nep-rmg New Economics Papers
on Risk Management
Issue of 2009‒12‒11
eight papers chosen by
Stan Miles
Thompson Rivers University

  1. It Pays to Violate: How Effective are the Basel Accord Penalties? By Veiga, B. da; Chan, F.; McAleer, M.
  2. Comparing univariate and multivariate models to forecast portfolio value-at-risk By Andre A. P.; Francisco J. Nogales; Esther Ruiz
  3. A new algorithm for the loss distribution function with applications to Operational Risk Management By Dominique Guegan; Bertrand Hassani
  4. Transmission of macro shocks to loan losses in a deep crisis: the case of Finland By Jokivuolle, Esa; Viren , Matti; Vähämaa, Oskari
  5. Risk-adjusted measures of value creation in financial institutions By Milne, Alistair; Onorato, Mario
  6. Bank safety under Basel II capital requirements By Vauhkonen, Jukka
  7. Credit derivatives: instruments of hedging and factors of instability. The example of “Credit Default Swaps” on French reference entities. By Nathalie Rey
  8. Risk spillover among hedge funds: The role of redemptions and fund failures. By Benjamin Klaus; Bronka Rzepkowski

  1. By: Veiga, B. da; Chan, F.; McAleer, M. (Erasmus Econometric Institute)
    Abstract: The internal models amendment to the Basel Accord allows banks to use internal models to forecast Value-at-Risk (VaR) thresholds, which are used to calculate the required capital that banks must hold in reserve as a protection against negative changes in the value of their trading portfolios. As capital reserves lead to an opportunity cost to banks, it is likely that banks could be tempted to use models that underpredict risk, and hence lead to low capital charges. In order to avoid this problem the Basel Accord introduced a backtesting procedure, whereby banks using models that led to excessive violations are penalised through higher capital charges. This paper investigates the performance of five popular volatility models that can be used to forecast VaR thresholds under a variety of distributional assumptions. The results suggest that, within the current constraints and the penalty structure of the Basel Accord, the lowest capital charges arise when using models that lead to excessive violations, thereby suggesting the current penalty structure is not severe enough to control risk management. In addition, this paper suggests an alternative penalty structure that is more effective at aligning the interests of banks and regulators.
    Keywords: Value-at-Risk (VaR);GARCH;risk management;violations;forecasting;simulations;Basel accord penalties
    Date: 2009–11–24
  2. By: Andre A. P.; Francisco J. Nogales; Esther Ruiz
    Abstract: This article addresses the problem of forecasting portfolio value-at-risk (VaR) with multivariate GARCH models vis-à-vis univariate models. Existing literature has tried to answer this question by analyzing only small portfolios and using a testing framework not appropriate for ranking VaR models. In this work we provide a more comprehensive look at the problem of portfolio VaR forecasting by using more appropriate statistical tests of comparative predictive ability. Moreover, we compare univariate vs. multivariate VaR models in the context of diversified portfolios containing a large number of assets and also provide evidence based on Monte Carlo experiments. We conclude that, if the sample size is moderately large, multivariate models outperform univariate counterparts on an out-of-sample basis.
    Keywords: Market risk, Backtesting, Conditional predictive ability, GARCH, Volatility, Capital requirements, Basel II
    Date: 2009–11
  3. By: Dominique Guegan (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris); Bertrand Hassani (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Panthéon-Sorbonne - Paris I)
    Abstract: Operational risks inside banks and insurance companies is currently an important task. The computation of a risk measure associated to these risks lies on the knowledge of the so-called Loss Distribution Function. Traditionally this distribution function is computed via the Panjer algorithm which is an iterative algorithm. In this paper, we propose an adaptation of this last algorithm in order to improve the computation of convolutions between Panjer class distributions and continuous distributions. This new approach permits to reduce drastically the variance of the estimated VAR associated to the operational risks.
    Keywords: Operational risk, Panjer algorithm, Kernel, numerical integration, convolution.
    Date: 2009–11
  4. By: Jokivuolle, Esa (Bank of Finland Research); Viren , Matti (Bank of Finland Research and University of Turku); Vähämaa, Oskari (Bank of Finland Research)
    Abstract: Building on the work of Sorge and Virolainen (2006), we revisit the data on aggregate Finnish bank loan losses from the corporate sector, which covers the ‘Big Five’ crisis in Finland in the early 1990s. Several extensions to the empirical model are considered. These extensions are then used in the simulations of the aggregate loan loss distribution. The simulation results provide some guidance as to what might be the most important dimensions in which to improve the basic model. We found that making the average LGD depend on the business cycle seems to be the most important improvement. We also compare the empirical fit of the annual expected losses over a long period. In scenario-based analyses we find that a prolonged deep recession (as well as simultaneity of various macro shocks) has a convex effect on cumulative loan losses. This emphasizes the importance of an early policy response to a looming crisis. Finally, a comparison of the loan loss distribution on the eve of the 1990s crisis with the most recent distribution demonstrates the greatly elevated risk level prior to the 1990s crisis.
    Keywords: credit risk; bank loan losses; banking crisis; macro shocks; default rates; stress testing
    JEL: C15 E37 G21 G32 G33
    Date: 2009–11–02
  5. By: Milne, Alistair (Faculty of Finance, Cass Business School, City University, London and Bank of Finland Research); Onorato, Mario (Algorithmics Inc & Faculty of Finance, Cass Business School, City University, London)
    Abstract: Measuring value creation by comparing the RAROC of an exposure (the return on risk capital) with a single institution-wide hurdle rate is inconsistent with the standard theory of financial valuation. We use asset pricing theory to determine the appropriate hurdle rate for such a RAROC performance measure. We find that this hurdle rate varies with the skewness of asset returns. Thus the RAROC hurdle rate should differ substantially between equity which has a right skew and debt which has a pronounced left skew and also between different qualities of debt exposure. We discuss implications for financial institution risk management and supervision.
    Keywords: asset pricing; banking; capital allocation; capital budgeting; capital management; corporate finance; downside risk; economic capital; performance measurement; RAROC; risk management; value creation; hurdle rate; value at risk
    JEL: G22 G31
    Date: 2009–11–02
  6. By: Vauhkonen, Jukka (Bank of Finland Research)
    Abstract: We consider the impact of mandatory information disclosure on bank safety in a spatial model of banking competition in which a bank’s probability of success depends on the quality of its risk measurement and management systems. Under Basel II capital requirements, this quality is either fully or partially disclosed to market participants by the Pillar 3 disclosures. We show that, under stringent Pillar 3 disclosure requirements, banks’ equilibrium probability of success and total welfare may be higher under a simple Basel II standardized approach than under the more sophisticated internal ratings-based (IRB) approach.
    Keywords: Basel II; capital requirements; information disclosure; market discipline; moral hazard
    JEL: D43 D82 G14 G21 G28
    Date: 2009–11–03
  7. By: Nathalie Rey (CEPN - Centre d'économie de l'Université de Paris Nord - CNRS : UMR7115 - Université Paris-Nord - Paris XIII)
    Abstract: Through a long-period analysis of the inter-temporal relations between the French markets for credit default swaps (CDS), shares and bonds between 2001 and 2008, this article shows how a financial innovation like CDS could heighten financial instability. After describing the operating principles of credit derivatives in general and CDS in particular, we construct two difference VAR models on the series: the share return rates, the variation in bond spreads and the variation in CDS spreads for thirteen French companies, with the aim of bringing to light the relations between these three markets. According to these models, there is indeed an interdependence between the French share, CDS and bond markets, with a strong influence of the share market on the other two. This interdependence increases during periods of tension on the markets (2001-2002, and since the summer of 2007).
    Keywords: credit derivatives ; credit risk ; credit default swap ; inter-temporal relations between markets ; VAR models
    Date: 2009
  8. By: Benjamin Klaus (House of Finance, Goethe University Frankfurt, Grueneburgplatz 1, D-60323 Frankfurt am Main, Germany.); Bronka Rzepkowski (Committee of European Securities Regulators (CESR), 11-13 Avenue de Friedland, F-75008 Paris, France.)
    Abstract: This paper aims at analysing the mortality patterns of hedge funds over the period January 1994 to May 2008. In particular, we investigate the extent to which a spillover of risk among hedge funds through redemptions and failures of other funds has affected the probability of fund failure. We find that risk spillover is significantly related to the failure probability of hedge funds, with the relation being more pronounced for redemptions than for failures of other funds. Hedge funds within the same investment style are adversely affected through both channels of risk spillover. In addition, we find that funds being diversified in assets and geographically have a significantly lower failure probability and are not affected by risk spillover via redemptions. JEL Classification: G11, G20, G23, G33.
    Keywords: Hedge Funds, Survival Analysis, Risk Spillover, Diversification.
    Date: 2009–11

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