|
on Risk Management |
Issue of 2013‒03‒16
eleven papers chosen by |
By: | Nataliya Klimenko (AMSE - Aix-Marseille School of Economics - Aix-Marseille Univ. - Centre national de la recherche scientifique (CNRS) - Ecole des Hautes Etudes en Sciences Sociales (EHESS) - Ecole Centrale Marseille (ECM)) |
Abstract: | The experience of the 2007-09 financial crisis has showed that the bank capital regulation in place was inadequate to deal with "manufacturing" tail risk in the financial sector. This paper proposes an incentive-based design of bank capital regulation aimed at efficiently dealing with tail risk engendered by bank top managers. It has two specific features: (i) first, it incorporates information on the optimal incentive contract between bank shareholders and bank managers, thereby dealing with the internal agency problem; (ii) second, it relies on the mechanism of mandatory recapitalization to ensure this contract is adopted by bank shareholders. |
Keywords: | capital requirements; tail risk; recapitalization; incentive compensation; moral hazard |
Date: | 2013–02 |
URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:halshs-00796490&r=rmg |
By: | Gareth W. Peters; Rodrigo S. Targino; Pavel V. Shevchenko |
Abstract: | We set the context for capital approximation within the framework of the Basel II / III regulatory capital accords. This is particularly topical as the Basel III accord is shortly due to take effect. In this regard, we provide a summary of the role of capital adequacy in the new accord, highlighting along the way the significant loss events that have been attributed to the Operational Risk class that was introduced in the Basel II and III accords. Then we provide a semi-tutorial discussion on the modelling aspects of capital estimation under a Loss Distributional Approach (LDA). Our emphasis is to focus on the important loss processes with regard to those that contribute most to capital, the so called high consequence, low frequency loss processes. This leads us to provide a tutorial overview of heavy tailed loss process modelling in OpRisk under Basel III, with discussion on the implications of such tail assumptions for the severity model in an LDA structure. This provides practitioners with a clear understanding of the features that they may wish to consider when developing OpRisk severity models in practice. From this discussion on heavy tailed severity models, we then develop an understanding of the impact such models have on the right tail asymptotics of the compound loss process and we provide detailed presentation of what are known as first and second order tail approximations for the resulting heavy tailed loss process. From this we develop a tutorial on three key families of risk measures and their equivalent second order asymptotic approximations: Value-at-Risk (Basel III industry standard); Expected Shortfall (ES) and the Spectral Risk Measure. These then form the capital approximations. |
Date: | 2013–03 |
URL: | http://d.repec.org/n?u=RePEc:arx:papers:1303.2910&r=rmg |
By: | Ruston, Agustina; García Fronti, Javier |
Abstract: | The Greek sovereign debt crisis exposed the weaknesses of the financial system in relation to the control and risk management in the European context. Moreover, as part of the Greek sovereign debt is concentrated in European banks, a default affect its solvency and liquidity. The new regulation introduces by the Basel Committee, known as Basel III, raises new rules aiming to improve risk management in banks. The European Community has conducted stress tests on some European banks, whose results were presented in July 2011. These showed a strong banking system, with strong capital positions. However, current evidence, although preliminary, show otherwise. |
Keywords: | stress test basel III greek crisis |
JEL: | F3 G2 |
Date: | 2013 |
URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:44907&r=rmg |
By: | Raffaella Calabrese (Department of Quantitative Methods for Economics and Business Sciences, University of Milano-Bicocca); Paolo Giudici (Department of Economics and Management, University of Pavia) |
Abstract: | This paper considers the joint role of macroeconomic and bankspecific factors in explaining the occurrence of bank failures. As bank failures are, fortunately, rare, we apply a regression model, based on extreme value theory, that turns out to be more effective than classical logistic regression models. The application of this model to the occurrence of bank defaults in Italy shows that, while capital ratios considered by the regulatory requirements of Basel III are extremely significant to explain proper failures, macroeconomic conditions are relevant only when failures are defined also in terms of merger and acquisition. We also apply the joint beta regression model, in order to estimate the factors that most contribute to the bank capital ratios monitored by Basel III. Our results show that the Tier 1 capital ratio and the Total capital ratio are affected by similar variables, at the micro and macroeconomic level. An important outcome of this part of the analysis is that capital ratio variables can be taken as reasonable proxies of distress, at least as far as the effect sign of the determinants of failure risk is being considered. |
Date: | 2013–03 |
URL: | http://d.repec.org/n?u=RePEc:pav:demwpp:035&r=rmg |
By: | Bertrand K. Hassani (Centre d'Economie de la Sorbonne et Santander UK); Alexis Renaudin (Aon Global Risk Consulting) |
Abstract: | According to the last proposals of the Basel Committee on Banking Supervision, banks under the Advanced Measurement Approach (AMA) must use four different sources of information to assess their Operational Risk capital requirement. The fourth including "business environment and internal control factors", i.e. qualitative criteria, the three main quantitative sources available to banks to build the Loss Distribution are Internal Loss Data, External Loss Data, and Scenario Analysis. This paper proposes an innovative methodology to bring together these three different sources in the Loss Distribution Approach (LDA) framework through a Bayesian strategy. The integration of the different elements is performed in two different steps to ensure an internal data driven model is obtained. In a first step, scenarios are used to inform the prior distributions and external data informs the likelihood component of the posterior function. In the second step, the initial posterior function is used as the prior distribution and the internal loss data inform the likelihood component of the second posterior. This latter posterior function enables the estimation of the parameters of the severity distribution selected to represent the Operational Risk event types. |
Keywords: | Operational risk, loss distribution approach, Bayesian inference, Marchov chain Monte Carlo, extreme value theory, non-parametric statistics, risk measures. |
JEL: | C02 C11 C13 C63 G32 |
Date: | 2013–02 |
URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:13009&r=rmg |
By: | Bengtsson, E. |
Abstract: | Fund managers play an important role in increasing efficiency and stability in financial markets. But research also indicates that fund management in certain circumstances may contribute to the buildup of systemic risk and severity of financial crises. The global financial crisis provided a number of new experiences on the contribution of fund managers to systemic risk. In this article, we focus on these lessons from the crisis. We distinguish between three sources of systemic risk in the financial system that may arise from fund management: insufficient credit risk transfer to fund managers; runs on funds that cause sudden reductions in funding to banks and other financial entities; and contagion through business ties between fund managers and their sponsors. Our discussion relates to the current intense debate on the role the so-called shadow banking system played in the global financial crisis. Several regulatory initiatives have been launched or suggested to reduce the systemic risk arising from non-bank financial entities, and we briefly discuss the likely impact of these on the sources of systemic risk outlined in the article. |
Keywords: | Systemic risk; shadow banking; fund management; credit risk transfer; liquidity risk; financial crisis |
Date: | 2013 |
URL: | http://d.repec.org/n?u=RePEc:dip:dpaper:2013-06&r=rmg |
By: | Irem Talasli |
Abstract: | This study utilizes Turkish financial institutions stock market returns and balance sheet data through 2000–2001 banking sector crisis and 2007–2009 global financial crisis in order to investigate applicability of systemic expected shortfall (SES) measure introduced by Acharya et al. (2010). SES is assumed to measure contribution of each institution to systems total risk in case of a financial distress. Our regression results indicate that SES model, which includes both marginal expected shortfall and leverage ratios of institutions calculated prior to the crisis period, explains financial sector losses observed crisis periods better than generally accepted risk measures like expected shortfall, stock market beta and annualized stock return volatility estimated with the same data set. Empirical results have proved that SES is a powerful alternative in tracking potential riskiness of the financial stocks. |
Keywords: | Systemic expected shortfall, marginal expected shortfall, systemic risk |
JEL: | C21 C58 G01 |
Date: | 2013 |
URL: | http://d.repec.org/n?u=RePEc:tcb:wpaper:1311&r=rmg |
By: | Duncan Alford (Asian Development Bank Institute (ADBI)) |
Abstract: | This paper focuses on the relevance to emerging economies of three major financial reforms following the global financial crisis of 2007–2009 : (1) the improved capital requirements intended to reduce the risk of bank failure (“Basel IIIâ€), (2) the improved recovery and resolution regimes for global banks, and (3) the development of supervisory colleges of cross-border financial institutions to improve supervisory cooperation and convergence. The paper also addresses the implications of these regulatory reforms for Asian emerging markets. |
Keywords: | Asian Emerging Markets, Financial Reforms, G20, Basel III, Financial supervision |
JEL: | G2 G28 O16 |
Date: | 2013–01 |
URL: | http://d.repec.org/n?u=RePEc:eab:govern:23387&r=rmg |
By: | Grzegorz Hałaj (European Central Bank); Christoffer Kok Sørensen (European Central Bank) |
Abstract: | This paper presents a new approach to randomly generate interbank networks while overcoming shortcomings in the availability of bank-by-bank bilateral exposures. Our model can be used to simulate and assess interbankcontagion effects on banking sector soundness and resilience. We find a strongly non-linear pattern across the distribution of simulated networks, whereby only for a small percentage of networks the impact of interbank contagion will substantially reduce average solvency of the system. In the vast majority of the simulated networks the system-wide contagion effects are largely negligible. The approach furthermore enables to form a view aboutthe most systemic banks in the system in terms of the banks whose failure would have the most detrimental contagion effects on the system as a whole. Finally, as the simulation of the network structures is computationally verycostly, we also propose a simplified measure - a so-called Systemic Probability Index (SPI) - that also captures the likelihood of contagion from the failure of a given bank to honour its interbank payment obligations but at the same time is less costly to compute. We find that the SPI is broadly consistent with the results from the simulated network structures. |
Keywords: | Network theory; interbank contagion; systemic risk; banking; stress-testing |
Date: | 2013–01 |
URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20131506&r=rmg |
By: | Mohamed El Hedi Arouri (LEO - Laboratoire d'économie d'Orleans - CNRS : UMR6221 - Université d'Orléans); Amine Lahiani (LEO - Laboratoire d'économie d'Orleans - CNRS : UMR6221 - Université d'Orléans); Duc Khuong Nguyen (CERAG - Centre d'études et de recherches appliquées à la gestion - CNRS : UMR5820 - Université Pierre Mendès-France - Grenoble II) |
Abstract: | In this paper we make use of several multivariate GARCH models (CCC-, DCC-, BEKK-, diagonal BEKK-, and VAR-GARCH) to investigate both return and volatility spillovers between world gold prices and stock market in China over the period from March 22, 2004 through March 31, 2011. We also analyze the optimal weights and hedge ratios for gold-stock portfolio holdings and show how empirical results can be used to build effective diversification and hedging strategy. Our results show evidence of significant return and volatility cross effects between gold prices and stock prices in China. In particular, past gold returns play a crucial role in explaining the dynamics of conditional return and volatility of Chinese stock market and should thus be accounted for when forecasting future stock returns. Our portfolio analysis suggests that adding gold to a portfolio of Chinese stocks improves its risk-adjusted return and that gold risk exposures can be effectively hedged in portfolios of stocks over time. Finally, we show that the VAR-GARCH model performs better than the other multivariate GARCH models. |
Date: | 2013–03–07 |
URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-00798038&r=rmg |
By: | Vincent Brousseau (European Central Bank); Alain Durré (European Central Bank; IESEG - School of Management; Lille Economie & Management) |
Abstract: | In this paper we propose a new methodology to estimate the volatility of interest rates in the euro area money market. In particular, our approach aims at avoiding the limitations of currently available measures, i.e. the dependency on arbitrary choices in terms of maturity and frequencies and/or of factors other than pure interest rates, e.g. credit risk or liquidity risk. The measure is constructed as the implied instantaneous volatility of a consol bond that would be priced on the EONIA swap curve over the sample period from 4 January 1999 to 20 November 2012. We show that this measure tracks well the historical volatility, in the sense that dividing the consol excess returns by this volatility removes nearly entirely excess of kurtosis and volatility clustering, bringing them close to an ordinary Gaussian white noise. JEL Classification: E43, E58, C22, C32 |
Keywords: | consol rate, historical volatility, overnight money market, interbank o¤ered interest rates |
Date: | 2013–01 |
URL: | http://d.repec.org/n?u=RePEc:ecb:ecbwps:20131505&r=rmg |