nep-rmg New Economics Papers
on Risk Management
Issue of 2022‒08‒08
fourteen papers chosen by

  1. Diversification Quotient: Measuring Diversification via Risk Measures By Xia Han; Liyuan Lin; Ruodu Wang
  2. How macroeconomic conditions affect systemic risk in the short and long-run? By Kurter, Zeynep O.
  3. Combining Retrospective Approximation with Importance Sampling for Optimising Conditional Value at Risk By Anand Deo; Karthyek Murthy; Tirtho Sarker
  4. Economic Scenario Generators: a risk management tool for insurance By Pierre-Edouard Arrouy; Alexandre Boumezoued; Bernard Lapeyre; Sophian Mehalla
  5. Multivariate backtests and copulas for risk evaluation By Boris David; Gilles Zumbach
  6. Managing Weather Risks Using Regenerative Ag and Crop Insurance By Griff, Lance
  7. Manage Risk in DeFi Portfolio By Hugo Inzirillo; Stanislas de Quenetain
  8. Increasing countries financial resilience through global catastrophe risk pooling By Alessio Ciullo; Eric Strobl; Simona Meiler; Olivia Martius; David N. Bresch
  9. Copula-based Risk Aggregation with Trapped Ion Quantum Computers By Daiwei Zhu; Weiwei Shen; Annarita Giani; Saikat Ray Majumder; Bogdan Neculaes; Sonika Johri
  10. Assessing the Risk of Climate Change Using Extreme Event Models By Borman, Julia
  11. Risk management in the context of the COVID19 crisis: The case of the University Hospital Center (CHU) Mohamed VI of Marrakech By Kenza Bennis; Khadija Benazzi
  12. Fundamental, technical and external factors induced positive and negative extreme events in the stock market By Anish Rai; Salam Rabindrajit Luwang; Md Nurujjaman; Kanish Debnath
  13. The (in)stability of farmers’ risk preferences By Finger, Robert; Wüpper, David; McCallum, Chloe
  14. Art as investment By Menconi, Denise

  1. By: Xia Han; Liyuan Lin; Ruodu Wang
    Abstract: The diversification quotient (DQ) is proposed as a new notion of diversification indices. Defined through a parametric family of risk measures, DQ satisfies three natural properties, namely, non-negativity, location invariance and scale invariance, which are shown to be conflicting for traditional diversification indices based on a single risk measure. We pay special attention to the two important classes of risk measures, Value-at-Risk (VaR) and Expected Shortfall (ES or CVaR). DQs based on VaR and ES enjoy many convenient technical properties, and they are efficient to optimize in portfolio selection. By analyzing the two popular multivariate models of elliptical and regular varying distributions, we find that DQ can properly distinguish tail heaviness and common shocks, which are neglected by traditional diversification indices. When illustrated with financial data, DQ is intuitive to interpret, and its performance is competitive when contrasted with other diversification methods in portfolio optimization.
    Date: 2022–06
  2. By: Kurter, Zeynep O. (University of Warwick)
    Abstract: This study quantifies the effects of macroeconomic variables on various market-based systemic-risk measures in 24 European banks over the 2008-2019 period. In a first step, I measure daily systemic risk for banks based on ∆CoVaR, MES, and SRISK frameworks, and examine the contributions of individual banks to aggregate systemic risk during specific stress events. Systemic risk in European banks has risen in the wake of the global financial crisis and the Brexit referendum result. In a second step, I investigate how macroeconomic conditions affect systemic risk in the short and long-run. I find that three systemic risk measures have a long-run stable relationship with EU industrial production, EU inflation, Euribor, and US equity market volatility, but some variables have opposite effects in the short and long-run.
    Keywords: Systemic Risk ; Value at Risk ; Quantile Regression ; DCC-GJRGARCH ; ARDL ; Banking Sector JEL classification: C22 ; G01 ; G18 ; G21 ; G32
    Date: 2022
  3. By: Anand Deo; Karthyek Murthy; Tirtho Sarker
    Abstract: This paper investigates the use of retrospective approximation solution paradigm in solving risk-averse optimization problems effectively via importance sampling (IS). While IS serves as a prominent means for tackling the large sample requirements in estimating tail risk measures such as Conditional Value at Risk (CVaR), its use in optimization problems driven by CVaR is complicated by the need to tailor the IS change of measure differently to different optimization iterates and the circularity which arises as a consequence. The proposed algorithm overcomes these challenges by employing a univariate IS transformation offering uniform variance reduction in a retrospective approximation procedure well-suited for tuning the IS parameter choice. The resulting simulation based approximation scheme enjoys both the computational efficiency bestowed by retrospective approximation and logarithmically efficient variance reduction offered by importance sampling
    Date: 2022–06
  4. By: Pierre-Edouard Arrouy (Recherche et Développement, Milliman Paris - Milliman); Alexandre Boumezoued (Recherche et Développement, Milliman Paris - Milliman); Bernard Lapeyre (ENPC - École des Ponts ParisTech); Sophian Mehalla (Recherche et Développement, Milliman Paris - Milliman)
    Abstract: We present a risk management tool, named Economic Scenario Generator (ESG), used by insurance companies for simulating the global state of one or several economies described by key financial risk drivers. This tool is of particular use within the Solvency II framework, since insurance companies are required to value their balance-sheet from a market-consistent viewpoint. However, there is no observable price of insurance contracts hence the necessity of relying on ESGs to perform Monte Carlo simulations useful for valuation. As such, the calibration of Risk-Neutral models underlying this valuation is of particular interest as there is a strong requirement to match observable market prices. Furthermore, for a variety of applications, the insurance company has to value its balance-sheet over a set of different economic conditions, leading to the need of intensive re-calibrations of such models. In this paper, we first provide an overview of the key requirements from Solvency II and their practical implications for insurance valuation. We then describe the different use cases of ESGs. A particular attention is paid to Risk-Neutral interest rates models, specifically the Libor Market Model with a stochastic volatility. We discuss the complexity of its calibration and describe fast calibration methods based on approximations and expansions of the probability density function. Comparisons with more common method highlight the reduction in calibration time.
    Date: 2022–05–18
  5. By: Boris David; Gilles Zumbach
    Abstract: Risk evaluation is a forecast, and its validity must be backtested. Probability distribution forecasts are used in this work and allow for more powerful validations compared to point forecasts. Our aim is to use bivariate copulas in order to characterize the in-sample copulas and to validate out-of-sample a bivariate forecast. For both set-ups, probability integral transforms (PIT) and Rosenblatt transforms are used to map the problem into an independent copula. For this simple copula, statistical tests can be applied to validate the choice of the in-sample copula or the validity of the bivariate forecast. The salient results are that a Student copula describes well the dependencies between financial time series (regardless of the correlation), and that the bivariate forecasts provided by a risk methodology based on historical innovations performs correctly out-of-sample. A prerequisite is to remove the heteroskedasticity in order to have stationary time series, in this work a long-memory ARCH volatility model is used.
    Date: 2022–06
  6. By: Griff, Lance
    Keywords: Environmental Economics and Policy, Risk and Uncertainty
    Date: 2022–02
  7. By: Hugo Inzirillo; Stanislas de Quenetain
    Abstract: Decentralized Finance (DeFi) is a new financial industry built on blockchain technologies. Decentralized financial services increased consequantly, the ability to lend, borrow and invest in decentralized investment vehicules, allowing investors to bypass third party intermediaries. DeFI promise is to reduce transactions costs, management fees while increasing the trust between agents of this financial industry 3.0. This paper provides an overview of Decentralized Finance different components as well as the risks involved in investing through these new vehicles. It also proposes an allocation methodology which integrate and quantify these risks.
    Date: 2022–05
  8. By: Alessio Ciullo; Eric Strobl; Simona Meiler; Olivia Martius; David N. Bresch
    Abstract: Extreme weather events can have severe impacts on national economies, leading the recovery of low- to middle-income countries to become reliant on foreign financial aid. Foreign aid, however, is slow and uncertain. Therefore, the Sendai Framework and the Paris Agreement advocate for more resilient financial instruments like sovereign catastrophe risk pools. Existing pools, however, might not fully exploit financial resilience potentials because they were not designed with the goal of maximizing risk diversification and they pool risk only regionally. To address this, we introduce a method that forms pools maximizing risk diversification and which selects countries with low bilateral correlations or low shares in the pool risk. We apply the method to explore the benefits of global pooling with respect to regional pooling. We find that global pooling increases risk diversification, it lowers countries shares in the pool risk and it increases the number of countries profiting from risk pooling.
    Date: 2022–06
  9. By: Daiwei Zhu; Weiwei Shen; Annarita Giani; Saikat Ray Majumder; Bogdan Neculaes; Sonika Johri
    Abstract: Copulas are mathematical tools for modeling joint probability distributions. Since copulas enable one to conveniently treat the marginal distribution of each variable and the interdependencies among variables separately, in the past 60 years they have become an essential analysis tool on classical computers in various fields ranging from quantitative finance and civil engineering to signal processing and medicine. The recent finding that copulas can be expressed as maximally entangled quantum states has revealed a promising approach to practical quantum advantages: performing tasks faster, requiring less memory, or, as we show, yielding better predictions. Studying the scalability of this quantum approach as both the precision and the number of modeled variables increase is crucial for its adoption in real-world applications. In this paper, we successfully apply a Quantum Circuit Born Machine (QCBM) based approach to modeling 3- and 4-variable copulas on trapped ion quantum computers. We study the training of QCBMs with different levels of precision and circuit design on a simulator and a state-of-the-art trapped ion quantum computer. We observe decreased training efficacy due to the increased complexity in parameter optimization as the models scale up. To address this challenge, we introduce an annealing-inspired strategy that dramatically improves the training results. In our end-to-end tests, various configurations of the quantum models make a comparable or better prediction in risk aggregation tasks than the standard classical models. Our detailed study of the copula paradigm using quantum computing opens opportunities for its deployment in various industries.
    Date: 2022–06
  10. By: Borman, Julia
    Keywords: Environmental Economics and Policy, Risk and Uncertainty
    Date: 2022–02
  11. By: Kenza Bennis (INREDD - Innovation, Responsabilités et Développement Durable - UCA - Université Cadi Ayyad [Marrakech]); Khadija Benazzi (INREDD - Innovation, Responsabilités et Développement Durable - UCA - Université Cadi Ayyad [Marrakech])
    Abstract: In times of crisis, multidimensional and interconnected risks appear. Indeed, if a risk is not managed with the most appropriate techniques, methods and tools, it can easily destroy an entire structure and system. In the context of the Covid19 crisis, we explored, through semi-directive interviews, the case of the Mohamed VI University Hospital Center (CHU) as one of the most affected public health care institutions in Morocco. In reality, the onset of a pandemic crisis was unpredictable and unimaginable, and public health care institutions had no room for error since the health and lives of citizens were at stake. They were challenged to adjust and adapt agilely and very quickly to deal with the emergency. The objective of this work is to understand and analyze how the University Hospital of Marrakech (3rd level hospital) was able to manage the different risks (psychosocial, related to decision-making, related to safety at work, related to the lack of human and financial resources, and relatedto the external environment) and respond to the repercussions and challenges of the crisis. Based on the results of the exploratory study, we were able to answer our main research question and develop a set of conclusions, and recommendations concerning mainlythe importance of improving risk management in these hospitals (including specific techniques and tools), and developing the hospital structure, emergency mechanisms and capacities for adaptation and resilience in order to cope with internal and external pressures.
    Abstract: En temps de crise, des risques multidimensionnels et interconnectés apparaissent. En effet, si un risque n'est pas managé avec les techniques, les méthodes et les outils les plus appropriés, il peut facilement détruire toute une structure et tout un système. Dans le cadre de la crise Covid19, nous avons exploré, par des entretiens semi-directifs, le cas du Centre Hospitalier Universitaire (CHU) Mohamed VI comme étant un des établissements publicsde soinsde santé les plus touchés au Maroc.Réellement, l'apparitiond'une crise pandémique était imprédictible etinimaginable, lesétablissements publics de soins de santé n'avaientsurtoutpas le droit à l'erreur puisque la santé et la vie des citoyens étaient en jeu. Ils ont été mis au défi de s'ajuster et de s'adapter agilement et très rapidement pour faire face à l'urgence. L'objectif de ce travail est de comprendre et analyser comment le CHU de Marrakech(établissementhospitalier de 3emeniveau)a pu manager les différents risques(psychosociaux, liés à la prise de décision, liés à la sécurité au travail, liés à l'insuffisance des ressources humaines et financières, et ceux liés à l'environnement externe) etrépondre aux répercussions et challenges de la crise. En nousbasant sur les résultats de l'étude exploratoire, nous avons pu répondre à notre problématique et à développer à un ensemble de conclusions et recommandations concernant principalement l'importance d'améliorer le management du risque dans ces établissements hospitaliers (y compris des techniques et des outils spécifiques), et de développerla structure hospitalière, les mécanismes d'urgences et les capacités d'adaptation et de résilience face aux pressions internes et externes.
    Keywords: Crisis,Covid19,Risk Management,Crisis Management,Public health care institutions,La crise,covid19,management du risque,gestion de crise,établissement public de soin de santé.
    Date: 2022–05–31
  12. By: Anish Rai; Salam Rabindrajit Luwang; Md Nurujjaman; Kanish Debnath
    Abstract: Sporadic large fluctuations in stock price are seen in the stock market. Such large fluctuations occur due to three important factors: (a) the significant change in the fundamental parameters like excellent or bad results; (b) the formation of a special technical setup in the stock price like double-bottom and (c) external factors like war. These factors may lead to occasional and rare upsurge or crash of significant height in the stock price, and such upsurge or crash is termed as positive or negative extreme event (EE), respectively. In this work, we have identified EE in the stock price of selected companies from global stock markets due to the above factors in minute, daily, weekly time-scales. Augmented Dickey-Fuller and degree of nonstationarity tests show that the stock price time-series is nonstationary. Subsequently, we applied the Hilbert-Huang transformation to identify EE. The analysis shows that the instantaneous energy ($IE$) concentration in the stock price is very high during an EE with $IE>E_{\mu}+4\sigma,$ where $E_{\mu}$ and $\sigma$ are the mean energy and standard deviation of energy, respectively. The analysis shows that investor can gain or lose a significant amount of their capital due to these events. Hence, identification of the EEs in the stock market is important as it helps the investor and trader to take rational decisions during such crisis. Investors should carefully monitor the factors that lead to EEs for entry or exit strategies in the market.
    Date: 2022–06
  13. By: Finger, Robert; Wüpper, David; McCallum, Chloe
    Abstract: We test and quantify the (in)stability of farmer risk preferences, accounting for both the instability across elicitation methods and the instability over time. We used repeated measurements (N=1530) with Swiss fruit and grapevine producers over 3 years, where different risk preference elicitation methods (domain-specific self-assessment and incentivized lotteries) were used. We find that farmers’ risk preferences change considerably when measured using different methods. For example, self-reported risk preference and findings from a Holt and Laury lottery correlate only weakly (correlation coefficients range from 0.06 to 0.23). Moreover, we find that risk preferences vary considerable over time too, i.e. applying the same elicitation method to the same farmer in a different point in time results in different risk preference estimates. Our results show self-reported risk preferences are moderately correlated (correlation coefficients range from 0.42 to 0.55) from one year to another. Finally, we find experiencing climate and pest related crop damages is associated with farmers becoming more risk loving.
    Keywords: Research Methods/ Statistical Methods, Risk and Uncertainty
    Date: 2022–04
  14. By: Menconi, Denise
    Abstract: This paper applies the Fama-French three-factors model, augmented with Momentum and Liquidity factors, to analyze Art as an Investment. It also compares investing in Art to several other traditional and non-traditional investments. There is evidence that Market and Momentum factors explain the risk premia in some Art sub-segments. The Market Beta, in particular, is lower than what is found in the existing literature, whereas the Momentum factor might explain part of the premia of Contemporary Art and Old Masters. There is no evidence, however, that Art and its subsegments command a Liquidity premium. The paper also discusses the efficient share of Art in a diversified portfolio.
    Date: 2022–03–14

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