nep-rmg New Economics Papers
on Risk Management
Issue of 2012‒03‒08
eleven papers chosen by
Stan Miles
Thompson Rivers University

  1. Next Generation System-Wide Liquidity Stress Testing By Heiko Hesse; Christian Schmieder; Claus Puhr; Benjamin Neudorfer; Stefan W. Schmitz
  2. "The connection between distortion risk measures and ordered weighted averaging operators" By Jaume Belles-Sampera; José M. Merigó; Montserrat Guillén; Miguel Santolino
  3. Risk minimization and set-valued average value at risk via linear vector optimization By Andreas H. Hamel; Birgit Rudloff; Mihaela Yankova
  4. Does Basel II Pillar 3 Risk Exposure Data help to Identify Risky Banks? By Ralf Sabiwalsky
  5. Quantile Regression in Risk Calibration By Shih-Kang Chao; Wolfgang Karl Härdle; Weining Wang
  6. Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests By Elena-Ivona Dumitrescu; Christophe Hurlin; Vinson Pham
  7. A Model of Endogenous Extreme Events By Chollete, Loran
  8. Bank Funding Structures and Risk: Evidence from the Global Financial Crisis By Francisco F. Vázquez; Pablo Federico
  9. Bank Capital Adequacy in Australia By Niamh Sheridan; B. Jang
  10. Active margin system for margin loans using cash and stock as collateral and its application in Chinese market By Guanghui Huang; Weiqing Gu; Wenting Xing; Hongyu Li
  11. Supply Shocks and the Cyclical Behaviour of Bank Lending Rates under the Basel Accords By Roy Zilberman

  1. By: Heiko Hesse; Christian Schmieder; Claus Puhr; Benjamin Neudorfer; Stefan W. Schmitz
    Abstract: A framework to run system-wide, balance sheet data-based liquidity stress tests is presented. The liquidity framework includes three elements: (a) a module to simulate the impact of bank run scenarios; (b) a module to assess risks arising from maturity transformation and rollover risks, implemented either in a simplified manner or as a fully-fledged cash flow-based approach; and (c) a framework to link liquidity and solvency risks. The framework also allows the simulation of how banks cope with upcoming regulatory changes (Basel III), and accommodates differences in data availability. A case study shows the impact of a "Lehman" type event for stylized banks.
    Keywords: Bank supervision , Banks , Financial risk , Liquidity management , Risk management ,
    Date: 2012–01–09
  2. By: Jaume Belles-Sampera (Faculty of Economics, University of Barcelona); José M. Merigó (Faculty of Economics, University of Barcelona); Montserrat Guillén (Faculty of Economics, University of Barcelona); Miguel Santolino (Faculty of Economics, University of Barcelona)
    Abstract: Distortion risk measures summarize the risk of a loss distribution by means of a single value. In fuzzy systems, the Ordered Weighted Averaging (OWA) and Weighted Ordered Weighted Averaging (WOWA) operators are used to aggregate a large number of fuzzy rules into a single value. We show that these concepts can be derived from the Choquet integral, and then the mathematical relationship between distortion risk measures and the OWA and WOWA operators for discrete and nite random variables is presented. This connection oers a new interpretation of distortion risk measures and, in particular, Value-at-Risk and Tail Value-at-Risk can be understood from an aggregation operator perspective. The theoretical results are illustrated in an example and the degree of orness concept is discussed.
    Keywords: Fuzzy systems; Degree of orness; Risk quantification; Discrete random variable JEL classification:C02,C60
    Date: 2012–01
  3. By: Andreas H. Hamel; Birgit Rudloff; Mihaela Yankova
    Abstract: In this paper, the market extension of set-valued risk measures for models with proportional transaction costs is linked with set-valued risk minimization problems. As a particular example, the set-valued average value at risk (AV@R) is defined and its market extension and corresponding risk minimization problems are studied. We show that for a finite probability space the calculation of the values of AV@R reduces to linear vector optimization problems which can be solved using known algorithms. The formulation of AV@R as a linear vector optimization problem is an extension of the corresponding scalar result by Rockafellar and Uryasev.
    Date: 2012–02
  4. By: Ralf Sabiwalsky
    Abstract: Basel II Pillar 3 reports provide information about banks' exposure towards a number of risk factors, such as corporate credit risk and interest rate risk. Previous studies nd that the quality of such information is likely to be weak. We analyze the marginal contribution of pillar 3 exposure data to the quality of equity volatility forecasts for individual banks. Our method uses (local in time) measures of risk factor risk using a multivariate stochastic volatility model for ve risk factors, and uses measures of bank sensitivity with respect to these risk factors. We use two sets of sensitivity measures. One takes into account pillar 3 information, and the other one does not. Generally, we generate volatility forecasts as if no market prices of equity were available for the bank the forecast is made for. We do this for banks for which such data is, in fact, available so that we can conduct ex post - tests of the quality of volatility forecasts. We nd that (1) pillar 3 information allows for a better-than-random ranking of banks according to their risk, but (2) pillar 3 exposure data does not help reduce volatility forecast error magnitude.
    Keywords: Risk Reporting, Stochastic Volatility, Risk Factors
    JEL: G17 G21
    Date: 2012–02
  5. By: Shih-Kang Chao; Wolfgang Karl Härdle; Weining Wang
    Abstract: Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a stressful situation for one market participant, one likes to measure how this stress affects other factors. The CoVaR (Conditional VaR) framework has been developed for this purpose. The basic technical elements of CoVaR estimation are two levels of quantile regression: one on market risk factors; another on individual risk factor. Tests on the functional form of the two-level quantile regression reject the linearity. A flexible semiparametric modeling framework for CoVaR is proposed. A partial linear model (PLM) is analyzed. In applying the technology to stock data covering the crisis period, the PLM outperforms in the crisis time, with the justification of the backtesting procedures. Moreover, using the data on global stock markets indices, the analysis on marginal contribution of risk (MCR) defined as the local first order derivative of the quantile curve sheds some light on the source of the global market risk.
    Keywords: CoVaR, Value-at-Risk, quantile regression, locally linear quantile regression, partial linear model, semiparametric model
    JEL: C14 C21 C22 C53 G01 G10 G20 G32
    Date: 2012–01
  6. By: Elena-Ivona Dumitrescu (LEO - Laboratoire d'économie d'Orleans - CNRS : UMR6221 - Université d'Orléans); Christophe Hurlin (LEO - Laboratoire d'économie d'Orleans - CNRS : UMR6221 - Université d'Orléans); Vinson Pham (UCSC - University of California at Santa Cruz - University of California at Santa Cruz)
    Abstract: In this paper we propose a new tool for backtesting that examines the quality of Value-at- Risk (VaR) forecasts. To date, the most distinguished regression-based backtest, proposed by Engle and Manganelli (2004), relies on a linear model. However, in view of the di- chotomic character of the series of violations, a non-linear model seems more appropriate. In this paper we thus propose a new tool for backtesting (denoted DB) based on a dy- namic binary regression model. Our discrete-choice model, e.g. Probit, Logit, links the sequence of violations to a set of explanatory variables including the lagged VaR and the lagged violations in particular. It allows us to separately test the unconditional coverage, the independence and the conditional coverage hypotheses and it is easy to implement. Monte-Carlo experiments show that the DB test exhibits good small sample properties in realistic sample settings (5% coverage rate with estimation risk). An application on a portfolio composed of three assets included in the CAC40 market index is nally proposed.
    Keywords: Value-at-Risk; Risk Management; Dynamic Binary Choice Models
    Date: 2012–02–07
  7. By: Chollete, Loran (UiS)
    Abstract: .
    Keywords: Endogenous Risk; Extreme Event; Financial Congestion; Network; Public Good
    JEL: D62 E44 E51 G01 H41
    Date: 2011–12–06
  8. By: Francisco F. Vázquez; Pablo Federico
    Abstract: This paper analyzes the evolution of bank funding structures in the run up to the global financial crisis and studies the implications for financial stability, exploiting a bank-level dataset that covers about 11,000 banks in the U.S. and Europe during 2001–09. The results show that banks with weaker structural liquidity and higher leverage in the pre-crisis period were more likely to fail afterward. The likelihood of bank failure also increases with bank risk-taking. In the cross-section, the smaller domestically-oriented banks were relatively more vulnerable to liquidity risk, while the large cross-border banks were more susceptible to solvency risk due to excessive leverage. The results support the proposed Basel III regulations on structural liquidity and leverage, but suggest that emphasis should be placed on the latter, particularly for the systemically-important institutions. Macroeconomic and monetary conditions are also shown to be related with the likelihood of bank failure, providing a case for the introduction of a macro-prudential approach to banking regulation.
    Keywords: Bankruptcy , Banks , Financial crisis , Global Financial Crisis 2008-2009 , Risk management ,
    Date: 2012–01–25
  9. By: Niamh Sheridan; B. Jang
    Abstract: The paper finds that, given Australia’s conservative approach in implementing the Basel II framework, Australian banks’ headline capital ratios underestimate their capital strengths. Given their high capital quality and the progress in their funding profiles since the global financial crisis, the Australian banks are making good progress toward meeting the Basel III requirements, including the new liquidity standards. Stress tests calibrated on the Irish crisis experience show that the banks could withstand sizable shocks to their exposure to residential mortgages. However, combining residential mortgage shocks with corporate losses expected at the peak of the global financial crisis would put more pressure on Australian banks’ capital. Therefore, it would be useful to consider the merits of higher capital requirements for systemically important domestic banks.
    Keywords: Bank supervision , Banking sector , Capital ,
    Date: 2012–01–23
  10. By: Guanghui Huang; Weiqing Gu; Wenting Xing; Hongyu Li
    Abstract: Margin system for margin loans using cash and stock as collateral is considered in this paper, which is the line of defence for brokers against risk associated with margin trading. The conditional probability of negative return is used as risk measure, and a recursive algorithm is proposed to realize this measure under a Markov chain model. Optimal margin system is chosen from those systems which satisfy the constraint of the risk measure. The resulted margin system is able to adjust actively with respect to the changes of stock prices. The margin system required by the Shanghai Stock Exchange is compared with the proposed system, where 25,200 margin loans of 126 stocks listed on the SSE are investigated. It is found that the number of margin calls under the proposed margin system is significantly less than its counterpart under the required system for the same level of risk, and the average costs of the loans are similar under the two types of margin systems.
    Date: 2012–02
  11. By: Roy Zilberman
    Abstract: This paper examines the procyclical e¤ects of bank capital requirements in a simple static general equilibrium model with credit market imperfections. A "bank capital channel" is introduced by assuming that bank capital buffers increase banks' incentives to screen and monitor borrowers more carefully, thus reducing the borrowers' probability of default and allowing banks to charge a lower interest rate on loans provided for investment purposes. We also identify a "collateral channel" by assuming that higher levels of effective collateral mitigate moral hazard behaviour by firms, which raises the repayment probability and lowers the loan rate. Basel I and Basel II regulatory regimes are then de…ned in terms of the calculation of the risk weights on loans with a distinction made between the Standardized and Foundation Internal Ratings Based (IRB) approaches of Basel II. We analyze the role of the bank capital channel in the transmission of a supply shock (and associated changes in prices) when the bank capital channel dominates the collateral channel and when the collateral channel dominates the bank capital channel. Our results suggest that in the former case, the lending rate is always procyclical with respect to supply shocks while in the latter, the loan rate can be either procyclical or countercyclical. Finally, in order to compare between the different regulatory regimes, it is crucial to understand which of the abovementioned channels dominates the other.
    Date: 2012

This nep-rmg issue is ©2012 by Stan Miles. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.