nep-rmg New Economics Papers
on Risk Management
Issue of 2014‒10‒03
nine papers chosen by
Stan Miles
Thompson Rivers University

  1. Financial big data analysis for the estimation of systemic risks By Paola Cerchiello; Paolo Giudici
  2. Beyond dimension two: A test for higher-order tail risk By Carsten Bormann; Melanie Schienle; Julia Schaumburg;
  3. Similarities and Differences between U.S. and German Regulation of the Use of Derivatives and Leverage by Mutual Funds – What Can Regulators Learn from Each Other? By Dominika Paula Gałkiewicz; ; Melanie;
  4. Risk indicators with several lines of business: comparison, asymptotic behavior and applications to optimal reserve allocation By Peggy Cénac; Stéphane Loisel; Véronique Maume-Deschamps; Clémentine Prieur
  5. Estimation of Firms' Default Rates in terms of Intangible Assets By Saiki Tsuchiya; Shinichi Nishioka
  6. Corporate governance and bank insolvency risk : international evidence By Anginer, Deniz; Demirguc-Kunt, Asli; Huizinga, Harry; Ma, Kebin
  7. On Correlated Defaults and Incomplete Information By Wai-Ki Ching; Jia-Wen Gu; Harry Zheng
  8. The Economics Of Structured Leasing By João Pinto; Luís K. Pacheco
  9. The effect of the number of states on the validity of credit ratings By P. Lencastre; F. Raischel; P. G. Lind

  1. By: Paola Cerchiello (Department of Economics and Management, University of Pavia); Paolo Giudici (Department of Economics and Management, University of Pavia)
    Abstract: Systemic risk modelling concerns the estimation of the interrelationships between financial institutions, with the aim of establishing which of them are more central and, therefore, more contagious/subject to contagion. The aim of this paper is to develop a novel systemic risk model. A model that, differently from existing ones, employs not only the information contained in financial market prices, but also big data coming from financial tweets. From a methodological viewpoint, the novelty of our paper is the estimation of systemic risk models using two different data sources: financial markets and financial tweets, and a proposal to combine them, using a Bayesian approach. From an applied viewpoint, we present the first systemic risk model based on big data, and show that such a model can shed further light on the interrelationships between financial institutions.
    Keywords: Twitter data analysis, Graphical Gaussian models, Graphical Model selection, Banking and Finance applications, Risk Management
    Date: 2014–09
  2. By: Carsten Bormann; Melanie Schienle; Julia Schaumburg;
    Abstract: In practice, multivariate dependencies between extreme risks are often only assessed in a pairwise way. We propose a test to detect when tail dependence is truly high{dimensional and bivariate simplications would produce misleading results. This occurs when a signicant portion of the multivariate dependence structure in the tails is of higher dimension than two. Our test statistic is based on a decomposition of the stable tail dependence function, which is standard in extreme value theory for describing multivariate tail dependence. The asymptotic properties of the test are provided and a bootstrap based nite sample version of the test is suggested. A simulation study documents the good performance of the test for standard sample sizes. In an application to international government bonds, we detect a high tail{risk and low return situation during the last decade which can essentially be attributed to increased higher{order tail risk. We also illustrate the empirical consequences from ignoring higher-dimensional tail risk.
    Keywords: decomposition of tail dependence; multivariate extreme values; stable tail dependence function; subsample bootstrap; tail correlation
    JEL: C01 C46 C58
    Date: 2014–09
  3. By: Dominika Paula Gałkiewicz; ; Melanie;
    Abstract: This study analyzes current regulation with respect to the use of derivatives and leverage by mutual funds in the U.S. and Germany. After presenting a detailed overview of U.S. and German regulations, this study thoroughly compares the level of flexibility funds have in both countries. I find that funds in the U.S. and Germany face limits on direct leverage (amount of bank borrowing) of up to 33% and 10% of their net assets, respectively. Funds can extend these limits indirectly by using derivatives beyond their net assets (e.g., by selling credit default swaps protection with a notional amount equal to their net assets). Additionally, issuer-oriented rules in the U.S. and Germany account for issuer risk differently: U.S. funds have greater discretion to undervalue derivative exposure compared to German funds. All analyses of this study reveal that under existing derivative and leverage regulation, funds in both countries are able to increase risk by using derivatives up to the point at which it is possible for them to default solely due to investments in derivatives. The results of this study are highly relevant for the public and regulators.
    Keywords: Regulation, mutual funds, leverage, derivative, credit default swaps
    JEL: G15 G18
    Date: 2014–09
  4. By: Peggy Cénac (IMB - Institut de Mathématiques de Bourgogne - CNRS : UMR5584 - Université de Bourgogne); Stéphane Loisel (SAF - Laboratoire de Sciences Actuarielle et Financière - Université Claude Bernard - Lyon I (UCBL) : EA2429); Véronique Maume-Deschamps (ICJ - Institut Camille Jordan - CNRS : UMR5208 - Université Claude Bernard - Lyon I (UCBL) - Ecole Centrale de Lyon - Institut National des Sciences Appliquées [INSA] : - LYON - Université Jean Monnet - Saint-Etienne); Clémentine Prieur (INRIA Grenoble Rhône-Alpes / LJK Laboratoire Jean Kuntzmann - MOISE - CNRS : UMR5224 - INRIA - Laboratoire Jean Kuntzmann - Université Joseph Fourier - Grenoble I - Institut polytechnique de Grenoble (Grenoble INP), (Méthodes d'Analyse Stochastique des Codes et Traitements Numériques) - GdR MASCOT-NUM - CNRS : GDR3179)
    Abstract: In a multi-dimensional risk model with dependent lines of business, we propose to allocate capital with respect to the minimization of some risk indicators. These indicators are sums of expected penalties due to the insolvency of a branch while the global reserve is either positive or negative. Explicit formulas in the case of two branches are obtained for several models independent exponential, correlated Pareto). The asymptotic behavior (as the initial capital goes to infinity) is studied. For higher dimension and several periods, no explicit expression is available. Using a stochastic algorithm, we get estimations of the allocation, compare the different allocations and study the impact of dependence.
    Keywords: risk indicators; dependent lines of business; capital allocation
    Date: 2014
  5. By: Saiki Tsuchiya (Bank of Japan); Shinichi Nishioka (Bank of Japan)
    Abstract: This paper quantitatively analyzes how firms' default rates are affected by intangible assets, which play a crucial role in business management but are difficult to assess objectively. We use intangible assets such as firms' technological capability and the qualifications of senior management, for which numerical data from each firm are available. The results are as follows: (1) intangible assets have statistical explanatory power for firms' default rates in addition to financial data; (2) a model that incorporates intangible assets has greater accuracy in estimating default rates than one that incorporates only financial data, and the difference in the accuracy is statistically significant; and (3) the impact of changes in intangible assets on firms' default rates is comparable with that of changes in financial data. Based on our analysis, it may be effective to take into consideration intangible assets to enhance the accuracy in estimating firms' default rates. Therefore, in assessing firms' credit risk, it is important to enhance the information on intangible assets to objectively assess these assets.
    Keywords: Estimated default rates; Intangible assets; Logit model; Bootstrap method
    Date: 2014–02–07
  6. By: Anginer, Deniz; Demirguc-Kunt, Asli; Huizinga, Harry; Ma, Kebin
    Abstract: This paper finds that shareholder-friendly corporate governance is positively associated with bank insolvency risk, as proxied by the Z-score and the Merton's distance to default measure, for an international sample of banks over the 2004-08 period. Banks are special in that"good"corporate governance increases bank insolvency risk relatively more for banks that are large and located in countries with sound public finances, as banks aim to exploit the financial safety net. Good corporate governance is specifically associated with higher asset volatility, more nonperforming loans, and a lower tangible capital ratio. Furthermore, good corporate governance is associated with more bank risk-taking at times of rapid economic expansion. Consistent with increased risk-taking, good corporate governance is associated with a higher valuation of the implicit insurance provided by the financial safety net, especially in the case of large banks. These results underline the importance of the financial safety net and too-big-to-fail policies in encouraging excessive risk-taking by banks.
    Keywords: Banks&Banking Reform,Emerging Markets,Bankruptcy and Resolution of Financial Distress,Debt Markets,Governance Indicators
    Date: 2014–09–01
  7. By: Wai-Ki Ching; Jia-Wen Gu; Harry Zheng
    Abstract: In this paper, we study a continuous time structural asset value model for two correlated firms using a two-dimensional Brownian motion. We consider the situation of incomplete information, where the information set available to the market participants includes the default time of each firm and the periodic asset value reports. In this situation, the default time of each firm becomes a totally inaccessible stopping time to the market participants. The original structural model is first transformed to a reduced-form model. Then the conditional distribution of the default time together with the asset value of each name are derived. We prove the existence of the intensity processes of default times and also give the explicit form of the intensity processes. Numerical studies on the intensities of the two correlated names are conducted for some special cases. We also indicate the possible future research extension into three names case by considering a special correlation structure.
    Date: 2014–09
  8. By: João Pinto (Faculdade de Economia e Gestão - Universidade Católica Portuguesa, Porto); Luís K. Pacheco (Faculdade de Economia e Gestão - Universidade Católica Portuguesa, Porto)
    Abstract: A structured leasing is a new and highly flexible transaction that develops synergies between funding policy, risk management of the underlying assets, and tax benefits. It is used in particular transactions involving complex and large-scale assets, such as airplanes, ships, industrial plant and equipment, and large real estate projects. As in other tax-based techniques, the implementation of a structured leasing transaction, either a leveraged lease or a synthetic lease, is more significant when the value of the asset is large and allows for a potentially greater tax benefits’ appropriation. Structured leasing creates value by increasing liquidity and funding, reducing the funding costs, allowing sponsors to attain greater leverage and to increase tax shields, improving lessees’ risk management, and allowing lessees to maintain financial flexibility, by improving or maintaining financial ratios. Although all of the above-mentioned economic advantages, structured leasing also has problems. The most commonly referred problems of structured leases are complexity, offbalance sheet treatment, higher transaction costs, and wealth expropriation. Besides describing the economic motivations and problems of structured leasing, this paper provides details on the characteristics of structured leasing activity and reviews the most influential papers, summarizes their results, and associates them with the existing empirical evidence.
    Keywords: financing, leasing, structured leases, leveraged leases, synthetic leases
    JEL: G23 G24 G32
    Date: 2014–07
  9. By: P. Lencastre; F. Raischel; P. G. Lind
    Abstract: We explicitly test if the reliability of credit ratings depends on the total number of admissible states. We analyse open access credit rating data and show that the effect of the number of states in the dynamical properties of ratings change with time, thus giving supportive evidence that the ideal number of admissible states changes with time. We use matrix estimation methods that explicitly assume the hypothesis needed for the process to be a valid rating process. By comparing with the likelihood maximization method of matrix estimation, we quantify the "likelihood-loss" of assuming that the process is a well grounded rating process.
    Date: 2014–09

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