New Economics Papers
on Risk Management
Issue of 2010‒11‒20
eleven papers chosen by

  1. Measuring sectoral/geographic concentration risk By Vincenzo Tola
  2. Bank capital : lessons from the financial crisis By Demirguc-Kunt, Asli; Detragiache, Enrica; Merrouche, Ouarda
  3. LGD credit risk model: estimation of capital with parameter uncertainty using MCMC By Xiaolin Luo; Pavel Shevchenko
  4. Analyzing Systemic Risk with Financial Networks An Application During a Financial Crash By Saltoglu, Burak; Yenilmez, Taylan
  5. Evaluating Value-at-Risk Models via Quantile Regression By Wagner Piazza Gaglianone; Luiz Renato Lima; Oliver Linton; Daniel Smith
  6. "GH skew Student's t-distribution in stochastic volatility model with application to stock returns" (in Japanese) By Jouchi Nakajima; Yasuhiro Omori
  7. Understanding Systemic Risk: The Trade-Offs between Capital, Short-Term Funding and Liquid Asset Holdings By Céline Gauthier; Zhongfang He; Moez Souissi
  8. Censored Gamma Regression Models for Limited Dependent Variables with an Application to Loss Given Default By Fabio Sigrist; Werner A. Stahel
  9. Moral Hazard and Ambiguity By Philipp Weinschenk
  10. Homeownership for the long run: an analysis of homeowner subsidies By O. Emre Ergungor
  11. Fallacies, Irrelevant Facts, and Myths in the Discussion of Capital Regulation: Why Bank Equity is Not Expensive By Anat R. Admati; Peter M. DeMarzo; Martin F. Hellwig; Paul Pfleiderer

  1. By: Vincenzo Tola (Banca d'Italia)
    Abstract: This article focuses on the application of the Pykhtin model to the Italian banking system to measure concentration risk by industry sector and geographic region. The proposed approach generalizes the portfolio model used in Pillar 1 for the calculation of the capital requirement, removing the assumptions of the existence of one systematic risk factor and of an infinitely granular portfolio. The difference between the unexpected loss stemming from the Pykhtin model and that calculated using the supervisory formula can be interpreted as a measure of concentration risk. The Pykhtin model is consistent with the Basel II framework. It accordingly generates an unexpected loss measure that is in line with the IRB capital requirements. The proposed model therefore has the advantage of “speaking the language of supervisors”. This approach makes it possible to interpret the difference between regulatory and economic capital. It also enables concentration risk to be broken down into its two components: single-name and sectoral/geographic concentration risk. The empirical results show the model’s ability to generate internally coherent rankings that are close to the economic intuition: exposure to sectoral/geographic concentration risk is negatively correlated to banks’size.
    Keywords: Basel 2, concentration risk, economic capital, VaR
    JEL: G21
    Date: 2010–10
  2. By: Demirguc-Kunt, Asli; Detragiache, Enrica; Merrouche, Ouarda
    Abstract: Using a multi-country panel of banks, the authors study whether better capitalized banks fared better in terms of stock returns during the financial crisis. They differentiate among various types of capital ratios: the Basel risk-adjusted ratio; the leverage ratio; the Tier I and Tier II ratios; and the common equity ratio. They find several results: (i) before the crisis, differences in capital did not affect subsequent stock returns; (ii) during the crisis, higher capital resulted in better stock performance, most markedly for larger banks and less well-capitalized banks; (iii) the relationship between stock returns and capital is stronger when capital is measured by the leverage ratio rather than the risk-adjusted capital ratio; (iv) there is evidence that higher quality forms of capital, such as Tier 1 capital, were more relevant. They also examine the relationship between bank capitalization and credit default swap (CDS) spreads.
    Keywords: Banks&Banking Reform,Access to Finance,Debt Markets,Economic Theory&Research,Banking Law
    Date: 2010–11–01
  3. By: Xiaolin Luo; Pavel Shevchenko
    Abstract: This paper investigates the impact of parameter uncertainty on capital estimate in the well-known extended Loss Given Default (LGD) model with systematic dependence between default and recovery. We demonstrate how the uncertainty can be quantified using the full posterior distribution of model parameters obtained from Bayesian inference via Markov chain Monte Carlo (MCMC). Results show that the parameter uncertainty and its impact on capital can be very significant. We have also quantified the effect of diversification for a finite number of borrowers in comparison with the infinitely granular portfolio.
    Date: 2010–11
  4. By: Saltoglu, Burak; Yenilmez, Taylan
    Abstract: A financial network model, where the coded identity of the counterparties of every trade is known, is applied to both stable and crisis periods in a large and liquid overnight repo market in an emerging market economy. We have analyzed the financial crisis by using various network investigation tools such as links, interconnectivity, and reciprocity. In addition, we proposed a centrality measure to monitor and detect the ‘systemically important financial institution’ in the financial system. We have shown that our measure gives strong signals much before the crisis.
    Keywords: systemic risk; financial regulation; financial crisis; BASEL III; systemically important financial institution; Turkey; IMF
    JEL: D53 C45 F47 D85 C01
    Date: 2010–11–14
  5. By: Wagner Piazza Gaglianone (Central Bank of Brazil and Fucape Buisness School); Luiz Renato Lima (University of Tennessee and EFGE-FGV); Oliver Linton (London School of Economics); Daniel Smith (Simon Fraser University and QUT)
    Abstract: This paper is concerned with evaluating Value-at-Risk estimates. It is well known that using only binary variables, such as whether or not there was an exception, sacrifices too much information. However, most of the specification tests (also called backtests) available in the literature, such as Christofferson (1998) and Engle and Mangenelli (2004) are based on such variables. In this paper we propose a new backtest that does not rely solely on binary variables. It is shown that the new backtest provides a sufficient condtion to assess the finite sample performance of a quantile model whereas the existing ones do not. The proposed methodolgy allows us to identify periods of an increased risk exposure based on a quantile regression model (Koenker and Xiao, 2002). Our theoretical findings are corroborated through a Monte Carlo simulation and an empirical exercise with daily S&P500 time series.
    Keywords: Value-at-Risk, Backtesting, Quantile Regression
    JEL: C12 C14 C52 G11
    Date: 2010–11–05
  6. By: Jouchi Nakajima (Department of Statistical Science, Duke University); Yasuhiro Omori (Faculty of Economics, University of Tokyo)
    Abstract: This paper represents empirical studies of SV models with a generalized hyperbolic (GH) skew Student's t-error distribution to embed both asymmetric heavy-tailness and leverage effects for financial time series. An efficient Markov chain Monte Carlo estimation method is described and the model is fit to daily S&P500 stock returns. The practical importance of the proposed model is highlighted through the model comparison based on the marginal likelihood, Value at Risk (VaR) and expected shortfall. The empirical results show that incorporating leverage and asymmetric heavy-tailness contributes to the model fit and predicting the expected shortfall.
    Date: 2010–11
  7. By: Céline Gauthier; Zhongfang He; Moez Souissi
    Abstract: We offer a multi-period systemic risk assessment framework with which to assess recent liquidity and capital regulatory requirement proposals in a holistic way. Following Morris and Shin (2009), we introduce funding liquidity risk as an endogenous outcome of the interaction between market liquidity risk, solvency risk, and the funding structure of banks. To assess the overall impact of different mix of capital and liquidity, we simulate the framework under a severe but plausible macro scenario for different balance-sheet structures. Of particular interest, we find that (1) capital has a decreasing marginal effect on systemic risk, (2) increasing capital alone is much less effective in reducing liquidity risk than solvency risk, (3) high liquid asset holdings reduce the marginal effect of increasing short term liability on systemic risk, and (4) changing liquid asset holdings has little effect on systemic risk when short term liability is sufficiently low.
    Keywords: Financial stability; Financial system regulation and policies
    JEL: G21 C15 C81 E44
    Date: 2010
  8. By: Fabio Sigrist; Werner A. Stahel
    Abstract: Regression models for limited continuous dependent variables having a non-negligible probability of attaining exactly their limits are presented. The models differ in the number of parameters and in their flexibility. It is shown how to fit these models and they are applied to a Loss Given Default dataset from insurance to which they provide a good fit.
    Date: 2010–11
  9. By: Philipp Weinschenk (Max Planck Institute for Research on Collective Goods)
    Abstract: We consider a principal-agent model with moral hazard where the agent’s knowledge about the performance measure is ambiguous and he is averse towards ambiguity. We show that the principal may optimally provide no incentives or contract only on a subset of all informative performance measures. That is, the Informativeness Principle does not hold in our model. These results stand in stark contrast to the ones of the orthodox theory, but are empirically of high relevance.
    Keywords: financial crisis, Basel Accord, banking regulation, capital requirements, modelbased approach, systemic risk
    JEL: D82 M12 M52
    Date: 2010–09
  10. By: O. Emre Ergungor
    Abstract: This paper examines the impact of interest-rate and down-payment subsidies on default rates and losses given default, and finds that down-payment subsidies create successful homeowners at a lower cost than interest-rate subsidies.
    Keywords: Mortgage loans ; Default (Finance) ; Housing - Finance
    Date: 2010
  11. By: Anat R. Admati (Graduate School of Business, Stanford University); Peter M. DeMarzo (Graduate School of Business, Stanford University); Martin F. Hellwig (Max Planck Institute for Research on Collective Goods); Paul Pfleiderer (Graduate School of Business, Stanford University)
    Abstract: We examine the pervasive view that “equity is expensive,” which leads to claims that high capital requirements are costly and would affect credit markets adversely. We find that arguments made to support this view are either fallacious, irrelevant, or very weak. For example, the return on equity contains a risk premium that must go down if banks have more equity. It is thus incorrect to assume that the required return on equity remains fixed as capital requirements increase. It is also incorrect to translate higher taxes paid by banks to a social cost. Policies that subsidize debt and indirectly penalize equity through taxes and implicit guarantees are distortive. Any desirable public subsidies to banks’ activities should be given directly and not in ways that encourage leverage. Finally, suggestions that high leverage serves a necessary disciplining role are based on inadequate theory lacking empirical support. We conclude that bank equity is not socially expensive, and that high leverage is not necessary for banks to perform all their socially valuable functions, including lending, taking deposits and issuing money-like securities. To the contrary, better capitalized banks suffer fewer distortions in lending decisions and would perform better. The fact that banks choose high leverage does not imply that this is socially optimal, and, viewed from an ex ante perspective, high leverage may not even be privately optimal for banks. Setting equity requirements significantly higher than the levels currently proposed would entail large social benefits and minimal, if any, social costs. Approaches based on equity dominate alternatives, including contingent capital. To achieve better capitalization quickly and efficiently and prevent disruption to lending, regulators must actively control equity payouts and issuance. If remaining challenges are addressed, capital regulation can be a powerful tool for enhancing the role of banks in the economy.
    Keywords: capital regulation, financial institutions, capital structure, too big to fail, systemic risk, bank equity, contingent capital, Basel.
    JEL: G32 K23 G21 G28 G38 H81
    Date: 2010–09

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