to better include the complexities of dynamic and uncertain market environments. |
| Date: | 2025–05–20 |
| URL: | https://d.repec.org/n?u=RePEc:dar:wpaper:154892 |
| By: | Biais, Bruno; Gersbach, Hans; Rochet, Jean-Charles; von Thadden, Ernst-Ludwig; Villeneuve, Stéphane |
| Abstract: | We analyze dynamic capital allocation and risk sharing between a principal and many agents, who privately observe their output. The state variables of the mechanism design problem are aggregate capital and the distribution of continuation utilities across agents. This gives rise to a Bellman equation in an infinite dimensional space, which we solve with mean-field techniques. We fully characterize the optimal mechanism and show that the level of risk agents must be exposed to for incentive reasons is decreasing in their initial outside utility. We extend classical welfare theorems by showing that any incentive- constrained optimal allocation can be implemented as an equilibrium allocation, with appropriate money issuance and wealth taxation by the principal. |
| Date: | 2025–05–22 |
| URL: | https://d.repec.org/n?u=RePEc:tse:wpaper:130553 |
| By: | Diego Bonelli (BANCO DE ESPAÑA); Berardino Palazzo (FEDERAL RESERVE BOARD OF GOVERNORS); Ram Yamarthy (FEDERAL RESERVE BOARD OF GOVERNORS) |
| Abstract: | Using inflation swap prices, we study how changes in expected inflation affect firm-level credit spreads and equity returns, and uncover evidence of a time-varying inflation sensitivity. In times of “good inflation, ” when inflation news is perceived by investors to be more positively correlated with real economic growth, movements in expected inflation substantially reduce corporate credit spreads and raise equity valuations. Meanwhile in times of “bad inflation, ” these effects are attenuated and the opposite may even occur. These dynamics naturally arise in an equilibrium asset pricing model with a time-varying inflation-growth covariance and persistent macroeconomic expectations. |
| Keywords: | inflation sensitivity, time variation, asset prices, stock-bond correlation |
| JEL: | E31 E44 G12 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:bde:wpaper:2525 |
| By: | Marc Fleurbaey (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Stéphane Zuber (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | How can social prospects be evaluated and compared when there may be a risk on i) the actual allocations that people will receive, ii) the existence of these future people, and iii) their preferences? This paper investigates this question, which can arise when considering policies, such as climate policy, that affect people who do not yet exist. We start from the observation that there is no social ordering that meets minimal requirements of fairness, social rationality, and respect for people's ex ante preferences. We explore three ways around this impossibility. First, if we drop the ex ante Pareto requirement, we can obtain fair ex post criteria that take an (arbitrary) expected utility of an equally-distributed equivalent level of well-being. Second, if the social ordering is not an expected utility, we can obtain fair ex ante criteria that evaluate uncertain individual prospects with a certaintyequivalent measure of well-being. Third, if we accept that interpersonal comparisons rely on VNM utility functions even in absence of risk, we can construct expected utility social orderings that satisfy of a version of Pareto ex ante. |
| Keywords: | Fairness, Social risk, Intergenerational equity |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:halshs-05053424 |
| By: | Harrison Hong; Serena Ng; Jiangmin Xu |
| Abstract: | We estimate the return of climate adaptation by modeling the uncertain impact of global warming for extreme weather. Unexpected arrivals elevate extreme-weather risk, which leads households and firms to adapt and thereby lowering the damage of each subsequent arrival. Our approach provides country-specific estimates of disaster risk as extreme-weather events unfold, and state-dependent marginal effects of extreme-weather damage on economic growth. Applying our approach to cyclones and heatwaves from 1980-2019, average country income in 2019 is several percent lower absent state-dependent adaptation. Adaptation becomes significantly more valuable in the long run as the uncertainty regarding extreme weather is resolved. |
| JEL: | O1 O40 O47 Q50 Q54 Q56 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33824 |
| By: | Othmane Zarhali; Cecilia Aubrun; Emmanuel Bacry; Jean-Philippe Bouchaud; Jean-Fran\c{c}ois Muzy |
| Abstract: | The Nested factor model was introduced by Chicheportiche et al. to represent non-linear correlations between stocks. Stock returns are explained by a standard factor model, but the (log)-volatilities of factors and residuals are themselves decomposed into factor modes, with a common dominant volatility mode affecting both market and sector factors but also residuals. Here, we consider the case of a single factor where the only dominant log-volatility mode is rough, with a Hurst exponent $H \simeq 0.11$ and the log-volatility residuals are ''super-rough'', with $H \simeq 0$. We demonstrate that such a construction naturally accounts for the somewhat surprising stylized fact reported by Wu et al. , where it has been observed that the Hurst exponents of stock indexes are large compared to those of individual stocks. We propose a statistical procedure to estimate the Hurst factor exponent from the stock returns dynamics together with theoretical guarantees of its consistency. We demonstrate the effectiveness of our approach through numerical experiments and apply it to daily stock data from the S&P500 index. The estimated roughness exponents for both the factor and idiosyncratic components validate the assumptions underlying our model. |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2505.02678 |
| By: | Benyounes Rahouti (Université Mohammed Premier [Oujda] = Université Mohammed Ier) |
| Abstract: | This article proposes to present a reflection on theapprehension of uncertainty in a particular and unprecedented environment, such as that of the 2020 health crisis. Today, with multidisciplinary, theoretical and intellectual proliferation has made the concept of uncertainty particularly polysemic and a source of confusion. The attribution of a precise and universal definition remains very problematic. Attempts to define uncertainty in different historicalcontexts have come up against epistemological approaches, methods of analysis, and even specific and very disparate intervention languages, creating a rich but sometimes controversial conceptual landscape. On this basis, this article attempts to explore in depth the meaning of the concept given the hostile and unpredictable context of the Covid-19 pandemic period. The interest of such a perspective is to provide contextual and interpretative insight into this test of apprehension uncertainty. The line of argument developed in this paper reveals the value of apprehending the concept's full complexity through the lens of an ignorance continuum, spanning near-certainty to absolute ignorance. Transcending traditional dichotomous boundaries of uncertainty (measurable vs. immeasurable), this progressive and gradual vision makes it possible to visualize the variety of unknowns that range from the partially controllable to utterly unpredictable unknown. |
| Abstract: | Cet article propose de restituer une réflexion portant sur l'appréhension de l'incertitude dans un environnement particulier et inédit, tel que celui de la crise sanitaire de 2020.Aujourd'hui, avec la pluridisciplinarité, le foisonnement théorique et intellectuel a rendu le concept d'incertitude particulièrement polysémique et source de confusion. L'attribution d'une définition précise et universelle demeure très problématique. Les tentatives de cerner l'incertitude, au travers de différents contextes historiques, se sont heurtées à des approches épistémologiques, des méthodes d'analyse, voire des langages d'intervention spécifiques et très disparates, créant un paysage conceptuel riche, mais parfois controversé. Sur ce fondement, le présent article tente d'explorer en profondeur le sens du concept compte tenu du contexte hostile et imprévisible qu'a revêtu la période pandémiquedeCovid-19.L'enjeu d'une telle perspective est d'apporter un éclairage contextuel et interprétatif à cette épreuve d'appréhension de l'incertitude. L'argumentaire déployé dans ce papier révèle l'intérêt de saisir toute la complexité du concept à travers l'optique du continuum d'inconnaissance, oscillant entre la quasi-certitude et l'ignorance totale. Transcendant les frontières dichotomiques traditionnelles de l'incertitude (mesurable vs. non mesurable), cette vision progressive et graduelle permet de visualiser la variété d'inconnues qui s'étend de l'inconnu partiellement maîtrisable à celui qui demeure hors de contrôle et de toute possibilité de prévision. |
| Keywords: | Uncertainty, risk, Covid-19, black swan, continuum of unknowing, Incertitude, risque, cygne noir, continuum d'inconnaissance |
| Date: | 2025–04–21 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05043795 |
| By: | Brooke Hathhorn; Michael T. Owyang |
| Abstract: | While recession probabilities can provide a snapshot of current economic conditions, relying on them to judge whether a recession is underway can be risky. |
| Keywords: | recession forecasts |
| Date: | 2025–05–27 |
| URL: | https://d.repec.org/n?u=RePEc:fip:l00001:100021 |