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on Risk Management |
| By: | Michele Bonollo; Martino Grasselli; Gianmarco Mori; Havva Nilsu Oz |
| Abstract: | Despite decades of research in risk management, most of the literature has focused on scalar risk measures (like e.g. Value-at-Risk and Expected Shortfall). While such scalar measures provide compact and tractable summaries, they provide a poor informative value as they miss the intrinsic multivariate nature of risk.To contribute to a paradigmatic enhancement, and building on recent theoretical work by Faugeras and Pag\'es (2024), we propose a novel multivariate representation of risk that better reflects the structure of potential portfolio losses, while maintaining desirable properties of interpretability and analytical coherence. The proposed framework extends the classical frequency-severity approach and provides a more comprehensive characterization of extreme events. Several empirical applications based on real-world data demonstrate the feasibility, robustness and practical relevance of the methodology, suggesting its potential for both regulatory and managerial applications. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.21556 |
| By: | Franco Da Silveira, Rodrigo Lanna; Davoli Alvarenga, Mayara; Luna, Ivette; Coltri, Priscila Pereira; Gonçalves, Renata Ribeiro Do Valle; Torres, Guilherme Almussa Leite |
| Keywords: | Agricultural Finance, Farm Management, Financial Economics |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ags:aaea24:343570 |
| By: | Jin Man Lee; James Shilling; Janet Ge |
| Abstract: | The paper examines the vulnerability of US households today (2020-2022) to the risk of rent increases compared to previous years, particularly 2007-2015. To measure vulnerability requires a normative framework. We follow the approach developed by Sinai and Souleles (2005). We find that households are more vulnerable to rent increases now than they were at the start of our sample period. Traditionally, owning a property has been the primary means of hedging against rising rent risk. However, not all households can afford this option. We propose that insurance contracts could provide an alternative solution for households to hedge against the risk of rising rents. Similar to renters insurance, which protects personal belongings, these contracts could offer protection against rent hikes. |
| Keywords: | housing; Investment Decision; Rents; Risk and Uncertainty |
| JEL: | R3 |
| Date: | 2025–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:arz:wpaper:eres2025_33 |
| By: | Perez, Pedro Gurrola; Murphy, David |
| Abstract: | In recent years, many derivatives market participants received large margin calls in episodes of elevated market volatility such as the onset of the Covid-19 global pandemic and the illegal Russian invasion of Ukraine. The lack of some market participants’ preparedness to meet these calls resulted in liquidity stress and reinvigorated the policy debate about how reactive margin should be to changes in market conditions. This debate has been hampered by the lack of a generally accepted way of measuring the reactiveness of the models used to calculate initial margin. The first contribution of this paper is to provide such a measure. We consider a step function in volatility, and examine the responses of various initial margin models to paths of risk factor returns consistent with this impulse, introducing the impulse response function as a convenient means of presenting this reaction. The results presented demonstrate that a model's impulse response is a robust and useful measure of its reactiveness. This approach could be used both to measure initial margin model reactiveness, or procyclicality as it is often termed, and to capture the uncertainty in this measurement. It also provides significant, novel insights into the behaviour of some economically important margin models. In particular, the tendency of some filtered historical simulation value at risk models to over-react to sharp stepwise increases in volatility is demonstrated and the reasons for it are explored. The behaviour of two widely-used anti-procyclicality tools, the buffer and the use of a stressed period, are also analysed: the latter is found to be more successful at mitigating procyclicality than the former. The paper concludes with a discussion of the policy implications of the results presented. |
| Keywords: | anti-procyclicality; impulse response function; initial margin model; margin model response; procyclicality; volatility estimation |
| JEL: | G13 C52 C12 |
| Date: | 2025–11–30 |
| URL: | https://d.repec.org/n?u=RePEc:ehl:lserod:128641 |
| By: | Nicolas Baradel |
| Abstract: | In incomplete financial markets, pricing and hedging European options lack a unique no-arbitrage solution due to unhedgeable risks. This paper introduces a constrained deep learning approach to determine option prices and hedging strategies that minimize the Profit and Loss (P&L) distribution around zero. We employ a single neural network to represent the option price function, with its gradient serving as the hedging strategy, optimized via a loss function enforcing the self-financing portfolio condition. A key challenge arises from the non-smooth nature of option payoffs (e.g., vanilla calls are non-differentiable at-the-money, while digital options are discontinuous), which conflicts with the inherent smoothness of standard neural networks. To address this, we compare unconstrained networks against constrained architectures that explicitly embed the terminal payoff condition, drawing inspiration from PDE-solving techniques. Our framework assumes two tradable assets: the underlying and a liquid call option capturing volatility dynamics. Numerical experiments evaluate the method on simple options with varying non-smoothness, the exotic Equinox option, and scenarios with market jumps for robustness. Results demonstrate superior P&L distributions, highlighting the efficacy of constrained networks in handling realistic payoffs. This work advances machine learning applications in quantitative finance by integrating boundary constraints, offering a practical tool for pricing and hedging in incomplete markets. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.20837 |
| By: | Jan Maelger |
| Abstract: | We develop a formalism for insurance profit optimisation for the in-force business constraint by regulatory and risk policy related requirements. This approach is applicable to Life, P&C and Reinsurance businesses and applies in all regulatory frameworks with a solvency requirement defined in the form of a solvency ratio, notably Solvency II and the Swiss Solvency Test. We identify the optimal asset allocation for profit maximisation within a pre-defined risk appetite and deduce the annual opportunity cost faced by the insurance company. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.13959 |
| By: | Cecchetti, Stephen G.; Lumsdaine, Robin L.; Peltonen, Tuomas; Sánchez Serrano, Antonio |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:srk:srkasc:202516 |
| By: | Gerrit Meyerheim (University of Munich) |
| Abstract: | This paper integrates tail aversion, implemented via a one-period entropic tilt, with rare disasters in a consumption-based asset pricing model with CRRA utility to jointly address the equity premium and risk-free rate puzzles. The model delivers closed-form expressions for the risk-free rate and asset moments, pushes out the Hansen-Jagannathan bound, implies a low risk-free rate via diffusion and disaster channels, and delivers natural upper and lower bounds of risk aversion. Calibrated to long-run return data and disciplined by disaster evidence, the model matches average returns, volatility, and a low real risk-free rate with very modest risk aversion. |
| Keywords: | equity premium puzzle; risk-free rate puzzle; rare disasters; entropic tilt; multiplier (kl) preferences; robust control; consumption-based asset pricing; |
| JEL: | G12 E44 E43 E21 D81 |
| Date: | 2025–10–30 |
| URL: | https://d.repec.org/n?u=RePEc:rco:dpaper:549 |
| By: | Bertolozzi-Caredio, Daniele; Soriano, Barbara; Urquhart, Julie; Vigani, Mauro |
| Abstract: | Understanding how farmers learn and how this influences their decisions is still a key question in research, especially in the context of increasing challenges and uncertainties. We explore whether and how different learning preferences, notably learning by doing, from other farmers and through social media, influence farmers’ risk management (RM) choices. Based on a survey of farmers in Spain and the UK, we employed multivariate probit regressions and Poisson models with instrument variables. We found that all learning preferences are significantly correlated to RM choice, with learning through social media and from peers leading to more strategies adopted by the farmer, and learning by doing leading to fewer strategies. The results, however, show that each learning preference affects different specific RM strategies. Our findings suggest that policymakers should consider leveraging informal learning networks to improve farmers’ RM, whereas policy incentives might be designed to formalize and promote social media use (also by existing extension services) to boost the adoption of RM strategies. |
| Keywords: | Farm Management, Risk and Uncertainty |
| Date: | 2024–07–26 |
| URL: | https://d.repec.org/n?u=RePEc:ags:iaae24:344372 |
| By: | Pin-Te Lin; Yu-Lieh Huang |
| Abstract: | This study examines the inflation-hedging benefits across various asset classes—stocks, housing, bonds, and bills—over the long term, from 1870 to 2020, in the US markets. Specifically, it compares and contrasts the hedging benefits of each asset class against both expected and unexpected inflation. Historical explorations of the inflation-hedging properties across asset classes can have implications for portfolio management. |
| Keywords: | Expected inflation; Inflation Hedging; Unexpected inflation |
| JEL: | R3 |
| Date: | 2025–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:arz:wpaper:eres2025_235 |
| By: | Ismail Benslimane (USMBA - Université Sidi Mohamed Ben Abdellah [Fès]); Nabil Sifouh (Université Mohammed Premier [Oujda] = Université Mohammed Ier = University of Mohammed First); Sanae Benjelloun (USMBA - Université Sidi Mohamed Ben Abdellah [Fès]); Karim Ameziane (UCD - Université Chouaib Doukkali); Yassire Elotmani (UM5 - Université Mohammed V de Rabat [Agdal]) |
| Abstract: | The objective of this article is to highlight three key concepts in the field of innovation: risk, ambiguity, and uncertainty. To this end, we reviewed the literature to identify the (probability/outcome) pair that helps distinguish these three notions and prevent any confusion. Particular attention is given to the eight types of uncertainty related to innovation, as well as to the various mechanisms available to reduce them. This research also aims to identify the primary source of ambiguity in innovative industries – namely, complexity – while addressing the risks inherent in technological innovation, whether internal or external. Finally, the article proposes an 'uncertainty tree' that synthesizes these various dimensions and situates the three aspects of uncertainty within a process-oriented framework, in order to determine the respective phases in which they emerge. |
| Keywords: | unforeseen uncertainty, radical uncertainty, uncertainty tree, ambiguity, risk |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05312346 |
| By: | Moritz Loewenfeld (Universität Wien = University of Vienna); Jiakun Zheng (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | Allowing risk preferences to depend on the correlation between lottery outcomes can explain behavioral anomalies, while empirical evidence is limited and mixed. Using the framework of correlation sensitivity, we classify preferences into three types and adapt a choice task to categorize subjects. Experiments show that aggregate choices exhibit correlation sensitivity opposite to regret and salience theory predictions. Clustering analysis reveals that a correlation-sensitive minority drives these patterns, while most subjects display no sensitivity. We further disentangle deliberate within-state comparisons from incidental payoff comparisons, finding that both contribute to correlation sensitivity, with deliberate comparisons exerting slightly stronger effects. |
| Keywords: | regret theory, salience theory, experiment, correlation effects, choice under risk |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05346525 |
| By: | Eduardo M. Azevedo; Florian Scheuer; Kent Smetters; Min Yang |
| Abstract: | Recent proposals to tax unrealized capital gains or wealth have sparked a debate about their impact on entrepreneurship. We show that accrual-based taxation creates two opposing effects: successful founders face greater dilution from advance tax payments, whereas unsuccessful founders receive tax credits that effectively provide insurance. Using comprehensive new data on U.S. venture capital deals, we find that founder returns remain extremely skewed, with 84% receiving zero exit value while the top 2% capture 80% of total value. Moving from current realization-based to accrual-based taxation would reduce founder ownership at exit by 25% on average but would also increase the fraction receiving positive payoffs from 16% to 47% when tax credits are refunded. Embedding these distributions in a dynamic career choice model, we find that founders with no or moderate risk aversion prefer the current realization-based tax system, while more risk-averse founders prefer accrual-based taxation. We estimate that a 2% annual wealth tax has a similar impact on dilution as taxing unrealized capital gains but produces no risk-sharing benefits due to the absence of tax credits in case of down rounds. |
| JEL: | D86 H2 H3 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34512 |
| By: | Georges Dionne (HEC Montreal, Canada Research Chair in Risk Management); Denise Desjardins (HEC Montreal, Canada Research Chair in Risk Management) |
| Abstract: | We study the effect of inflation on P&C insurers with individual data. We use observed and forecasted measures of inflation. We compute forecasted rates of inflation from the Bayesian Vector Autoregression (BVAR) model under two different assumptions, the Gaussian distribution and the Student-t distribution. For the econometric estimations, we proceed with the Generalized Method of Moments (GMM). Overall, the findings indicate that insurers are responsive to forecasted inflation as well to realized inflation. Proactive strategies—particularly those based on long-term forecasts—appear to enhance profitability and stabilize operations, while short-term reactions to realized inflation are more defensive. |
| Keywords: | Inflation rate; US P&C insurance industry; forecasted inflation; observed inflation; reinsurance demand; liquidity creation; ROA; GMM estimation model; BVAR model |
| JEL: | B22 E3 E4 G20 G22 G32 G38 G52 |
| Date: | 2025–12–05 |
| URL: | https://d.repec.org/n?u=RePEc:ris:crcrmw:021827 |