nep-rmg New Economics Papers
on Risk Management
Issue of 2015‒02‒16
fifteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Risk weights, lending, and financial stability: Limits to model-based capital regulation By Behn, Markus; Haselmann, Rainer; Vig, Vikrant
  2. Credit Valuation Adjustment Modelling During a Global Low Interest Rate Environment By Petr Macek; Petr Teply
  3. Systemic Risk with Exchangeable Contagion: Application to the European Banking System By Umberto Cherubini; Sabrina Mulinacci
  4. Oil Volatility Risk and Expected Stock Returns By Peter Christoffersen; Xuhui (Nick) Pan
  5. How is credit scoring used to predict default in China? By Ha-Thu Nguyen
  6. Federal Reinsurance for Terrorism Risk: An Update By Congressional Budget Office
  7. Systemic Risk in the Insurance Sector: Review and Directions for Future Research By Eling, Martin; Pankoke, David
  8. On the (Ab)Use of Omega? By Bertrand Maillet; Michele Costola; Massimiliano Caporin; Gregory Jannin
  9. A New Methodology for Estimating Internal Credit Risk and Bankruptcy Prediction under Basel II Regime By M. Naresh Kumar; V. Sree Hari Rao
  10. Enhancing the reliability of performance measures in empirical based research: leverage ratios and theoretical based research By Ojo, Marianne
  11. Risk-Based Capital Requirements for Banks and International Trade By Michalski , Tomasz; Ors , Evren
  12. Quantifying Catastrophic and Climate Impacted Hazards Based on Local Expert Opinions By Tim Keighley; Thomas Longden; Supriya Mathew; Stefan Trück
  13. Spatial GAS models for systemic risk measurement By Schaumburg, Julia; Blasques, Francisco; Koopman, Siem Jan; Lucas, Andre
  14. Computer model for evaluating performance and economic risk at the level of farms of different sizes By Berevoianu, Rozi Liliana
  15. Corporate Policies with Temporary and Permanent Shocks By Décamps, Jean-Paul; Gryglewicz, S.; Morellec, E.; Villeneuve, Stéphane

  1. By: Behn, Markus; Haselmann, Rainer; Vig, Vikrant
    Abstract: Model-based capital regulation is considered to be one of the key innovations of Basel II. The objective of this innovation was to make capital charges more sensitive to risk. Using data from the German credit register, and employing a difference-indifference identification strategy, we empirically investigate how the introduction of this regulation affected the quantity and the composition of bank lending. We find that credit supplied by banks that introduced the model-based approach exhibits a higher sensitivity to model-based PDs as compared with credit supplied by banks that remained under the traditional approach. Interestingly, however, we find that risk models used for regulatory purposes tend to underpredict actual default rates. There is no such prediction error in PDs for loans under the traditional approach.
    JEL: G01 G28 G21
    Date: 2014
    URL: http://d.repec.org/n?u=RePEc:zbw:vfsc14:100430&r=rmg
  2. By: Petr Macek (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nábreží 6, 111 01 Prague 1, Czech Republic); Petr Teply (Institute of Economic Studies, Faculty of Social Sciences, Charles University in Prague, Smetanovo nábreží 6, 111 01 Prague 1, Czech Republic)
    Abstract: The 2008/2009 global crisis highlighted the vulnerabilities and inter-dependencies in the financial system including the global over-the-counter (OTC) derivatives markets, where significant counterparty credit risk prevails. In this paper, we deal with risk under Basel III banking regulation and provide credit valuation adjustment (CVA) modelling, which is a measure of the market value of counterparty credit risk. We use simulated data to develop a stress test model to determine the impact of counterparty credit risk on bank capital regulatory requirements. We developed six scenarios of different interest rate levels and from these scenarios we computed the exposure levels and CVA. Consequently, based on CVA modelling, we estimate the impact of an interest rate hike on portfolios of the top 3 Czech banks (Èeská spoøitelna, ÈSOB and Komerèní banka) and top 3 US banks (Bank of America, Citibank and JP Morgan). We conclude that i) the analyzed Czech banks report sufficient capital buffers to withstand increase of interest rates in any scenario; ii) the observed US banks with high exposure to derivatives would face significant capital shortfalls if the interest rates increase rapidly.
    Keywords: bank capital, Basel III, counterparty credit risk, credit valuation adjustment, market risk
    JEL: G21 G28 G32 G33
    Date: 2015–01
    URL: http://d.repec.org/n?u=RePEc:fau:wpaper:wp2015_01&r=rmg
  3. By: Umberto Cherubini; Sabrina Mulinacci
    Abstract: We propose a model and an estimation technique to distinguish systemic risk and contagion in credit risk. The main idea is to assume, for a set of $d$ obligors, a set of $d$ idiosyncratic shocks and a shock that triggers the default of all them. All shocks are assumed to be linked by a dependence relationship, that in this paper is assumed to be exchangeable and Archimedean. This approach is able to encompass both systemic risk and contagion, with the Marshall-Olkin pure systemic risk model and the Archimedean contagion model as extreme cases. Moreover, we show that assuming an affine structure for the intensities of idiosyncratic and systemic shocks and a Gumbel copula, the approach delivers a complete multivariate distribution with exponential marginal distributions. The model can be estimated by applying a moment matching procedure to the bivariate marginals. We also provide an easy visual check of the good specification of the model. The model is applied to a selected sample of banks for 8 European countries, assuming a common shock for every country. The model is found to be well specified for 4 of the 8 countries. We also provide the theoretical extension of the model to the non-exchangeable case and we suggest possible avenues of research for the estimation.
    Date: 2015–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1502.01918&r=rmg
  4. By: Peter Christoffersen (University of Toronto, Rotman School of Management and CREATES); Xuhui (Nick) Pan (Tulane University, A.B. Freeman School of Business)
    Abstract: After the financialization of commodity futures markets in 2004-05 oil volatility has become a strong predictor of returns and volatility of the overall stock market. Furthermore, stocks' exposure to oil volatility risk now drives the cross-section of expected returns. The difference in average return between the quintile of stocks with low exposure and high exposure to oil volatility is significant at 0.66% per month, and oil volatility risk carries a significant risk premium of -0.60% per month. In the post-financialization period, oil volatility risk is strongly related with various measures of funding liquidity constraints suggesting an economic channel for the effect.
    Keywords: option-implied volatility, oil prices, volatility risk, cross-section, factor-mimicking portfolios, financial intermediaries
    JEL: G12 G13 E44 Q02
    Date: 2014–12–02
    URL: http://d.repec.org/n?u=RePEc:aah:create:2015-06&r=rmg
  5. By: Ha-Thu Nguyen
    Abstract: In this paper, we carry out a review of literature for both traditional and sophisticated credit assessment techniques, with a particular focus on credit scoring which is broadly used as a costeffective credit risk management tool. The objective of the paper is to present a set-up of an application credit-scoring model and to estimate such a model using an auto loan data-set of one of the largest automobile manufacturers in China. The logistic regression approach, which is widely used in credit scoring, is employed to construct our scorecard. A detailed step-by-step development process is provided, as are discussions about specific modeling issues. The paper finally shows that “married”, “house owner”, “female”, age in years, “working in public institutions, foreign, or joint venture companies”, down payment rate, and maximum months on book of current accounts negatively impact the probability of default.
    Keywords: Credit Risk, Credit Scoring, Auto Loans, Logistic Regression.
    JEL: G3 C51 C52
    Date: 2015
    URL: http://d.repec.org/n?u=RePEc:drm:wpaper:2015-1&r=rmg
  6. By: Congressional Budget Office
    Abstract: The federal program that provides insurance against the risk of terrorism expired at the end of 2014. Without such a program, taxpayers will face less financial risk, but some businesses will lose or drop their terrorism coverage. Last year the Congress considered legislation to reauthorize the program but shift more risk to the private sector. Other options include limiting federal coverage to attacks using nonconventional weapons, and charging risk-based prices for federal coverage.
    JEL: G22 G28 H25 H42
    Date: 2015–01–06
    URL: http://d.repec.org/n?u=RePEc:cbo:report:49866&r=rmg
  7. By: Eling, Martin; Pankoke, David
    Abstract: This paper reviews the extant research on systemic risk in the insurance sector and outlines new areas of research in this field. We summarize and classify 43 theoretical and empirical research papers from both academia and practitioner organizations. The survey reveals that traditional insurance activity in the life, non-life, and reinsurance sectors neither contributes to systemic risk, nor increases insurers’ vulnerability to impairments of the financial system. However, non-traditional activities (e.g., CDS underwriting) might increase vulnerability and life insurers might be more vulnerable than non-life insurers due to higher leverage. Whether non-traditional activities also contribute to systemic risk is not entirely clear; however, the activities with the potential to contribute to systemic risk include underwriting financial derivatives, providing financial guarantees, and short-term funding. This paper is of interest not only to academics, but is also highly relevant for the industry, regulators, and policymakers.
    Keywords: Systemic Risk; Insurance; Solvency II; Financial Crisis
    Date: 2014–11
    URL: http://d.repec.org/n?u=RePEc:usg:sfwpfi:2014:21&r=rmg
  8. By: Bertrand Maillet (A.A.Advisors-QCG (ABN AMRO), Variances, Univ. Paris Dauphine and Orleans(LEDa-SDFi, LEO/CNRS and LBI)); Michele Costola (Department of Economics, University Of Venice Cà Foscari); Massimiliano Caporin (Department of Economics and Management, University of Padova); Gregory Jannin (A.A.Advisors-QCG (ABN AMRO), Variances, Univ. Paris-1 Pantheon-Sorbonne (PRISM))
    Abstract: Several recent finance articles employ the Omega measure, proposed by Keating and Shadwick (2002) - defined as a ratio of potential gains out of possible losses - for gauging the performance of funds or active strategies (e.g. Eling and Schuhmacher, 2007; Farinelli and Tibiletti, 2008; Annaert et al., 2009; Bertrand and Prigent, 2011; Zieling et al., 2014; Kapsos et al., 2014; Hamidi et al., 2014), in substitution of the traditional Sharpe ratio (1966), with the arguments that return distributions are not Gaussian and volatility is not, always, the relevant risk metric. Other authors also use the same criterion for optimizing (non-linear) portfolios with important downside risk. However, we wonder in this article about the relevance of such approaches. First, we show through a basic illustration that the Omega ratio is inconsistent with the Strict Inferior Second-order Stochastic Dominance criterion. Furthermore, we observe that the trade-off between return and risk, corresponding to the Omega measure, may be essentially influenced by the mean return. Next, we illustrate in static and dynamic frameworks that Omega-based optimal portfolios can be associated with traditional optimization paradigms depending on the chosen threshold used in the computation of Omega. Finally, we present some robustness checks on long-only asset and hedge fund databases that all confirm our general results.
    Keywords: C10, C11, G12.
    URL: http://d.repec.org/n?u=RePEc:ven:wpaper:2015:02&r=rmg
  9. By: M. Naresh Kumar; V. Sree Hari Rao
    Abstract: Credit estimation and bankruptcy prediction methods have been utilizing Altman's $z$ score method for the last several years. It is reported in many studies that $z$ score is sensitive to changes in accounting figures. Researches have proposed different variations to conventional $z$ score that can improve the prediction accuracy. In this paper we develop a new multivariate non-linear model for computing the $z$ score. In addition we develop a new credit risk index by fitting a Pearson type-III distribution to the transformed financial ratios. The results from our study have shown that the new $z$ score can predict the bankruptcy with an accuracy of $98.6\%$ as compared to $93.5\%$ by the Altman's $z$ score. Also, the discriminate analysis revealed that the new transformed financial ratios could predict the bankruptcy probability with an accuracy of $93.0\%$ as compared to $87.4\%$ using the weights of Altman's $z$ score.
    Date: 2015–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1502.00882&r=rmg
  10. By: Ojo, Marianne
    Abstract: As well as incorporating and exploring the role of formal analytical methods as a means of highlighting and discovering foundational and fundamental strategy issues, such as the determinants/causes of performance differences between banking institutions and other corporate structures across various jurisdictions, this paper aims to contribute to the literature on how limitations of empirical based research can be mitigated. Such causes of performance differences will incorporate a consideration of what these determinants are, how they operate, how performance should be measured, the extent to which such differences persist, the extent to which such performance measures should be relied upon. Performance measures to be incorporated in this paper will focus primarily on firm performance measures, such as leverage ratios, as well as a brief discussion of macro-economic indicators. From this perspective, the rise of macroeconomics, micro economic inefficiency debates - as well as the validity of such debates will be considered. In its aim to accentuate why many doubts have arisen as regards the reliability of the Basel III Leverage Ratio as a performance measure, and principally in respect of calibration issues, this paper will also provide an analysis of the recent updates which have taken place in respect of the Basel III Leverage Ratio and the Basel III Supplementary Leverage Ratio – both in respect of recent amendments introduced by the Basel Committee and proposals introduced in several jurisdictions such as the United Kingdom and the United States. The paper will also aim to highlight the role of enforcement and the enforceability of rules, ratios and standards, in ensuring that more comparable, consistent, objective and ultimately reliable performance measures are generated.
    Keywords: Basel III; Capital Requirements Directive IV; leverage ratios; enforcement; supervision; Binding Technical Standards; Keynesian revolution; macroeconomics; micro economic inefficiency
    JEL: D8 E3 G2 G3 G38 K2 M4
    Date: 2015–02–02
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:61789&r=rmg
  11. By: Michalski , Tomasz; Ors , Evren
    Abstract: The authors provide the first evidence that changes in risk-based capital requirements for banks affect the real economy through international trade. Using a natural experiment – mandatory Basel II adoption in its Standardized Approach by all banks in Turkey on July 1, 2012 – they investigate the impact of new risk-weights applied to commercial letters of credit (CLC) on that country’s exports to 174 countries. The authors estimate the resulting payment-term-cost elasticity of CLC-financed trade to be between -0.5 and -1 while the overall trade elasticity to be between -0.032 and -0.179. Calculations suggest that both CLC-related bank pricing and rationing channels are involved.
    Keywords: commercial letters of credit; international trade finance; exports; risk-weights; Basel II
    JEL: F14 G21 G28
    Date: 2014–10–28
    URL: http://d.repec.org/n?u=RePEc:ebg:heccah:1064&r=rmg
  12. By: Tim Keighley (Faculty of Business and Economics, Macquarie University); Thomas Longden (Faculty of Business and Economics, Macquarie University); Supriya Mathew (Northern Institute, Charles Darwin University); Stefan Trück (Faculty of Business and Economics, Macquarie University)
    Abstract: The analysis of catastrophic and climate impacted hazards is a challenging but important exercise, as the occurrence of such events is usually associated with high damage and uncertainty. Often, at the local level, there is a lack of information on rare extreme events, such that available data is not sufficient to fit a distribution and derive parameter values for the frequency and severity distributions. This paper discusses local assessments of extreme events and examines the potential of using expert opinions in order to obtain values for the distribution parameters. In particular, we illustrate a simple approach, where a local expert is required to only specify two percentiles of the loss distribution in order to provide an estimate for the severity distribution of climate impacted hazards. In our approach, we focus on so-called heavy-tailed distributions for the severity, such as the Lognormal, Weibull and Burr XII distribution. These distributions are widely used to fit data from catastrophic events and can also represent extreme losses or the so-called tail of the distribution. An illustration of the method is provided utilising an example that quantifies the risk of bushfires in a local area in Northern Sydney.
    Keywords: Catastrophic Risks, Climate Impacted Hazards, Expert Opinions, Local Level Decision Making, Loss Distribution Approach
    JEL: Q5 Q54 Q58
    Date: 2014–11
    URL: http://d.repec.org/n?u=RePEc:fem:femwpa:2014.93&r=rmg
  13. By: Schaumburg, Julia; Blasques, Francisco; Koopman, Siem Jan; Lucas, Andre
    Abstract: A new model for time-varying spatial dependencies is introduced. It forms an extension to the popular spatial lag model and can be estimated conveniently by maximum likelihood. The spatial dependence parameter is assumed to follow a generalized autoregressive score (GAS) process. The theoretical properties of the model are established and its satisfactory finite sample performance is shown in a small simulation study. In an empirical application, spatial dependencies between nine European sovereign CDS spreads are estimated for the time period from November 2008 until October 2013. The empirical model features a spatial weights matrix constructed from cross-border lending data and regressors including country-specific and Europe-wide risk factors. The estimation results indicate a high, time-varying degree of spatial spillovers in the spread data. A spatial GAS model with t-distributed errors provides the best fit. There is evidence for a downturn in spatial dependence after the Greek default in winter 2012, which can be explained economically by a change in bank regulation.
    JEL: C58 C23 G15
    Date: 2014
    URL: http://d.repec.org/n?u=RePEc:zbw:vfsc14:100632&r=rmg
  14. By: Berevoianu, Rozi Liliana
    Abstract: Computer Model for performance evaluation and economic risk is a model complex based on appropriate methodologies with specific indicators, necessary to administer the agricultural farm, management, efficient and increase its productivity. System of indicators is intended as a centralized source of information necessary to improve economic performance and efficient use of production factors by which to ensure the development of commercial farms, efficient use of input, raising yields and improve economic performance.
    Keywords: computer model, agricultural management, economic and financial indicators, economic risk
    JEL: D24 D81 L86 Q12 R0 R00
    Date: 2014–11–20
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:61763&r=rmg
  15. By: Décamps, Jean-Paul; Gryglewicz, S.; Morellec, E.; Villeneuve, Stéphane
    Abstract: We develop a dynamic model of investment, cash holdings, financing, and risk management policies in which firms face financing frictions and are subject to permanent and temporary cash ow shocks. In this model, target cash holdings depend on the long-term prospects of the firm, implying that the payout policy of the firm, its financing policy, and its cashow sensitivity of cash display a more realistic behavior than in prior models with financing frictions. In addition, risk management policies are richer and depend on the nature of cash ow shocks and potential collateral constraints. Lastly, the timing of investment and the firms initial asset mix both reect financing frictions and the joint effects of permanent and temporary shocks.
    Keywords: Corporate policies; permanent vs. temporary shocks; financing frictions.
    JEL: F32 G31 G35
    Date: 2015–01
    URL: http://d.repec.org/n?u=RePEc:tse:wpaper:28979&r=rmg

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