nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒01‒15
fourteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Reevaluation of the capital charge in insurance after a large shock: empirical and theoretical views By F. Borel-Mathurin; S. Loisel; J. Segers
  2. Corporate payments networks and credit risk rating By Elisa Letizia; Fabrizio Lillo
  3. Optimal Risk Allocation in Reinsurance Networks By Nicole B\"auerle; Alexander Glauner
  4. Quantile graphical models: prediction and conditional independence with applications to systemic risk By Alexandre Belloni; Mingli Chen; Victor Chernozhukov
  5. Classification of the Bounds on the Probability of Ruin for Lévy Processes with Light-tailed Jumps By Jérôme Spielmann
  6. Counterparty credit limits: An effective tool for mitigating counterparty risk? By Gould, Martin D.; Hautsch, Nikolaus; Howison, Sam D.; Porter, Mason A.
  7. The Cross-Section of Risk and Return By Kent Daniel; Lira Mota; Simon Rottke; Tano Santos
  8. A nonparametric copula approach to conditional Value-at-Risk By Gery Geenens; Richard Dunn
  9. On the attitude to risk and the decision-making behavior By Cocioc, Paul
  10. New approaches to regulating insurance markets in the European Union in the aftermath of the financial crisis By Eliska Hrabalova; Eva Vavrova; David Hampel
  11. Does ‘Too High’ Profitability Hamper Stability for European Banks? By P. Pessarossi; J.-L. Thevenon; L. Weill
  12. The volatility effect on precious metals prices in a stochastic volatility in mean model with time-varying parameters By Mehmet Balcilar; Zeynel Abidin Ozdemir
  13. The performance of Islamic banks in the MENA region: Are specific risks a minor attribute? By Imène Berguiga; Philippe Adair; Nadia Zrelli; Ali Abdallah
  14. Cost-benefit analysis for flood risk management and water governance in the Netherlands; an overview of one century By Bos, Frits; Zwaneveld, Peter

  1. By: F. Borel-Mathurin; S. Loisel; J. Segers
    Abstract: Motivated by the recent introduction of regulatory stress tests in the Solvency II framework, we study the impact of the re-estimation of the tail risk and of loss absorbing capacities on post-stress solvency ratios. Our contribution is threefold. First, we build the first stylized model for re-estimated solvency ratio in insurance. Second, we solve a new theoretical problem in statistical theory: what is the asymptotic impact of a record on the re-estimation of tail quantiles and tail probabilities for classical extreme value estimators? Third, we quantify the impact of the re-estimation of tail quantiles and of loss absorbing capacities on real-world solvency ratios thanks to regulatory data from EIOPA. Our analysis sheds a first light on the role of the loss absorbing capacity and its paramount importance in the Solvency II capital charge computations. We conclude with a number of policy recommendations for insurance regulators.
    Keywords: Insurance, Extreme Value Theory, Financial Regulation, Solvency II, Solvency Capital Requirement, Loss Absorbing Capacities, Stress Tests, Enterprise Risk Management.
    JEL: G22 G18 C13 C15
    Date: 2017
  2. By: Elisa Letizia; Fabrizio Lillo
    Abstract: Understanding the structure of interactions between corporate firms is critical to identify risk concentration and the possible pathways of propagation of financial distress. In this paper we consider the in- teraction due to payments and, by investigating a large proprietary dataset of Italian firms, we characterize the topological properties of the payment network. We then focus on the relation between the net- work of payments and the risk of firms. We show the existence of an homophily of risk, i.e. the tendency of firms with similar risk pro- file to be statistically more connected among themselves. This effect is observed both when considering pairs of firms and when consider- ing communities or hierarchies identified in the network. By applying machine learning techniques, we leverage this knowledge to show that network properties of a node can be used to predict the missing rating of a firm. Our results suggest that risk assessment should take quan- titatively into account also the network of interactions among firms.
    Date: 2017–11
  3. By: Nicole B\"auerle; Alexander Glauner
    Abstract: In this paper we consider reinsurance or risk sharing from a macroeconomic point of view. Our aim is to find socially optimal reinsurance treaties. In our setting we assume that there are $n$ insurance companies each bearing a certain risk and one representative reinsurer. The optimization problem is to minimize the sum of all capital requirements of the insurers where we assume that all insurance companies use a form of Range-Value-at-Risk. We show that in case all insurers use Value-at-Risk and the reinsurer's premium principle satisfies monotonicity, then layer reinsurance treaties are socially optimal. For this result we do not need any dependence structure between the risks. In the general setting with Range-Value-at-Risk we obtain again the optimality of layer reinsurance treaties under further assumptions, in particular under the assumption that the individual risks are positively dependent through the stochastic ordering. At the end, we discuss the difference between socially optimal reinsurance treaties and individually optimal ones by looking at a number of special cases.
    Date: 2017–11
  4. By: Alexandre Belloni (Institute for Fiscal Studies); Mingli Chen (Institute for Fiscal Studies and Warwick); Victor Chernozhukov (Institute for Fiscal Studies and MIT)
    Abstract: The understanding of co-movements, dependence, and influence between variables of interest is key in many applications. Broadly speaking such understanding can lead to better predictions and decision making in many settings. We propose Quantile Graphical Models (QGMs) to characterize prediction and conditional independence relationships within a set of random variables of interest. Although those models are of interest in a variety of applications, we draw our motivation and contribute to the financial risk management literature. Importantly, the proposed framework is intended to be applied to non-Gaussian settings, which are ubiquitous in many real applications, and to handle a large number of variables and conditioning events. We propose two distinct QGMs. First, Condition Independence Quantile Graphical Models (CIQGMs) characterize conditional independence at each quantile index revealing the distributional dependence structure. Second, Prediction Quantile Graphical Models (PQGMs) characterize the best linear predictor under asymmetric loss functions. A key difference between those models is the (non-vanishing) misspeci cation between the best linear predictor and the conditional quantile functions. We also propose estimators for those QGMs. Due to high-dimensionality, the two distinct QGMs require different estimators. The estimators are based on high-dimensional techniques including (a continuum of) L1-penalized quantile regressions (and low biased equations), which allow us to handle the potential large number of variables. We build upon a recent literature to obtain new results for valid choice of the penalty parameters, rates of convergence, and con dence regions that are simultaneously valid. We illustrate how to use QGMs to quantify tail interdependence (instead of mean dependence) between a large set of variables which is relevant in applications concerning with extreme events. We show that the associated tail risk network can be used for measuring systemic risk contributions. We also apply the framework to study international financial contagion and the impact of market downside movement on the dependence structure of assets' returns.
    Keywords: High-dimensional approximately sparse model, tail risk network, conditional independence, nonlinear correlation, penalized quantile regression, systemic risk, financial contagion, downside movement
    Date: 2017–12–05
  5. By: Jérôme Spielmann (LAREMA - Laboratoire Angevin de REcherche en MAthématiques - UA - Université d'Angers - CNRS - Centre National de la Recherche Scientifique)
    Abstract: In this note, we study the ultimate ruin probabilities of a real-valued Lévy process X with light-tailed negative jumps. It is well-known that, for such Lévy processes, the probability of ruin decreases as an exponential function with a rate given by the root of the Laplace exponent, when the initial value goes to infinity. Under the additional assumption that X has integrable positive jumps, we show how a finer analysis of the Laplace exponent gives in fact a complete description of the bounds on the probability of ruin for this class of Lévy processes. This leads to the identification of a case that is not considered in the literature and for which we give an example. We then apply the result to various risk models and in particular the Cramér-Lundberg model perturbed by Brownian motion.
    Keywords: Bounds, Laplace exponent, Lévy processes,MSC 2010 subject classifications: 91B30, 60G51, Ruin probabilities,Perturbed model, Lundberg equation
    Date: 2017–09–28
  6. By: Gould, Martin D.; Hautsch, Nikolaus; Howison, Sam D.; Porter, Mason A.
    Abstract: A counterparty credit limit (CCL) is a limit imposed by a financial institution to cap its maximum possible exposure to a specified counterparty. Although CCLs are designed to help institutions mitigate counterparty risk by selective diversification of their exposures, their implementation restricts the liquidity that institutions can access in an otherwise centralized pool. We address the question of how this mechanism impacts trade prices and volatility, both empirically and via a new model of trading with CCLs. We find empirically that CCLs cause little impact on trade. However, our model highlights that in extreme situations, CCLs could serve to destabilize prices and thereby influence systemic risk.
    Keywords: Counterparty Credit Limits,Counterparty Risk,Price Formation,Market Design,Systemic Risk
    Date: 2017
  7. By: Kent Daniel; Lira Mota; Simon Rottke; Tano Santos
    Abstract: In the finance literature, a common practice is to create factor-portfolios by sorting on characteristics (such as book-to-market, profitability or investment) associated with average returns. The goal of this exercise is to create a parsimonious set of factor-portfolios that explain the cross-section of average returns, in the sense that the returns of these factor-portfolios span the mean-variance efficient portfolio. We argue that this is unlikely to be the case, as factor-portfolios constructed in this way fail to incorporate information about the covariance structure of returns. By using a high statistical power methodology to forecast future covariances, we are able to construct a set of portfolios which maintains the expected return, but hedges out much of the unpriced risk. We apply our methodology to hedge out unpriced risk in the Fama and French (2015) five-factors. We find that the squared Sharpe ratio of the optimal combination of the resulting hedged factor-portfolios is 2.29, compared with 1.31 for the unhedged portfolios, and is highly statistically significant.
    JEL: G00 G1 G12 G14
    Date: 2017–12
  8. By: Gery Geenens; Richard Dunn
    Abstract: Value-at-Risk and its conditional allegory, which takes into account the available information about the economic environment, form the centrepiece of the Basel framework for the evaluation of market risk in the banking sector. In this paper, a new nonparametric framework for estimating this conditional Value-at-Risk is presented. A nonparametric approach is particularly pertinent as the traditionally used parametric distributions have been shown to be insufficiently robust and flexible in most of the equity-return data sets observed in practice. The method extracts the quantile of the conditional distribution of interest, whose estimation is based on a novel estimator of the density of the copula describing the dynamic dependence observed in the series of returns. Real-world back-testing analyses demonstrate the potential of the approach, whose performance may be superior to its industry counterparts.
    Date: 2017–12
  9. By: Cocioc, Paul
    Abstract: The paper is intended to be a synthesis of the general approaches on economic risk and economic decisions under risk. Delimitation of the risk from the uncertainty is based on Knight’s views. Basically decisions are analyzed in a conventional manner by using the expected utility hypothesis. The paradigm is presented both historycal and critically from Bernoulli to von Neumann and Morgenstern. It develops some ideas on the elements encountered in establishing the minimal acceptable level of outcomes for risk-taking. The comments and conclusions highlight certain limits on rationality in economic decision.
    Keywords: risk; risk-aversion; uncertainty; decision-making; expected-utility hypothesis
    JEL: D01 D11 D81
    Date: 2017
  10. By: Eliska Hrabalova (Department of Finance, Faculty of Business and Economics, Mendel University in Brno); Eva Vavrova (Department of Finance, Faculty of Business and Economics, Mendel University in Brno); David Hampel (Department of Statistics and Operation Analysis, Faculty of Business and Economics, Mendel University in Brno)
    Abstract: The main objective of this paper is to analyze the impact of the financial crisis on insurance markets in the European Union and to evaluate changes in the approaches to insurance regulation depending on the effects of the financial crisis. The financial crisis has triggered an identified banking crisis and has shifted through the contagion channels from the US mortgage market to other financial sectors and regions of the world. With regard to the integration of financial institutions in the EU and the globalization of financial markets, a number of regulatory proposals has emerged in recent years to address the impact of the crisis, to eliminate the trigger of the crisis and to prevent recurrence of the causes of the crisis. The authors assess the development of financial health of insurers in the European insurance markets in the period of lingering financial crisis and draw conclusions based on the analysis of the insurance sector. The methods of panel regression and resulting models were used to achieve the aim of the paper.
    Keywords: financial crisis, insurance market, regulation, supervisory authority, Directive Solvency II
    JEL: G01 G15 G22 G28
    Date: 2017–12
  11. By: P. Pessarossi; J.-L. Thevenon; L. Weill
    Abstract: We investigate how high profitability influences the occurrence of bank distress in Europe. We utilize four indicators for ‘too high’ profitability, defined as the top quantiles of earnings, in logit models to explain bank distress with a hand-collected dataset of European bank distresses over the 2001-2014 period. We test the hypothesis that profitability can be beneficial for stability until a certain level but can turn detrimental at high level. We find that ‘too high’ profitability does not reduce the occurrence of bank distress. We obtain limited evidence that the top quantiles of the profitability distribution can lead to enhance such occurrence through a time horizon of about 3 years. With the hindsight of the Great Financial Crisis, our findings therefore qualify the view that bank profitability only should be promoted to favor bank stability.
    Keywords: Bank profitability, financial distress, financial stability.
    JEL: G21 G33
    Date: 2017
  12. By: Mehmet Balcilar (Department of Economics, Eastern Mediterranean University); Zeynel Abidin Ozdemir (Gazi University, Ankara, Turkey)
    Abstract: We use the time-varying parameter stochastic volatility (TVP-SV) model and monthly data from 1962 to 2017 to examine the effect of uncertainty in the precious metal markets (gold, silver, platinum, and palladium). We find evidence that uncertainty has a largely time-varying impact on the precious metal prices. The results also show significant variation in the level of volatility, with high volatility being associated with periods of large volatility shocks corresponding to known historical events. The results show that uncertainty has a significant negative impact on the precious metal prices and the impact is more negative during higher volatility periods, implying that large volatility increases cause crashes in the precious metals markets. The market volatility is also found to be extremely persistent, implying that strong policy measures might be required to restore equilibrium. The estimates also show that price level has a positive and significant effect on the volatility and, thus, higher precious metal prices generates increased future uncertainty.
    Keywords: Precious metals; Uncertainty; Stochastic volatility; State–space.
    JEL: C22 E32
    Date: 2018
  13. By: Imène Berguiga; Philippe Adair (ERUDITE - Equipe de Recherche sur l’Utilisation des Données Individuelles en lien avec la Théorie Economique - UPEC UP12 - Université Paris-Est Créteil Val-de-Marne - Paris 12 - UPEM - Université Paris-Est Marne-la-Vallée); Nadia Zrelli; Ali Abdallah
    Abstract: Islamic banks face specific risks related to Sharia-compliant contracts. We provide an exhaustive literature review addressing the methodological issues of the measurement of performance and document the main stylised facts regarding the performance of Islamic banks (IBs) in the MENA region. We investigate 53 IBs in 11 MENA countries over 2007-2014, first using cross-sectional analysis as of year 2013. A panel data model with instrumental variables estimates the impact of risks upon the returns on assets and equity of Islamic banks. Four salient results emerge: Sharia compliance exerts an ambiguous effect upon performance; Islamic specificity is a minor attribute according to the insignificant share of profit and loss sharing (PLS) contracts in total assets; there is no relationship between Sharia compliance and specific risk;. loan loss provisions do not restrict to specific risks (PLS), hedging all risks
    Keywords: performance,risks ,cross-section analysis,Islamic banks,MENA region,panel data econometrics
    Date: 2017–12
  14. By: Bos, Frits; Zwaneveld, Peter
    Abstract: The Netherlands is a global reference for flood risk management. This reputation is based on a mix of world-class civil engineering projects and innovative concepts of water governance. For more than a century, cost-benefit analysis has been important for flood risk management and water governance in the Netherlands. It has helped to select the most effective and efficient flood risk projects and to coordinate and reconcile the interests of various policy areas, levels of government and private stakeholders. This paper provides for the first time an overview of this well-developed practice. This includes the cost-benefit analysis in the 1901 act for enclosure of the Zuiderzee, van Dantzig’s famous formula for the economically optimal strength of dikes and a whole set of cost-benefit analyses for More room for rivers and the Delta Program for the next century. Dutch practice illustrates how cost-benefit analysis can support and improve flood risk management and water governance; other countries may learn from this. Rough calculations indicate that investing in cost-benefit analysis has been a highly profitable investment for Dutch society.
    Keywords: History of cost-benefit analysis in the Netherlands, management of natural resources, optimal strength of dikes, value of statistical life, biodiversity, Lely, Tinbergen, van Dantzig, Eijgenraam, Zuiderzee Works, Delta Works, More room for rivers, Delta Program for the next century
    JEL: A1 B0 C44 D61 H54 Q5
    Date: 2017–08

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