nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒04‒16
23 papers chosen by
Stan Miles
Thompson Rivers University

  1. On the Basel Liquidity Formula for Elliptical Distributions By Janine Balter; Alexander J. McNeil
  2. On Fairness of Systemic Risk Measures By Francesca Biagini; Jean-Pierre Fouque; Marco Frittelli; Thilo Meyer-Brandis
  3. Prediction bands for solar energy: New short-term time series forecasting techniques By Michel Fliess; Cédric Join; Cyril Voyant
  4. Approximation of Some Multivariate Risk Measures for Gaussian Risks By E. Hashorva
  5. Reducing Estimation Risk in Mean-Variance Portfolios with Machine Learning By Daniel Kinn
  6. Dependence of default probability and recovery rate in structural credit risk models: Case of Greek banks By Abdelkader Derbali; Lamia Jamel
  7. What is the Impact of Successful Cyberattacks on Target Firms? By Shinichi Kamiya; Jun-Koo Kang; Jungmin Kim; Andreas Milidonis; René M. Stulz
  8. Pricing Credit Default Swap Subject to Counterparty Risk and Collateralization By White, Alan
  9. Indifference Pricing in Reinsurance Using Coherent Monetary Criteria By Nabil Kazi-Tani
  10. Pricing Credit Default Swap Subject to Counterparty Risk and Collateralization By Alan White
  11. Boosting Fiscal Space; The Roles of GDP-Linked Debt and Longer Maturities By Jonathan David Ostry; Jun I. Kim
  12. Inf-Convolution of Choquet Integrals and Applications in Optimal Risk Transfer By Nabil Kazi-Tani
  13. Risk and systemic risk perception in the telecommunications sector in Brazil: an investor perspective assessment. By Charlita de Freitas, Luciano; Euler de Morais, Leonardo; Manuel Baigorri, Carlos
  14. Consumption volatility risk and the inversion of the yield curve By Adriana Grasso; Filippo Natoli
  15. Modelling multivariate volatilities via latent common factors By Li, Weiming; Gao, Jing; Li, Kunpeng; Yao, Qiwei
  16. Leverage—A Broader View By Manmohan Singh; Zohair Alam
  17. Estimating conditional means with heavy tails By Peng, Liang; Yao, Qiwei
  18. Multidimensional Risk Aversion: The Cardinal Sin By Louis Raymond Eeckhoudt; Elisa Pagani; Eugenio Peluso
  19. How safe is a safe asset? By De Grauwe, Paul; Ji, Yuemei
  20. Two Big Distortions: Bank Incentives for Debt Financing By Groenewegen, Jesse; Wierts, Peter
  21. How laboratory experiments could help disentangle the influences of production risk and risk preferences on input decisions By Bougherara, Douadia; Nauges, Céline
  22. Stock market reactions to wars and political risks: A cliometric perspective for a falling empire By Hanedar, Avni Önder; Yaldız Hanedar, Elmas
  23. An Analysis of the Management of Supply Chain Risk: A Study of the Islamic Fashion Industry in Bandung, Indonesia By Katlea Fitriani

  1. By: Janine Balter; Alexander J. McNeil
    Abstract: A justification of the Basel liquidity formula for risk capital in the trading book is given under the assumption that market risk-factor changes form a Gaussian white noise process over 10-day time steps and changes to P&L are linear in the risk-factor changes. A generalization of the formula is derived under the more general assumption that risk-factor changes are multivariate elliptical. It is shown that the Basel formula tends to be conservative when the elliptical distributions are from the heavier-tailed generalized hyperbolic family. As a by-product of the analysis a Fourier approach to calculating expected shortfall for general symmetric loss distributions is developed.
    Date: 2018–03
  2. By: Francesca Biagini; Jean-Pierre Fouque; Marco Frittelli; Thilo Meyer-Brandis
    Abstract: In our previous paper \cite{BFFMB}, we have introduced a general class of systemic risk measures that allow random allocations to individual banks before aggregation of their risks. In the present paper, we address the question of fairness of these allocations and we propose a fair allocation of the total risk to individual banks. We show that the dual problem of the minimization problem which identify the systemic risk measure, provides a valuation of the random allocations which is fair both from the point of view of the society/regulator and from the individual financial institutions. The case with exponential utilities which allows for explicit computation is treated in details.
    Date: 2018–03
  3. By: Michel Fliess (AL.I.E.N. - ALgèbre pour Identification & Estimation Numériques, LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau] - CNRS - Centre National de la Recherche Scientifique - Polytechnique - X); Cédric Join (AL.I.E.N. - ALgèbre pour Identification & Estimation Numériques, CRAN - Centre de Recherche en Automatique de Nancy - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, NON-A - Non-Asymptotic estimation for online systems - Inria Lille - Nord Europe - Inria - Institut National de Recherche en Informatique et en Automatique - CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189 - Université de Lille, Sciences et Technologies - Ecole Centrale de Lille - Inria - Institut National de Recherche en Informatique et en Automatique - Université de Lille, Sciences Humaines et Sociales - Institut Mines-Télécom [Paris] - CNRS - Centre National de la Recherche Scientifique); Cyril Voyant (SPE - Sciences pour l'environnement - UPP - Université Pascal Paoli - CNRS - Centre National de la Recherche Scientifique, Centre hospitalier d'Ajaccio)
    Abstract: Short-term forecasts and risk management for photovoltaic energy is studied via a new standpoint on time series: a result published by P. Cartier and Y. Perrin in 1995 permits, without any probabilistic and/or statistical assumption, an additive decomposition of a time series into its mean, or trend, and quick fluctuations around it. The forecasts are achieved by applying quite new estimation techniques and some extrapolation procedures where the classic concept of "seasonalities" is fundamental. The quick fluctuations allow to define easily prediction bands around the mean. Several convincing computer simulations via real data, where the Gaussian probability distribution law is not satisfied, are provided and discussed. The concrete implementation of our setting needs neither tedious machine learning nor large historical data, contrarily to many other viewpoints.
    Keywords: mean,quick fluctuations,time series,prediction bands,short-term forecasts,Solar energy,persistence,risk,volatility,normality tests
    Date: 2018
  4. By: E. Hashorva
    Abstract: Gaussian random vectors exhibit the loss of dimension phenomena, which relate to their joint survival tail behaviour. Besides, the fact that the components of such vectors are light-tailed complicates the approximations of various multivariate risk measures significantly. In this contribution we derive precise approximations of marginal mean excess, marginal expected shortfall and multivariate conditional tail expectation of Gaussian random vectors and highlight links with conditional limit theorems. Our study indicates that similar results hold for elliptical and Gaussian like multivariate risks.
    Date: 2018–03
  5. By: Daniel Kinn
    Abstract: In portfolio analysis, the traditional approach of replacing population moments with sample counterparts may lead to suboptimal portfolio choices. In this paper I show that selecting asset positions to maximize expected quadratic utility is equivalent to a machine learning (ML) problem, where the asset weights are chosen to minimize out of sample mean squared error. It follows that ML specifically targets estimation risk when choosing the asset weights, and that "off-the-shelf" ML algorithms obtain optimal portfolios taking parameter uncertainty into account. Linear regression is a special case of the proposed ML framework, equivalent to the traditional approach. Standard results from the machine learning literature may be used to derive conditions for when ML algorithms improve upon linear regression. Based on simulation studies and several datasets, I find that ML significantly reduce estimation risk compared to the traditional approach and several shrinkage approaches proposed in the literature.
    Date: 2018–04
  6. By: Abdelkader Derbali (Institut Supérieur de Gestion Sousse, Université de Sousse); Lamia Jamel (Université de Sousse)
    Abstract: The main idea of this paper is to examine the dependence between the probability of default (PD) and the recovery rate (RR). For the empirically methodology, we use the bootstrapped quantile regression and the simultaneous quantile regression for a sample of 17 Greece banks listed in Athens Exchange over the period of study from January 02, 2006 to December 31, 2012. The measurement of this dependence is determinate by using 7 indicators such as; the probability of default, the recovery rate, the number of defaults, the expected value of losses, the growth rate of GDP in Greece and three dummy variables (the exit of another firm of the Athens Exchange, the new firm is listed in the Athens exchange and the date of the failure of Greece). The main empirical results show that the probability of default and the recovery rate are inversely related. Based on this result, the banks are obliged to maximize their recovery rate to reduce their probability of default.
    Date: 2018
  7. By: Shinichi Kamiya; Jun-Koo Kang; Jungmin Kim; Andreas Milidonis; René M. Stulz
    Abstract: We examine which firms are targets of successful cyberattacks and how they are affected. We find that cyberattacks are more likely to occur at larger and more visible firms, more highly valued firms, firms with more intangible assets, and firms with less board attention to risk management. These attacks affect firms adversely when consumer financial information is appropriated, but seem to have little impact otherwise. Attacks where consumer financial information is appropriated are associated with a significant negative stock market reaction, an increase in leverage following greater debt issuance, a deterioration in credit ratings, and an increase in cash flow volatility. These attacks also affect sales growth adversely for large firms and firms in retail industries, and there is evidence that they decrease investment in the short run. Affected firms respond to such attacks by cutting the CEO’s bonus as a fraction of total compensation, by reducing the risk-taking incentives of management, and by taking actions to strengthen their risk management. The evidence is consistent with cyberattacks increasing boards’ assessment of target firm risk exposures and decreasing their risk appetite.
    JEL: G14 G32 G34 G35
    Date: 2018–03
  8. By: White, Alan
    Abstract: This article presents a new model for valuing a credit default swap (CDS) contract that is affected by multiple credit risks of the buyer, seller and reference entity. We show that default dependency has a significant impact on asset pricing. In fact, correlated default risk is one of the most pervasive threats in financial markets. We also show that a fully collateralized CDS is not equivalent to a risk-free one. In other words, full collateralization cannot eliminate counterparty risk completely in the CDS market.
    Keywords: valuation model; credit risk modeling; collateralization; correlation, CDS.
    JEL: C63 D46 D53 G01 G12 G13
    Date: 2018–03–20
  9. By: Nabil Kazi-Tani (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)
    Abstract: This paper focuses on a non-proportional reinsurance pricing problem, for a layer contract with reinstatements. After defining the indifference price with respect to both a concave utility function and a convex risk measure, we prove that is is contained in some interval whose bounds are easily calculable. We provide numerical examples computed from real insurance data.
    Keywords: Insurance premium calculation, Coherent risk measures, Concave monetary utility functions, Reinstatements, Reinsurance layers
    Date: 2018–03–25
  10. By: Alan White
    Abstract: This article presents a new model for valuing a credit default swap (CDS) contract that is affected by multiple credit risks of the buyer, seller and reference entity. We show that default dependency has a significant impact on asset pricing. In fact, correlated default risk is one of the most pervasive threats in financial markets. We also show that a fully collateralized CDS is not equivalent to a risk-free one. In other words, full collateralization cannot eliminate counterparty risk completely in the CDS market.
    Date: 2018–03
  11. By: Jonathan David Ostry; Jun I. Kim
    Abstract: Can debt management policy provide a way to increase fiscal space for a given path of primary fiscal balances? This note explores the role of two such policies: issuance of state-contingent debt; and issuance of longer maturity debt. New analytical models determine the debt limit and the default risk under uncertainty, and undertake numerical simulations to gauge the practical significance of the effect of debt management policies on fiscal space. The results suggest that, by managing debt along these two dimensions, economically salient gains in fiscal space are plausible for advanced and emerging markets.
    Keywords: Fiscal policy;Fiscal policy;Debt management policies;Default;Fiscal space;
    Date: 2018–03–14
  12. By: Nabil Kazi-Tani (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)
    Abstract: Motivated by reinsurance optimization, we study in this paper some particular optimal risk transfer problems, between two economic agents who do not share the same risk vision and anticipation. More precisely, we conduct an analysis of Choquet integrals, as non necessarily law invariant monetary risk measures. We first establish a new representation result of convex comonotone risk measures, then we give a representation result of Choquet integrals by introducing the notion of local distortion. This allows us to compute in an explicit manner the inf-convolution of two Choquet integrals, with examples illustrating the impact of the absence of the law invariance property.
    Keywords: Capacity, Choquet Integrals, Risk Measures, Inf-convolution, Risk transfer
    Date: 2018–03–25
  13. By: Charlita de Freitas, Luciano; Euler de Morais, Leonardo; Manuel Baigorri, Carlos
    Abstract: This article approaches the risk perception towards the Brazilian telecommunications sector and how it might affect the flow of data driven investment in the country. Empirical evaluations are carried out with risk assessment metrics, Value at Risk (VaR) and Conditional Value at Risk (CoVaR), for a sample of telecommunications companies. Such approach is complemented by a descriptive review of the sector´s potential sources of risk and contagion channels. Results present own risk for each company in the sample and their individual contribution to the systemic risk in the sector. Besides, findings suggest that systemic risk perception might play an important role on investors´ decision to invest in the telecommunications sector in Brazil. Final remarks include notes on the potential benefits of adopting risk metrics as a tool to improve governance in the sector.
    Keywords: Risk, Systemic Risk, Infrastructure, Investment
    JEL: C1 C3 C5 G38 L96
    Date: 2017–12
  14. By: Adriana Grasso (LUISS Guido Carli); Filippo Natoli (Bank of Italy)
    Abstract: We propose a consumption-based model that allows for an inverted term structure of real and nominal risk-free rates. In our framework the agent is subject to time-varying macroeconomic risk, and interest rates at all maturities depend on her risk perception, which shapes saving propensities over time. In bad times, when risk is perceived to be higher in the short- than in the long-term, the agent would prefer to hedge against low realizations of consumption in the near future by investing in long-term securities. In equilibrium, this leads to the inversion of the yield curve. Pricing time-varying consumption volatility risk is essential in order to obtain the inversion of the real curve and allows the average level and the slope of the nominal level to be priced.
    Keywords: yield curve inversion, consumption volatility risk, real interest rates, macroeconomic uncertainty, habits
    JEL: G12
    Date: 2018–03
  15. By: Li, Weiming; Gao, Jing; Li, Kunpeng; Yao, Qiwei
    Abstract: Volatility, represented in the form of conditional heteroscedasticity, plays an impor- tant role in controlling and forecasting risks in various financial operations including asset pricing, portfolio allocation, and hedging futures. However, modeling and fore- casting multi-dimensional conditional heteroscedasticity are technically challenging. As the volatilities of many financial assets are often driven by a few common and latent factors, we propose in this paper a dimension reduction method to model a multivariate volatility process and to estimate a lower-dimensional space, to be called the volatility space, within which the dynamics of the multivariate volatility process is confined. The new method is simple to use, as technically it boils down to an eigenanalysis for a non- negative definite matrix. Hence it is applicable to the cases when the number of assets concerned is in the order of thousands (using an ordinary PC/laptop). On the other hand, the model has the capability to cater for complex conditional heteroscedastic- ity behavior for multi-dimensional processes. Some asymptotic properties for the new method are established. We further illustrate the new method using both simulated and real data examples.
    Keywords: Eigenanalysis; latent factors; multi-dimensional volatility process; volatility space
    JEL: C1 L81
    Date: 2016–10–01
  16. By: Manmohan Singh; Zohair Alam
    Abstract: Traditional measures of leverage in the financial system tend to reflect bank balance sheet data. The paper argues that these traditional, bank-centric measures should be augmented by considering pledged collateral in the financial system since pledged collateral provides a measure of an important part of nonbank funding to banks. From a policy perspective, the paper suggests that a broader view on leverage will enhance our understanding of global systemic risk, and complement the theoretical work in this field by providing a link from micro-level leverage data to macro aggregates such as credit to the economy.
    Date: 2018–03–19
  17. By: Peng, Liang; Yao, Qiwei
    Abstract: When a conditional distribution has an infinite variance, commonly employed kernel smoothing methods such as local polynomial estimators for the conditional mean admit non-normal limiting distributions (Hall et al., 2002). This complicates the related inference as the conventional tests and confidence intervals based on asymptotic normality are no longer applicable, and the standard bootstrap method often fails. By utilizing the middle part of data nonparametrically and the tail parts parametrically based on extreme value theory, this paper proposes a new estimation method for conditional means, resulting in asymptotically normal estimators even when the conditional distribution has infinite variance. Consequently the standard bootstrap method could be employed to construct, for example, confidence intervals regardless of the tail heaviness. The same idea can be applied to estimating the difference between a conditional mean and a conditional median, which is a useful measure in data exploratory analysis.
    Keywords: Asymptotic normality; Conditional mean; Extreme value theory; Heavy tail
    JEL: C1
    Date: 2017–08–01
  18. By: Louis Raymond Eeckhoudt (Department of Economics (University of Verona)); Elisa Pagani (Department of Economics (University of Verona)); Eugenio Peluso (Department of Economics (University of Verona))
    Abstract: Attitudes towards multidimensional risk depend both on the shape of the indifference map under certainty and on the degree of concavity of the utility function representing preferences under risk. A decomposition of the risk premium is built on the new notion of "compensated risk aversion". The balance between the two components is shown to depend on the association of the risks. This result is then used to disentangle risk attitudes from the strength of the preferences, in the "intrinsic risk aversion" setting (Bell and Raiffa 1979).
    Keywords: Multivariate Risk Aversion, Risk Premium, Intrinsic Risk aversion, Compensated Risk Aversion, Household Risk Aversion.
    JEL: D01 D11 D81
    Date: 2017–07
  19. By: De Grauwe, Paul; Ji, Yuemei
    Abstract: This contribution focuses on a recent proposal put forward by the European Systemic Risk Board to create a “safe asset” for the eurozone based on a repackaging of the risks of sovereign bonds, in the hope of stabilising an otherwise unstable system of sovereign bond markets. In the present paper, however, authors Paul De Grauwe and Yuemei Ji argue that a financial system that is fundamentally unstable cannot be stabilised by financial engineering. To this end, they first describe the nature of the instability of the government bond markets in a monetary union and then analyse whether this proposal of creating a safe asset will succeed in stabilising government bond markets in the eurozone.
    Date: 2018–02
  20. By: Groenewegen, Jesse; Wierts, Peter
    Abstract: Systemically important banks are subject to at least two departures from the neutrality of debt versus equity financing: the tax deductibility of interest payments and implicit funding subsidies. This paper fills a gap in the literature by comparing their mechanism and interaction within a common analytical framework. Findings indicate that both the tax shield and implicit funding subsidy remain large, in the order of up to 1 percent of GDP, despite decreases in recent years. But the underlying mechanisms differ. The tax shield incentivises debt financing as it reduces tax payments to the government. The implicit funding subsidy incentivises debt financing as it lowers private bankruptcy costs. This funding subsidy is passed on to other bank stakeholders. It therefore provides incentives for increases in balance sheet size and risk taking. This, in turn, increases the value of the tax shield. Overall, these results help to explain why systemically important banks are highly leveraged. JEL Classification: G21, G32, H25
    Keywords: debt, leverage, subsidies, taxation
    Date: 2017–08
  21. By: Bougherara, Douadia; Nauges, Céline
    Abstract: The purpose of this article is to further our understanding of input choices (such as pesticides or fertilisers) when producers face production risk that depends on a random shock and on the quantity of input used. Using laboratory experiments, we study the role of risk preferences and public policies (here, a lump-sum subsidy and insurance) on producers’ input decisions in two situations: i) a risk-decreasing input; and ii) a risk-increasing input. Our findings raise questions on the sensitivity of optimal input choices to risk preferences and the relevance of the expected utility model to describe farmers’ decisions.
    Keywords: laboratory experiment; input choice; production risk; risk preferences; subsidy; insurance
    Date: 2018–03
  22. By: Hanedar, Avni Önder; Yaldız Hanedar, Elmas
    Abstract: In this paper, based on cliometric methodology we use new historical data on the most popular stocks traded at the İstanbul bourse between 1910 and 1914, to examine the effect of wars on stock market prices. During this period, the Ottoman Empire was involved in the Turco-Italian and the Balkan wars, leading to massive land losses and risks for the companies before the First World War. The data are manually collected from the available volumes of a daily Ottoman newspaper, Tanin. Our findings are surprising, as we observe only a temporary and small drop in stock prices, indicating little perceived risk by stock investors of the İstanbul bourse.
    Keywords: Cliometrics; The İstanbul stock exchange; stocks; the Turco-Italian war; the Balkan wars; Structural breaks
    JEL: E44 G1 N25
    Date: 2017–02–02
  23. By: Katlea Fitriani (Faculty of Economics, Parahyangan Catholic University, Bandung-Indonesia Author-2-Name: Natalia Christi Author-2-Workplace-Name: Faculty of Economics, Parahyangan Catholic University, Bandung-Indonesia)
    Abstract: Objective – This paper aims to analyze Supply Chain Risk (SC Risk) and Supply Chain Risk Management (SCRM) in the Islamic fashion Industry in Bandung, with a particular focus on micro and small enterprises. Moreover, this paper will demonstrate the differences between the way the micro and small enterprises view SC Risk and SCRM. Methodology/Technique – This research uses questionnaires to obtain the data. The population in this study consists of 86 firms representing the center of the hijab fashion industry in BALTOS, Bandung. The data was obtained through observation and in-depth interviews with selected micro and small enterprises in the Islamic fashion industry, as well as the distribution of questionnaires from the hijab fashion industry in BALTOS. Findings – The results of this study raise concerns relating to SC Risk and the SCRM among micro and small enterprises in the Islamic fashion industry in BALTOS. The findings demonstrate that most Muslims consider that certain market conditions involve high levels of risks, which act as a threat to their businesses. Novelty – The global and dynamic evolution of the global market has contributed to increased levels of intense competition in various markets. The analysis of Supply Chain Risk Management (SCRM) strategies, to minimize the frequency of Supply Chain (SC) risk, is therefore important.
    Keywords: Supply Chain Risk Management; Supply Chain Risk; Supply Management; Islamic Fashion Industry; Micro-Small Enterprises.
    JEL: M30 M39
    Date: 2018–02–17

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