nep-rmg New Economics Papers
on Risk Management
Issue of 2023‒11‒13
ten papers chosen by
Stan Miles, Thompson Rivers University

  1. Leverage Ratio, Risk-Based Capital Requirements, and Risk-taking in the UK By Mahmoud Fatouh; Simone Giansante; Steven Ongena
  2. An axiomatic theory for comonotonicity-based risk sharing By Dhaene, Jan; Robert, Christian Y.; Cheung, Ka Chun; Denuit, Michel
  3. Partial hedging in rough volatility models By Motte, Edouard; Hainaut, Donatien
  4. Risk Assessment and Statistical Significance in the Age of Foundation Models By Apoorva Nitsure; Youssef Mroueh; Mattia Rigotti; Kristjan Greenewald; Brian Belgodere; Mikhail Yurochkin; Jiri Navratil; Igor Melnyk; Jerret Ross
  5. Hybrid life insurance valuation based on a new standard deviation premium principle in a stochastic interest rate framework By Belhouari, Oussama; Deelstra, Griselda; Devolder, Pierre
  6. Applying SOBANE Strategy for Risk Management in Museums By Pop, Izabela Luiza
  7. Economic Theory as Successive Approximations of Statistical Moments By Olkhov, Victor
  8. Applying Reinforcement Learning to Option Pricing and Hedging By Zoran Stoiljkovic
  9. Sovereign portfolio composition and bank risk: the case of European banks. By Selva Bahar Baziki; María J. Nieto; Rima Turk-Ariss
  10. An In-Depth Examination of Requirements for Disclosure Risk Assessment By Ron S. Jarmin; John M. Abowd; Robert Ashmead; Ryan Cumings-Menon; Nathan Goldschlag; Michael B. Hawes; Sallie Ann Keller; Daniel Kifer; Philip Leclerc; Jerome P. Reiter; Rolando A. Rodr\'iguez; Ian Schmutte; Victoria A. Velkoff; Pavel Zhuravlev

  1. By: Mahmoud Fatouh (Bank of England and University of Essex); Simone Giansante (University of Palermo); Steven Ongena (University of Zurich; Swiss Finance Institute; KU Leuven; NTNU Business School; CEPR)
    Abstract: We assess the impact of the leverage ratio capital requirements on the risk-taking behaviour of banks both theoretically and empirically. We use a difference-in-differences (DiD) setup to compare the behaviour of UK banks subject to the leverage ratio requirements (LR banks) to otherwise similar banks (non-LR banks). Conceptually, introducing binding leverage ratio requirements into a regulatory framework with risk-based capital requirements induces banks to re-optimise, shifting from safer to riskier assets (higher asset risk). Yet, this shift would not be one-for-one due to risk weight differences, meaning the shift would be associated with a lower level of leverage (lower insolvency-risk). The interaction of these two changes determines the impact on the aggregate level of risk. Empirically, we show that LR banks did not increase asset risk, and slightly reduced leverage levels, compared to the control group after the introduction of leverage ratio in the UK. As expected, these two changes lead to a lower aggregate level of risk. Our results show that credit default swap spreads on the 5-year subordinated debt of LR banks fell relative to non-LR banks post leverage ratio introduction.
    Keywords: Capital regulation; Risk-taking; Leverage ratio; risk-based requirements
    JEL: G01 G21 G28
    Date: 2023–10
  2. By: Dhaene, Jan (KU Leuven); Robert, Christian Y. (ENSAE); Cheung, Ka Chun (The Univeristy of Hong-Kong); Denuit, Michel (Université catholique de Louvain, LIDAM/ISBA, Belgium)
    Abstract: This paper studies the quantile risk-sharing rule introduced in Denuit, Dhaene & Robert (2022). This rule is not actuarially fair, but instead satisfies another type of fairness, which is comparable with “solvency fairness” in classical centralized insurance. New properties are investigated and an axiomatic theory is developed for the quantile risk-sharing rule, which allows for a deeper understanding of its proper use. The axiomatic characterization of the quantile risk-sharing rule is based on aggregate and comonotonicity-related properties of risk-sharing rules.
    Keywords: Quantile risk-sharing rule ; conditional mean risk-sharing rule ; pooling ; comonotonicity ; P2P insurance
    Date: 2023–07–14
  3. By: Motte, Edouard (Université catholique de Louvain, LIDAM/ISBA, Belgium); Hainaut, Donatien (Université catholique de Louvain, LIDAM/ISBA, Belgium)
    Abstract: This paper studies the problem of partial hedging within the framework of rough volatility models in an incomplete market setting. We employ a stochastic control problem formulation to minimize the discrepancy between a stochastic target and the terminal value of a hedging portfolio. As rough volatility models are neither Markovian nor semi-martingale, stochastic control problems associated to rough models are quite complex to solve. Therefore, we propose a multifactor approximation of the rough volatility model and introduce the associated Markov stochastic control problem. We establish the convergence of the optimal solution for the Markov partial hedging problem to the optimal solution of the original problem as the number of factors tends to infinity. Furthermore, the optimal solution of the Markov problem can be derived solving a Hamilton-Jacobi-Bellman (HJB) equation and more precisely a nonlinear partial differential equation (PDE). Due to the inherent complexity of this nonlinear PDE, an explicit formula for the optimal solution is generally unattainable. By introducing the dual solution of the Markov problem and expressing the primal solution as a function of the dual solution, we derive approximate solutions to the Markov problem using a dual control method. This method enables for sub-optimal choices of dual control to deduce lower and upper bounds on the optimal solution as well as sub-optimal hedging ratios. In particular, explicit formulas for partial hedging strategies in rough Heston model are derived.
    Keywords: Partial hedging ; rough volatility ; rough Heston ; stochastic control ; Hamilton-Jacobi-Bellman ; Markov approximation ; dual control method
    Date: 2023–06–29
  4. By: Apoorva Nitsure; Youssef Mroueh; Mattia Rigotti; Kristjan Greenewald; Brian Belgodere; Mikhail Yurochkin; Jiri Navratil; Igor Melnyk; Jerret Ross
    Abstract: We propose a distributional framework for assessing socio-technical risks of foundation models with quantified statistical significance. Our approach hinges on a new statistical relative testing based on first and second order stochastic dominance of real random variables. We show that the second order statistics in this test are linked to mean-risk models commonly used in econometrics and mathematical finance to balance risk and utility when choosing between alternatives. Using this framework, we formally develop a risk-aware approach for foundation model selection given guardrails quantified by specified metrics. Inspired by portfolio optimization and selection theory in mathematical finance, we define a \emph{metrics portfolio} for each model as a means to aggregate a collection of metrics, and perform model selection based on the stochastic dominance of these portfolios. The statistical significance of our tests is backed theoretically by an asymptotic analysis via central limit theorems instantiated in practice via a bootstrap variance estimate. We use our framework to compare various large language models regarding risks related to drifting from instructions and outputting toxic content.
    Date: 2023–10
  5. By: Belhouari, Oussama (Université catholique de Louvain, LIDAM/ISBA, Belgium); Deelstra, Griselda (Université Libre de Bruxelles); Devolder, Pierre (Université catholique de Louvain, LIDAM/ISBA, Belgium)
    Abstract: In a complete arbitrage-free financial market, financial products are valued with the risk-neutral measure and these products are completely hedgeable. In life insurance, the approach is different as the valuation is based on an insurance premium principle which includes a safety loading. The insurer reduces the risk by pooling a vast number of independent risks. In our framework, we suggest valuations of a class of products that are dependent on both mortality and financial risk, namely hybrid life products. The main contribution of this paper is to present a generalized standard deviation premium principle in a stochastic interest rate framework, and to integrate it in different valuation operators suggested in the literature. We illustrate our methods with a classical application, namely a Pure Endowment with profit. Several numerical results are presented, and an extensive sensitivity analysis is included.
    Keywords: Financial risk ; actuarial risk ; hybrid products ; fair valuation ; risk decomposition
    Date: 2023–05–31
  6. By: Pop, Izabela Luiza
    Abstract: One of the main responsibilities of museums is to keep the cultural heritage safe, so as it can be transmitted to future generations in good conditions. For fulfilling this responsibility, museum specialists have to pay a great attention to identifying, monitoring and keeping under control all the risk factors that can produce damages to museum collections. Therefore, the aim of this paper is to present several tools and instruments that can be used by museums for managing risks. The case study conducted at a Romanian art museum revealed how data loggers, statistical analysis and diagnostic analysis helped the museum to improve its conservation activities. Since incorrect temperature and relative humidity were among the factors with the highest risk of generating damages, a special attention was paid to presenting the statistical analysis of microclimate fluctuations. This analysis played a key role in the process of identifying the causes of fluctuations and finding solutions for improvement. The results of the study develop the literature in the field of museum risk management and provide significant information for those museums interested in improving their conservation activities.
    Keywords: management, risks, conservation, museums
    JEL: H00 M19
    Date: 2022–05–31
  7. By: Olkhov, Victor
    Abstract: This paper highlights the links between the descriptions of macroeconomic variables and statistical moments of market trade, price, and return. We consider economic transactions during the averaging time interval Δ as the exclusive matter that determines the change of any economic variables. We regard the stochasticity of market trade values and volumes during Δ as the only root of the random properties of price and return. We describe how the market-based n-th statistical moments of price and return during Δ depend on the n-th statistical moments of trade values and volumes or equally on sums during Δ of the n-th power of market trade values and volumes. We introduce the secondary averaging procedure that defines statistical moments of trade, price, and return during the averaging interval Δ2>>Δ. As well, the secondary averaging during Δ2>>Δ introduces statistical moments of macroeconomic variables, which were determined as sums of economic transactions during Δ. In the coming years, predictions of the market-based probabilities of price and return will be limited by Gaussian-type distributions determined by the first two statistical moments. We discuss the roots of the internal weakness of the conventional hedging tool, Value-at-Risk, that could not be solved and thus remain the source of additional risks and losses. One should consider economic theory as a set of successive approximations, each of which describes the next array of the n-th statistical moments of market transactions and macroeconomic variables, which are repeatedly averaged during the sequence of increasing time intervals.
    Keywords: economic theory; price and return; statistical moments; market-based probabilities
    JEL: C00 E00 E17 E37 G12 G17
    Date: 2023–09–28
  8. By: Zoran Stoiljkovic
    Abstract: This thesis provides an overview of the recent advances in reinforcement learning in pricing and hedging financial instruments, with a primary focus on a detailed explanation of the Q-Learning Black Scholes approach, introduced by Halperin (2017). This reinforcement learning approach bridges the traditional Black and Scholes (1973) model with novel artificial intelligence algorithms, enabling option pricing and hedging in a completely model-free and data-driven way. This paper also explores the algorithm's performance under different state variables and scenarios for a European put option. The results reveal that the model is an accurate estimator under different levels of volatility and hedging frequency. Moreover, this method exhibits robust performance across various levels of option's moneyness. Lastly, the algorithm incorporates proportional transaction costs, indicating diverse impacts on profit and loss, affected by different statistical properties of the state variables.
    Date: 2023–10
  9. By: Selva Bahar Baziki (Bloomberg); María J. Nieto (Banco de España); Rima Turk-Ariss (Fondo Monetario Internacional)
    Abstract: We extend the literature on the sovereign-bank nexus by examining the composition effects of sovereign portfolios on banks’ risk profile, unlike previous studies which generally analyzed the determinants of banks’ sovereign portfolios or the size effects of these portfolios. We also differ from previous studies with respect to the measures of risk considered and by covering a sample period that goes well beyond the global financial crisis (2009-2018). Drawing on granular data from the European Banking Authority, we find that banks are riskier when their portfolio includes a higher proportion of securities issued by higher-risk sovereigns or when they are themselves domiciled in a country with high sovereign credit risk. Nevertheless, we do not find conclusive evidence that larger holdings of government securities of the country where the bank is incorporated increase bank risk ex-post. However, the risk profile is higher for banks that received government capital injections than for banks that did not receive capital support in the aftermath of the global financial crisis. Banks that received government capital injections are less risky when their portfolio includes a higher proportion of securities issued by higher-risk sovereigns. These results may indicate that regulatory arbitrage motives at these banks are particularly important.
    Keywords: banks, sovereign crisis, EU
    JEL: G01 G21 G28 G38
    Date: 2023–09
  10. By: Ron S. Jarmin; John M. Abowd; Robert Ashmead; Ryan Cumings-Menon; Nathan Goldschlag; Michael B. Hawes; Sallie Ann Keller; Daniel Kifer; Philip Leclerc; Jerome P. Reiter; Rolando A. Rodr\'iguez; Ian Schmutte; Victoria A. Velkoff; Pavel Zhuravlev
    Abstract: The use of formal privacy to protect the confidentiality of responses in the 2020 Decennial Census of Population and Housing has triggered renewed interest and debate over how to measure the disclosure risks and societal benefits of the published data products. Following long-established precedent in economics and statistics, we argue that any proposal for quantifying disclosure risk should be based on pre-specified, objective criteria. Such criteria should be used to compare methodologies to identify those with the most desirable properties. We illustrate this approach, using simple desiderata, to evaluate the absolute disclosure risk framework, the counterfactual framework underlying differential privacy, and prior-to-posterior comparisons. We conclude that satisfying all the desiderata is impossible, but counterfactual comparisons satisfy the most while absolute disclosure risk satisfies the fewest. Furthermore, we explain that many of the criticisms levied against differential privacy would be levied against any technology that is not equivalent to direct, unrestricted access to confidential data. Thus, more research is needed, but in the near-term, the counterfactual approach appears best-suited for privacy-utility analysis.
    Date: 2023–10

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