nep-rmg New Economics Papers
on Risk Management
Issue of 2012‒09‒16
eleven papers chosen by
Stan Miles
Thompson Rivers University

  1. A New Heuristic Measure of Fragility and Tail Risks: Application to Stress Testing By Elena Loukoianova; Christian Schmieder; Tidiane Kinda; Nassim N. Taleb; Elie Canetti
  2. Value-at-Risk stressée chaotique d’un portefeuille bancaire By Rachida Hennani; Michel Terraza
  3. An MVAR framework to capture extreme events in macro-prudential stress tests By Paolo Guarda; Abdelaziz Rouabah; John Theal
  4. Dynamic factor models with macro, frailty and industry effects for US default counts: the credit crisis of 2008 By Siem Jan Koopman; André Lucas; Bernd Schwaab
  5. Bank Risk during the Financial Crisis: Do business models matter? By Yener Altunbas; Simone Manganelli; David Marques-Ibanez
  6. Moral hazard, dividends, and risk in banks By Enrico Onali
  7. Measuring Systemic Risk-Adjusted Liquidity (SRL) - A Model Approach By Andreas Jobst
  8. Systematic Risk, Debt Maturity, and the Term Structure of Credit Spreads By Hui Chen; Yu Xu; Jun Yang
  9. Does monetary policy affect bank risk? By Yener Altunbas; Leonardo Gambacorta; David Marques-Ibanez
  10. Executive Board Composition and Bank Risk Taking By Allen N. Berger; Thomas Kick; Klaus Schaeck
  11. Sovereign Defaults and Banking Crises By Sosa-Padilla, Cesar

  1. By: Elena Loukoianova; Christian Schmieder; Tidiane Kinda; Nassim N. Taleb; Elie Canetti
    Abstract: This paper presents a simple heuristic measure of tail risk, which is applied to individual bank stress tests and to public debt. Stress testing can be seen as a first order test of the level of potential negative outcomes in response to tail shocks. However, the results of stress testing can be misleading in the presence of model error and the uncertainty attending parameters and their estimation. The heuristic can be seen as a second order stress test to detect nonlinearities in the tails that can lead to fragility, i.e., provide additional information on the robustness of stress tests. It also shows how the measure can be used to assess the robustness of public debt forecasts, an important issue in many countries. The heuristic measure outlined here can be used in a variety of situations to ascertain an ordinal ranking of fragility to tail risks.
    Date: 2012–08–30
    URL: http://d.repec.org/n?u=RePEc:imf:imfwpa:12/216&r=rmg
  2. By: Rachida Hennani; Michel Terraza
    Abstract: Les révisions des règles prudentielles définies par Bâle 2 introduisent une exigence supplémentaire dans la détermination de fonds propres par le calcul d’une VaR stressée qui doit permettre d’intégrer le comportement violent des marchés en période de crise et par conséquent de rompre la procyclicité dans l’estimation de la VaR. La prise en compte simultanée de structures chaotiques et hétéroscédastiques conduit à une amélioration des prévisions des rentabilités, soulignée notamment par KYRTSOU et TERRAZA (2003, 2004, 2010). Cette précision par rapport au modèle GARCH(1,1) est utilisée dans cet article pour la prévision d’une VaR stressée d’un portefeuille bancaire construit selon le critère moyenne-Gini. L’évaluation des prévisions de la Value-at-Risk par les tests de backtesting indiquent une surperformance du modèle Mackey-Glass-GARCH(1,1).
    Date: 2012–09
    URL: http://d.repec.org/n?u=RePEc:lam:wpaper:12-23&r=rmg
  3. By: Paolo Guarda (Banque centrale du Luxembourg, 2, boulevard Royal, 2983 Luxembourg, Luxembourg); Abdelaziz Rouabah (Banque centrale du Luxembourg, 2, boulevard Royal, 2983 Luxembourg, Luxembourg); John Theal (Banque centrale du Luxembourg, 2, boulevard Royal, 2983 Luxembourg, Luxembourg)
    Abstract: Severe financial turbulences are driven by high impact and low probability events that are the characteristic hallmarks of systemic financial stress. These unlikely adverse events arise from the extreme tail of a probability distribution and are therefore very poorly captured by traditional econometric models that rely on the assumption of normality. In order to address the problem of extreme tail events, we adopt a mixture vector autoregressive (MVAR) model framework that allows for a multi-modal distribution of the residuals. A comparison between the respective results of a VAR and MVAR approach suggests that the mixture of distributions allows for a better assessment of the effect that adverse shocks have on counterparty credit risk, the real economy and banks’ capital requirements. Consequently, we argue that the MVAR provides a more accurate assessment of risk since it captures the fat tail events often observed in time series of default probabilities. JEL Classification: C15, E44, G01, G21
    Keywords: stress testing, MVAR, tier 1 capital ratio, counterparty risk, Luxembourg banking sector
    Date: 2012–08
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20121464&r=rmg
  4. By: Siem Jan Koopman (VU University Amsterdam, Department of Econometrics, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands and Tinbergen Institute); André Lucas (VU University Amsterdam, Department of Finance, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands, Tinbergen Institute and Duisenberg school of finance); Bernd Schwaab (European Central Bank, Kaiserstrasse 29, D-60311 Frankfurt, Germany)
    Abstract: We develop a high-dimensional and partly nonlinear non-Gaussian dynamic factor model for the decomposition of systematic default risk conditions into a set of latent components that correspond with macroeconomic/financial, default-specific (frailty), and industry-specific effects. Discrete default counts together with macroeconomic and financial variables are modeled simultaneously in this framework. In our empirical study based on defaults of U.S. firms, we find that approximately 35 percent of default rate variation is due to systematic and industry factors. Approximately one third of systematic variation is captured by macroeconomic/financial factors. The remainder is captured by frailty (about 40 percent) and industry (about 25 percent) effects. The default-specific effects are particularly relevant before and during times of financial turbulence. For example, we detect a build-up of systematic risk over the period preceding the 2008 credit crisis. JEL Classification: C33, G21
    Keywords: Financial crisis, default risk, credit portfolio models, frailty-correlated defaults, state space methods
    Date: 2012–08
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20121459&r=rmg
  5. By: Yener Altunbas (Bangor Business School); Simone Manganelli (European Central Bank); David Marques-Ibanez (European Central Bank)
    Abstract: We exploit the 2007-2009 financial crisis to analyze how risk relates to bank business models. Institutions with higher risk exposure had less capital, larger size, greater reliance on short-term market funding, and aggressive credit growth. Business models related to significantly reduced bank risk were characterized by a strong deposit base and greater income diversification. The effect of business models is non-linear: it has a different impact on riskier banks. Finally, it is difficult to establish in real time whether greater stock market capitalization involves real value creation or the accumulation of latent risk.
    Keywords: bank risk, business models, bank regulation, financial crisis, Basle III
    JEL: G21 G15 E58 G32
    Date: 2012–02
    URL: http://d.repec.org/n?u=RePEc:bng:wpaper:12003&r=rmg
  6. By: Enrico Onali (Bangor Business School)
    Abstract: The relation between dividends and bank soundness has recently drawn much attention from both academics and policy makers. However, the existing literature lacks an investigation of the relation between dividends and bank risk taking. I find a positive relation between default risk and payout ratios, although this relation is insignificant for very high levels of default risk. Capital requirements and the desire to preserve the charter can offset the positive relation between default risk and payout ratios. Dividends can increase despite very high default risk, and during the recent financial crisis many banks paid out dividends after recording a loss.
    Keywords: dividend, bank risk, moral hazard
    JEL: G21 G35
    Date: 2012–01
    URL: http://d.repec.org/n?u=RePEc:bng:wpaper:12001&r=rmg
  7. By: Andreas Jobst
    Abstract: Little progress has been made so far in addressing—in a comprehensive way—the externalities caused by impact of the interconnectedness within institutions and markets on funding and market liquidity risk within financial systems. The Systemic Risk-adjusted Liquidity (SRL) model combines option pricing with market information and balance sheet data to generate a probabilistic measure of the frequency and severity of multiple entities experiencing a joint liquidity event. It links a firm’s maturity mismatch between assets and liabilities impacting the stability of its funding with those characteristics of other firms, subject to individual changes in risk profiles and common changes in market conditions. This approach can then be used (i) to quantify an individual institution’s time-varying contribution to system-wide liquidity shortfalls and (ii) to price liquidity risk within a macroprudential framework that, if used to motivate a capital charge or insurance premia, provides incentives for liquidity managers to internalize the systemic risk of their decisions. The model can also accommodate a stress testing approach for institution-specific and/or general funding shocks that generate estimates of systemic liquidity risk (and associated charges) under adverse scenarios.
    Keywords: Banking sector , Economic models , Liquidity , Risk management , United States ,
    Date: 2012–08–24
    URL: http://d.repec.org/n?u=RePEc:imf:imfwpa:12/209&r=rmg
  8. By: Hui Chen; Yu Xu; Jun Yang
    Abstract: We build a dynamic capital structure model to study the link between firms' systematic risk exposures and their time-varying debt maturity choices, as well as its implications for the term structure of credit spreads. Compared to short-term debt, long-term debt helps reduce rollover risks, but its illiquidity raises the costs of financing. With both default risk and liquidity costs changing over the business cycle, our calibrated model implies that debt maturity is pro-cyclical, firms with high systematic risk favor longer debt maturity, and that these firms will have more stable maturity structures over the cycle. Moreover, pro-cyclical maturity variation can significantly amplify the impact of aggregate shocks on the term structure of credit spreads, especially for firms with high beta, high leverage, or a lumpy maturity structure. We provide empirical evidence for the model predictions on both debt maturity and credit spreads.
    JEL: E32 G32 G33
    Date: 2012–09
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:18367&r=rmg
  9. By: Yener Altunbas (Bangor Business School); Leonardo Gambacorta (Bank for International Settlements); David Marques-Ibanez (European Central Bank)
    Abstract: We investigate the effect of relatively loose monetary policy on bank risk through a large panel including quarterly information from listed banks operating in the European Union and the United States. We find evidence that relatively low levels of interest rates over an extended period of time contributed to an increase in bank risk. This result holds for a wide range of measures of risk, as well as macroeconomic and institutional controls including the intensity of supervision, securitization activity and bank competition. The results also hold when changes in realized bank risk due to the crisis are accounted for. The results suggest that monetary policy is not neutral from a financial stability perspective.
    Keywords: bank risk, monetary policy, credit crisis.
    JEL: E44 E52 G21
    Date: 2012–01
    URL: http://d.repec.org/n?u=RePEc:bng:wpaper:12002&r=rmg
  10. By: Allen N. Berger (University of South Carolina); Thomas Kick (Deutsche Bundesbank); Klaus Schaeck (Bangor Business School)
    Abstract: Little is known about how socioeconomic characteristics of executive teams affect corporate governance in banking. Exploiting a unique dataset, we show how age, gender, and education composition of executive teams affect risk taking of financial institutions. First, we establish that age, gender, and education jointly affect the variability of bank performance. Second, we use difference-in-difference estimations that focus exclusively on mandatory executive retirements and find that younger executive teams increase risk taking, as do board changes that result in a higher proportion of female executives. In contrast, if board changes increase the representation of executives holding Ph.D. degrees, risk taking declines.
    Keywords: Banks, executives, risk taking, age, gender, education
    JEL: G21 G34 I21 J16
    Date: 2012–02
    URL: http://d.repec.org/n?u=RePEc:bng:wpaper:12004&r=rmg
  11. By: Sosa-Padilla, Cesar
    Abstract: Episodes of sovereign default feature three key empirical regularities in connection with the banking systems of the countries where they occur: (i) sovereign defaults and banking crises tend to happen together, (ii) commercial banks have substantial holdings of government debt, and (iii) sovereign defaults result in major contractions in bank credit and production. This paper provides a rationale for these phenomena by extending the traditional sovereign default framework to incorporate bankers that lend to both the government and the corporate sector. When these bankers are highly exposed to government debt a default triggers a banking crisis which leads to a corporate credit collapse and subsequently to an output decline. When calibrated to Argentina's 2001 default episode the model produces default on equilibrium with a frequency in line with actual default frequencies, and when it happens credit experiences a sharp contraction which generates an output drop similar in magnitude to the one observed in the data. Moreover, the model also matches several moments of the cyclical dynamics of macroeconomic aggregates.
    Keywords: Sovereign Default; Banking Crisis; Credit Crunch; Optimal Fiscal Policy; Markov Perfect Equilibrium; Endogenous Cost of Default; Domestic Debt
    JEL: E62 F34
    Date: 2012
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:41074&r=rmg

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