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on Risk Management |
By: | \c{C}a\u{g}{\i}n Ararat; Zachary Feinstein |
Abstract: | Systemic risk measures aggregate the risks from multiple financial institutions to find system-wide capital requirements. Though much attention has been given to assessing the level of systemic risk, less has been given to allocating that risk to the constituent institutions. Within this work, we propose a Nash allocation rule that is inspired by game theory. Intuitively, to construct these capital allocations, the banks compete in a game to reduce their own capital requirements while, simultaneously, maintaining system-level acceptability. We provide sufficient conditions for the existence and uniqueness of Nash allocation rules, and apply our results to the prominent structures used for systemic risk measures in the literature. We demonstrate the efficacy of Nash allocations with numerical case studies using the Eisenberg-Noe aggregation mechanism. |
Date: | 2025–04 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.20413 |
By: | Jinghui Chen; Edward Furman; X. Sheldon Lin |
Abstract: | Measuring the contribution of a bank or an insurance company to the overall systemic risk of the market is an important issue, especially in the aftermath of the 2007-2009 financial crisis and the financial downturn of 2020. In this paper, we derive the worst-case and best-case bounds for marginal expected shortfall (MES) -- a key measure of systemic risk contribution -- under the assumption of known marginal distributions for individual companies' risks but an unknown dependence structure. We further derive improved bounds for the MES risk measure when partial information on companies' risk exposures -- and hence their dependence -- is available. To capture this partial information, we utilize three commonly used background risk models: the additive, minimum-based, and multiplicative factor models. Finally, we present an alternative set of improved MES bounds based on a linear regression relationship between individual companies' risks and overall market risk, consistent with the assumptions of the Capital Asset Pricing Model in finance and the Weighted Insurance Pricing Model in insurance. |
Date: | 2025–04 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.19953 |
By: | Robert Millar; Jinglai Li |
Abstract: | Optimal portfolio allocation is often formulated as a constrained risk problem, where one aims to minimize a risk measure subject to some performance constraints. This paper presents new Bayesian Optimization algorithms for such constrained minimization problems, seeking to minimize the conditional value-at-risk (a computationally intensive risk measure) under a minimum expected return constraint. The proposed algorithms utilize a new acquisition function, which drives sampling towards the optimal region. Additionally, a new two-stage procedure is developed, which significantly reduces the number of evaluations of the expensive-to-evaluate objective function. The proposed algorithm's competitive performance is demonstrated through practical examples. |
Date: | 2025–03 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2503.17737 |
By: | Masoud Ataei |
Abstract: | This paper investigates the structural dynamics of stock market volatility through the Financial Chaos Index, a tensor- and eigenvalue-based measure designed to capture realized volatility via mutual fluctuations among asset prices. Motivated by empirical evidence of regime-dependent volatility behavior and perceptual time dilation during financial crises, we develop a regime-switching framework based on the Modified Lognormal Power-Law distribution. Analysis of the FCIX from January 1990 to December 2023 identifies three distinct market regimes, low-chaos, intermediate-chaos, and high-chaos, each characterized by differing levels of systemic stress, statistical dispersion and persistence characteristics. Building upon the segmented regime structure, we further examine the informational forces that shape forward-looking market expectations. Using sentiment-based predictors derived from the Equity Market Volatility tracker, we employ an elastic net regression model to forecast implied volatility, as proxied by the VIX index. Our findings indicate that shifts in macroeconomic, financial, policy, and geopolitical uncertainty exhibit strong predictive power for volatility dynamics across regimes. Together, these results offer a unified empirical perspective on how systemic uncertainty governs both the realized evolution of financial markets and the anticipatory behavior embedded in implied volatility measures. |
Date: | 2025–04 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.18958 |
By: | Manuel Menkhoff |
Abstract: | This paper examines novel survey evidence on firms’ beliefs about macroeconomic tail risk and their role in investment decisions. In a large survey of German firms, I elicit (i) the subjective probability of a severe macroeconomic downturn and (ii) firms’ exposure to such an event. I consistently find across different empirical approaches that a higher probability of a severe macroeconomic downturn substantially lowers investment, particularly for firms that report higher exposure to the event. I attribute less than half of the investment response to changes in firms' subjective first and second moments. In a quantitative heterogeneous firm model calibrated to match the survey evidence, firms' concern with tail risk makes fiscal policy particularly effective for stabilizing investment. |
Keywords: | macroeconomic tail risk, rare events, firm expectations, investment. |
JEL: | D84 E22 E32 G30 |
Date: | 2025 |
URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11848 |
By: | Claire Mouminoux; Fanny Claise; Marielle Brunette |
Abstract: | This article examines insurance choices, observed through a laboratory experiment. We find that proposing a single insurance policy for multiple risks, known as bundled insurance, reduces the demand for coverage while mitigating adverse selection effects and enhancing insurers’ ability to manage losses. In contrast, offering a separate contract for each risk increases coverage for insured individuals but exposes insurers to greater adverse selection. Finally, we test a new type of insurance called semi-bundled insurance, which lies between separate and bundled insurance, conditioning the insured to choose a minimum number of risks to cover. Although we do not observe a significant difference in insurance coverage compared to separate insurance, we note an improvement in managing adverse selection relative to separate policies. These findings provide promising perspectives for addressing the issue of underinsurance while maintaining a minimum diversification of risk, which is essential for the sustainability of insurers. |
Keywords: | Insurance, Bundled, Decision, Microeconomics, Experiment. |
JEL: | C91 D81 G22 |
Date: | 2024 |
URL: | https://d.repec.org/n?u=RePEc:ulp:sbbeta:2024-53 |
By: | Hern\'an Larralde; Roberto Mota Navarro |
Abstract: | We show that assuming that the returns are independent when conditioned on the value of their variance (volatility), which itself varies in time randomly, then the distribution of returns is well described by the statistics of the sum of conditionally independent random variables. In particular, we show that the distribution of returns can be cast in a simple scaling form, and that its functional form is directly related to the distribution of the volatilities. This approach explains the presence of power-law tails in the returns as a direct consequence of the presence of a power law tail in the distribution of volatilities. It also provides the form of the distribution of Bitcoin returns, which behaves as a stretched exponential, as a consequence of the fact that the Bitcoin volatilities distribution is also closely described by a stretched exponential. We test our predictions with data from the S\&P 500 index, Apple and Paramount stocks; and Bitcoin. |
Date: | 2025–04 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.20488 |
By: | Aase, Knut K. (Dept. of Business and Management Science, Norwegian School of Economics) |
Abstract: | We consider optimal risk sharing in a dynamic setting, where agents have preferences represented by translation invariant recursive utility. This model has some appealing features, both compared to the scale invariant one and to the standard model with expected utility. First, the model allows for a treatment of heterogeneous preferences. This leads to extensions in more realistic directions of the standard, one-period risk sharing model. Second, the new endogenous variable entering the state price deflator is a traded security, an annuity, while in the scale invariant model the corresponding variable is the agent’s wealth. The model invites for a closer look at the mutuality principle in syndicates and optimal risk sharing in society. We also embed a stock market in our setting and derive a consumption based capital asset pricing model. |
Keywords: | Recursive utility; translation invariant model; utility gradients; optimal risk sharing; CCAPM; optimal risk sharing; the mutuality principle |
JEL: | D51 D53 D90 E21 G10 G12 |
Date: | 2025–05–09 |
URL: | https://d.repec.org/n?u=RePEc:hhs:nhhfms:2025_015 |
By: | Castro-Iragorri, Carlos (Universidad del Rosario); Parra-Diaz, Manuel (Universidad del Rosario) |
Abstract: | Recent advances in deep learning have spurred the development of end-to-end frameworks for portfolio optimization that utilize implicit layers. However, many such implementations are highly sensitive to neural network initialization, undermining performance consistency. This research introduces a robust end-to-end framework tailored for risk budgeting portfolios that effectively reduces sensitivity to initialization. Importantly, this enhanced stability does not compromise portfolio performance, as our framework consistently outperforms the risk parity benchmark. |
Keywords: | end-to-end framework; neural networks; risk budgeting; stability |
JEL: | C13 C45 G11 |
Date: | 2025–03–05 |
URL: | https://d.repec.org/n?u=RePEc:col:000092:021367 |
By: | Nicole B\"auerle; Tamara G\"oll |
Abstract: | In this paper, we consider $n$ agents who invest in a general financial market that is free of arbitrage and complete. The aim of each investor is to maximize her expected utility while ensuring, with a specified probability, that her terminal wealth exceeds a benchmark defined by her competitors' performance. This setup introduces an interdependence between agents, leading to a search for Nash equilibria. In the case of two agents and CRRA utility, we are able to derive all Nash equilibria in terms of terminal wealth. For $n>2$ agents and logarithmic utility we distinguish two cases. In the first case, the probabilities in the constraint are small and we can characterize all Nash equilibria. In the second case, the probabilities are larger and we look for Nash equilibria in a certain set. We also discuss the impact of the competition using some numerical examples. As a by-product, we solve some portfolio optimization problems with probability constraints. |
Date: | 2025–03 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2503.20340 |
By: | Levon Hakobyan; Sergey Lototsky |
Abstract: | While the Kelly portfolio has many desirable properties, including optimal long-term growth rate, the resulting investment strategy is rather aggressive. In this paper, we suggest a unified approach to the risk assessment of the Kelly criterion in both discrete and continuous time by introducing and analyzing the asymptotic variance that describes fluctuations of the portfolio growth, and use the results to propose two new measures for quantifying risk. |
Date: | 2025–03 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2503.17927 |
By: | Lars Hornuf; David J. Streich; Niklas Töllich |
Abstract: | Retrieval-augmented generation (RAG) has emerged as a promising way to improve task-specific performance in generative artificial intelligence (GenAI) applications such as large language models (LLMs). In this study, we evaluate the performance implications of providing various types of domain-specific information to LLMs in a simple portfolio allocation task. We compare the recommendations of seven state-of-the-art LLMs in various experimental conditions against a benchmark of professional financial advisors. Our main result is that the provision of domain-specific information does not unambiguously improve the quality of recommendations. In particular, we find that LLM recommendations underperform recommendations by human financial advisors in the baseline condition. However, providing firm-specific information improves historical performance in LLM portfolios and closes the gap with human advisors. Performance improvements are achieved through higher exposure to market risk and not through an increase in mean-variance efficiency within the risky portfolio share. Notably, portfolio risk increases primarily for risk-averse investors. We also document that quantitative firm-specific information affects recommendations more than qualitative firm-specific information, and that equipping models with generic finance theory does not affect recommendations. |
Keywords: | generative artificial intelligence, large language models, domain-specific information, retrieval-augmented generation, portfolio management, portfolio allocation. |
JEL: | G00 G11 G40 |
Date: | 2025 |
URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_11862 |
By: | Aase, Knut K. (Dept. of Business and Management Science, Norwegian School of Economics) |
Abstract: | We consider optimal risk sharing where agents have preferences represented by translation invariant recursive utility. The dynamics in continuous time is driven by diffusion processes. The model has some appealing features compared to the scale invariant version. First, the model allows for heterogenous agents, where optimal risk sharing can be addressed. Second, a new endogenous variable allows for a variety of results, not possible in the standard model. The model allows for a new look at the mutuality principle. We also endow the model with a stock market and derive a consumption based capital asset pricing model. |
Keywords: | Optimal risk sharing; the mutuality principle; recursive utility; CCAPM; the stochastic maximum principle |
JEL: | D51 D53 D90 E21 G10 G12 |
Date: | 2025–05–12 |
URL: | https://d.repec.org/n?u=RePEc:hhs:nhhfms:2025_016 |
By: | Baishuai Zuo; Chuancun Yin |
Abstract: | In this paper, we develop the lower and upper bounds of worst-case distortion riskmetrics and weighted entropy for unimodal, and symmetric unimodal distributions when mean and variance information are available. We also consider the sharp upper bounds of distortion riskmetrics and weighted entropy for symmetric distribution under known mean and variance. These results are applied to (weighted) entropies, shortfalls and other risk measures. Specifically, entropies include cumulative Tsallis past entropy, cumulative residual Tsallis entropy of order {\alpha}, extended Gini coefficient, fractional generalized cumulative residual entropy, and fractional generalized cumulative entropy. Shortfalls include extended Gini shortfall, Gini shortfall, shortfall of cumulative residual entropy, and shortfall of cumulative residual Tsallis entropy. Other risk measures include nth-order expected shortfall, dual power principle and proportional hazard principle. |
Date: | 2025–04 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.19725 |
By: | Eduardo Abi Jaber; Paul Gassiat; Dimitri Sotnikov |
Abstract: | We study the martingale property and moment explosions of a signature volatility model, where the volatility process of the log-price is given by a linear form of the signature of a time-extended Brownian motion. Excluding trivial cases, we demonstrate that the price process is a true martingale if and only if the order of the linear form is odd and a correlation parameter is negative. The proof involves a fine analysis of the explosion time of a signature stochastic differential equation. This result is of key practical relevance, as it highlights that, when used for approximation purposes, the linear combination of signature elements must be taken of odd order to preserve the martingale property. Once martingality is established, we also characterize the existence of higher moments of the price process in terms of a condition on a correlation parameter. |
Date: | 2025–03 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2503.17103 |
By: | Ajovalasit, Samantha; Consiglio, Andrea; Pagliardi, Giovanni; Zenios, Stauros Andrea |
Abstract: | Political risk is a significant determinant of sovereign debt dynamics. We estimate the sensitivity of bond yields and economic growth to a country-level broad proxy of political risk and develop a stochastic debt sustainability analysis optimization model with both yields and growth channels to show that political risk can render debt unsustainable, triggered by changes in the political rating level, volatility, or both. In contrast, existing models that neglect political risk would incorrectly predict sustainability. Importantly, we uncover political risk effects in developed countries, going beyond the emerging markets of earlier literature. We establish a positive predictive relation of structural reforms to political ratings, and benchmark reforms against a large-scale quantitative easing program and find them comparably effective, highlighting their significance in restoring debt sustainability. We also establish the effect of political risk on the optimal choice of debt financing maturities. We validate the model out-of-sample on the Italian 2014-2019 reforms, showing that it would have predicted the country's debt more accurately than existing models. Likewise, a simulation of the French 2024 snap elections finds a much higher risk of debt unsustainability than that estimated if the political shock is omitted. |
Keywords: | Debt management, debt sustainability, political risk, structural reforms |
JEL: | E52 E62 F30 F34 G15 G18 H62 H63 H68 |
Date: | 2025 |
URL: | https://d.repec.org/n?u=RePEc:zbw:eabhps:317786 |
By: | Lorenzo Bastianello (Universite Paris 2 Pantheon-Assas, LEMMA, Paris, France); Alain Chateauneuf (IPAG Business School, Paris, France and Paris School of Economics and Universite Paris 1, Paris, France); Bernard Cornet (Department of Economics, University of Kansas, Lawrence, KS 66045, USA) |
Abstract: | Two acts are comonotonic if they co-vary in the same direction. The main purpose of this paper is to derive a new characterization of Cumulative Prospect Theory (CPT) through simple properties involving comonotonicity. The main novelty is a concept dubbed gain-loss hedging: mixing positive and negative acts creates hedging possibilities even when acts are comonotonic. This allows us to clarify in which sense CPT differs from Choquet expected utility. Our analysis is performed under the assumption that acts are real-valued functions. This entails a simple (piece-wise) constant marginal utility representation of CPT, which allows us to clearly separate the perception of uncertainty from the evaluation of outcomes. |
Keywords: | Cumulative Prospect Theory, Comonotonicity, Gain-loss hedging, Sipos integral, Choquet integral. |
JEL: | D81 |
Date: | 2025–04 |
URL: | https://d.repec.org/n?u=RePEc:kan:wpaper:202511 |
By: | Iman Khajepour; Geoffrey Pritchard; Danny Ralph; Golbon Zakeri |
Abstract: | We consider a competitive market with risk-averse participants. We assume that agents' risks are measured by coherent risk measures introduced by Artzner et al. (1999). Fundamental theorems of welfare economics have long established the equivalence of competitive equilibria and system welfare optimization (see, e.g., Samuelson (1947)). These have been extended to the case of risk-averse agents with complete risk markets in Ralph and Smeers (2015). In this paper, we consider risk trading in incomplete markets and introduce a mechanism to complete the market iteratively while monotonically enhancing welfare. |
Date: | 2025–04 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.18436 |
By: | Ho Ka Chan; Taro Toyoizumi |
Abstract: | People often deviate from expected utility theory when making risky and intertemporal choices. While the effects of probabilistic risk and time delay have been extensively studied in isolation, their interplay and underlying theoretical basis are still under debate. In this work, we applied our previously proposed anticipated surprise framework to intertemporal choices with and without explicit probabilistic risk, assuming that delayed reward may fail to materialize at a fixed hazard rate. The model prediction is consistent with key empirical findings: time inconsistency and aversion to timing risk stem from the avoidance of large negative surprises, while differences in mental representations of outcome resolution explain the conflicting effects of probabilistic risk on temporal discounting. This framework is applicable to a broad range of decision-making problems and offers a new perspective over how various types of risk may interact. |
Date: | 2025–03 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2503.19514 |
By: | Huixin Bi; Andrew Foerster; Nora Traum |
Abstract: | Using a two-country monetary union framework with financial frictions, we quantify the efficacy of targeted asset purchases, as well as expectations of such programs, in the presence of sovereign default and financial liquidity risks. The risk of default increases with the level of government debt and shifts in investors’ perception of fiscal solvency. Liquidity risks increase when the probability of default affects the tightness of credit markets. We calibrate the model to Italy during the 2012 European debt crisis and compare it to key features of the data. We find that changes in investors’ perception played a more significant role than increases in government debt in affecting the macroeconomy. When a debt crisis occurs, asset purchases help stabilize both financial markets and the economy. This stabilization effect can occur even if asset purchases are expected but never implemented. Moreover, expectations of potential asset purchases during a crisis alter the level of economic activity in periods when there are no crises. |
Keywords: | fiscal policy; monetary policy; unconventional monetary policy; Monetary Union; financial frictions; Regime-Switching Models |
JEL: | E58 E63 F45 |
Date: | 2025–05–07 |
URL: | https://d.repec.org/n?u=RePEc:fip:fedfwp:99977 |
By: | Boyang Mu (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - GENES - Groupe des Écoles Nationales d'Économie et Statistique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - GENES - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique, IP Paris - Institut Polytechnique de Paris); Natkamon Tovanich (CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - GENES - Groupe des Écoles Nationales d'Économie et Statistique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - GENES - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique, X - École polytechnique - IP Paris - Institut Polytechnique de Paris); Julien Prat (CNRS - Centre National de la Recherche Scientifique, CREST - Centre de Recherche en Économie et Statistique - ENSAI - Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] - GENES - Groupe des Écoles Nationales d'Économie et Statistique - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - ENSAE Paris - École Nationale de la Statistique et de l'Administration Économique - GENES - Groupe des Écoles Nationales d'Économie et Statistique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique, X - École polytechnique - IP Paris - Institut Polytechnique de Paris) |
Abstract: | Lending protocols have transformed the Decentralized Finance (DeFi) ecosystem, driving innovation while also introducing new risks. This study develops a machine learning framework to predict user behavior and assess factors influencing changes in health ratios within the Compound V2 protocol. By analyzing user historical data, position metrics, and market conditions, we propose machine learning-based models to predict whether users will adjust their positions or face liquidation. We find that Random Forest and XGBoost models excel in predicting these outcomes, with features like collateral values, historical risk exposure, and asset composition playing significant roles. Additionally, panel regression models reveal insights into health ratio dynamics over time and across asset types, as well as user sophistication. These findings offer a better understanding of user behavior, highlighting opportunities for improved risk modeling and adaptive strategies in DeFi lending. |
Keywords: | user modeling, decision-making, liquidation, financial risks, decentralized finance, lending protocols |
Date: | 2025–06–02 |
URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05041569 |
By: | Adam Epp; Jeffrey Gao |
Abstract: | This paper studies the rapid increase since 2019 of Government of Canada (GoC) debt issuance alongside greater hedge fund participation at GoC bond auctions. We find a systematic relationship between GoC debt stock and hedge fund bidding shares at auction. We attribute this to hedge funds’ business models, which are based on volume and leverage. We also use bid-level auction data and find that hedge funds are more willing than other investor types to buy bonds at lower auction yields (higher auction prices). These two results i) help explain why GoC auction performance has remained steady despite greater issuance and ii) affirm the importance of hedge funds in supporting Canada’s cost-effective debt distribution in recent years. In addition, we conduct a counterfactual analysis of the exit of hedge funds from auction, which further affirms the importance of hedge funds to GoC auction performance. However, the concentration of hedge funds represents a potential vulnerability because hedge funds have a greater flight risk relative to domestic real money investors and thus contribute to a potentially less stable investor base. |
Keywords: | Debt management; Financial markets; Financial institutions; Financial stability |
JEL: | D44 G12 G2 G23 H63 |
Date: | 2025–05 |
URL: | https://d.repec.org/n?u=RePEc:bca:bocadp:25-07 |
By: | Patrick Ling |
Abstract: | Although the valuation of life contingent assets has been thoroughly investigated under the framework of mathematical statistics, little financial economics research pays attention to the pricing of these assets in a non-arbitrage, complete market. In this paper, we first revisit the Fundamental Theorem of Asset Pricing (FTAP) and the short proof of it. Then we point out that discounted asset price is a martingale only when dividends are zero under all random states of the world, using a simple proof based on pricing kernel. Next, we apply Fundamental Theorem of Asset Pricing (FTAP) to find valuation formula for life contingent assets including life insurance policies and life contingent annuities. Last but not least, we state the assumption of static portfolio in a dynamic economy, and clarify the FTAP that accommodates the valuation of a portfolio of life contingent policies. |
Date: | 2025–03 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2503.21256 |
By: | Lawrence, Alice |
Abstract: | In today’s volatile global economy, over-reliance on single-source suppliers or geographically concentrated supply chains exposes businesses to significant risks ranging from geopolitical disruptions and natural disasters to trade restrictions and pandemics. This paper explores diversification as a strategic approach to mitigating these supply chain dependency risks. Through an analysis of real-world case studies and recent academic research, we examine how firms in sectors such as automotive, pharmaceuticals, and electronics have implemented multi-sourcing, regionalization, vertical integration, and strategic inventory management to build more resilient supply chains. The findings suggest that while diversification involves added costs and complexity, it ultimately enhances operational agility and long-term stability. Moreover, we discuss the role of digital tools, such as supply chain mapping and AI-driven risk assessment, in supporting informed diversification decisions. By balancing cost efficiency with resilience, companies can better withstand unforeseen disruptions and maintain a competitive advantage in an increasingly uncertain environment. Keywords: supply chain risk, diversification strategy, multi-sourcing, resilience, supply chain management, dependency risk, global trade disruptions, supply chain resilience, procurement strategy, operational agility |
Date: | 2024–07–14 |
URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:u2wej_v1 |
By: | Appelbaum, Elie; Leshno, Moshe; Prisman, Eitan; Prisman, Eliezer, Z. |
Abstract: | The problem of crossing Kaplan-Meier curves has not been solved in the medical research literature to date. This paper integrates survival curve comparisons into decision theory, providing a theoretical framework and a solution to the problem of crossing Kaplan-Meier curves. The application of decision theory allows us to apply stochastic dominance concepts and risk preference attributes to compare treatments even when standard Kaplan-Meier curves cross. The paper shows that as additional risk preference attributes are adopted, Kaplan-Meier curves can be ranked under weaker restrictions, namely with higher orders of stochastic dominance. Consequently, even Kaplan-Meier curves that cross may be ranked. The method we present allows us to extract all possible information from survival functions; hence, superior treatments that cannot be identified using standard Kaplan-Meier curves may become identifiable. Our methodology is applied to two examples of published empirical medical studies. We show that treatments deemed non-comparable because their Kaplan-Meier curves intersect can be compared using our method. |
Keywords: | Survival Curve Analysis; Decision Theory; Risk Preference Modelling; Stochastic Dominance; Medical Treatment Comparison; Healthcare Data Interpretation |
JEL: | C18 C65 D81 I10 I12 I19 |
Date: | 2025–03–20 |
URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:124419 |
By: | Bruno Giorgio |
Abstract: | This dissertation investigates the ability of the Ising model to replicate statistical characteristics, or stylized facts, commonly observed in financial assets. The study specifically examines in the S&P500 index the following features: volatility clustering, negative skewness, heavy tails, the absence of autocorrelation in returns, and the presence of autocorrelation in absolute returns. A significant portion of the dissertation is dedicated to Ising model-based simulations. Due to the lack of an analytical or deterministic solution, the Monte Carlo method was employed to explore the model's statistical properties. The results demonstrate that the Ising model is capable of replicating the majority of the statistical features analyzed. |
Date: | 2025–04 |
URL: | https://d.repec.org/n?u=RePEc:arx:papers:2504.19050 |
By: | Alain Chateauneuf (IPAG Business School, Paris, France and Paris School of Economics and Universite Paris 1, Paris, France); Bernard Cornet (Department of Economics, University of Kansas, Lawrence, KS 66045, USA and and Paris School of Economics, Paris, France) |
Abstract: | This paper considers financial markets with bid-ask spreads and studies the class of markets with hedging complements, a property formalized by the complementarity of its hedging price, in the same way as strategic complements is defined on agents' payoff functions in game theory. The class of markets with hedging complements contains both markets with frictionless securities and the larger class markets with independent marketed securities together with the frictionless bond, assuming both to be arbitrage-free. Moreover, the hedging prices of the latter markets are proved to satisfy a tractable explicit formula, as the sum of a "generalized" convex Choquet integral and of a modular term. Finally this class of markets also satisfy the put-call parity of Cerreia-Vioglio, Maccheroni, Marinacci, and Montrucchio (2015). |
Keywords: | Financial markets, bid-ask spread, hedging complements, generalized Choquet integral, submodularity, decreasing difference property, put-call parity |
Date: | 2025–04 |
URL: | https://d.repec.org/n?u=RePEc:kan:wpaper:202510 |
By: | Andrian, Leandro Gaston; Leon-Diaz, John; Rojas, Eugenio |
Abstract: | We examine hedging as a macroprudential tool in a Sudden Stops model of an economy exposed to commodity price fluctuations. We find that hedging commodity revenues yields significant welfare gains by stabilizing public expenditure, which heavily depends on these revenues. However, this added stability weakens precautionary motives and exacerbates the pecuniary externality that drives overborrowing in such models. As a result, hedging and traditional macroprudential policy act as complements rather than substitutes, with more ag- gressive hedging inducing a stronger macroprudential response. Our findings suggest that while hedging enhances stability and improves welfare, it does not eliminate the need for macroprudential regulation. |
Keywords: | Hedging;Sudden stops;Financial Crises;Macroprudential policy |
JEL: | F32 F41 G13 |
Date: | 2025–04 |
URL: | https://d.repec.org/n?u=RePEc:idb:brikps:14083 |