New Economics Papers
on Risk Management
Issue of 2011‒09‒05
eight papers chosen by

  1. Empirical estimation of default and asset correlation of large corporates and banks in India By Bandyopadhyay, Arindam; Ganguly, Sonali
  2. Operational–risk Dependencies and the Determination of Risk Capital By Stefan Mittnik; Sandra Paterlini; Tina Yener
  3. Basel III – responses to consultative documents, vital aspects of the consultative processes and the journey culminating in the present framework (Part 1) By Ojo, Marianne
  4. Who Borrows and Who May Not Repay? By Alena Bicakova; Zuzana Prelcova; Renata Pasalicova
  5. Default risk modeling beyond the first-passage approximation: Position-dependent killing By Yuri A. Katz
  6. Living on the multi-dimensional edge: seeking hidden risks using regular variation By Bikramjit Das; Abhimanyu Mitra; Sidney Resnick
  7. Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density By Xibin Zhang; Maxwell L. King; Han Lin Shang
  8. Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data By Evzen Kocenda; Martin Vojtek

  1. By: Bandyopadhyay, Arindam; Ganguly, Sonali
    Abstract: Estimation of default and asset correlation is crucial for banks to manage and measure portfolio credit risk. This would require studying the risk profile of the banks’ entire credit portfolio and developing the appropriate methodology for the estimation of default dependence. Measurement and management of correlation risk in the credit portfolio of banks has also become an important area of concern for bank regulators worldwide. The BCBS (2006) has specifically included an asset correlation factor in the computation of credit risk capital requirement by banks adopting the Internal Ratings Based Approach. We estimate default correlation in the credit portfolio of banks. These correlation estimates will help the regulator in India to understand the linkage between bank’s portfolio default risks with the systematic factors. We also derive default and asset correlations of Indian corporate and compare it with global scenario. The work tries to find the relationship of the correlation to the default probability as specified by the Basel committee. The findings of this paper could be used further in estimating portfolio credit risk, economic capital and risk adjusted returns on economic capital for large corporate exposures of banks.
    Keywords: Default Correlation; Asset Correlation; Credit Portfolio Risk
    JEL: G32 C15 G21
    Date: 2011–08–16
  2. By: Stefan Mittnik; Sandra Paterlini; Tina Yener
    Abstract: With the advent of Basel II, risk–capital provisions need to also account for operational risk. The specification of dependence structures and the assessment of their effects on aggregate risk–capital are still open issues in modeling operational risk. In this paper, we investigate the potential consequences of adopting the restrictive Basel’s Loss Distribution Approach (LDA), as compared to strategies that take dependencies explicitly into account. Drawing on a real–world database, we fit alternative dependence structures, using parametric copulas and nonparametric tail–dependence coefficients, and discuss the implications on the estimation of aggregate risk capital. We find that risk–capital estimates may increase relative to that derived for the LDA when accounting explicitly for the presence of dependencies. This phenomenon is not only be due to the (fitted) characteristics of the data, but also arise from the specific Monte Carlo setup in simulation–based risk–capital analysis.
    Keywords: Copula, Nonparametric Tail Dependence, Basel II, Loss Distribution Approach, Value–at–Risk, Subadditivity
    JEL: C14 C15 G10 G21
    Date: 2011–08
  3. By: Ojo, Marianne
    Abstract: Parts I and II of this paper are aimed at providing a comprehensive overview of, and responses to, four very vital components of the consultative processes which have contributed to the new framework known as Basel III. The papers will approach these components in the order of the consultative processes, namely, the capital proposals, the liquidity proposals and the Proposal to ensure the loss absorbency of regulatory capital at the point of non-viability. The capital proposals comprise proposals aimed at strengthening the resilience of the banking sector, the proposal relating to international framework for liquidity risk measurement, standards and monitoring and, the countercyclical capital buffer proposal. Whilst the capital proposals have been welcomed, there has been growing realization since the aftermath of the recent Financial Crisis that banks which have been complying with capital adequacy requirements could still face severe liquidity problems. As well as highlighting the importance of introducing counter cyclical capital buffers, the response to the countercyclical proposal draws attention to the need for greater focus on more forward looking provisions, as well as provisions which are aimed at addressing losses and unforeseen problems attributed to “maturity transformation of short-term deposits into long term loans.” The Committee's acknowledgement of negative incentives arising from the use of external ratings to determine regulatory capital requirements and proposals to mitigate these incentives is well - founded – however, regulators will also be able to manage, with greater ability, systemic risks to the financial system during such periods when firms which are highly leveraged become reluctant to lend where more market participants such as credit rating agencies, could be engaged in the supervisory process.
    Keywords: counter cyclical buffers; credit ratings; credit rating agencies; liquidity risks; pro cyclicality; loan loss provisions; financial crises; bank; regulation; leverage; capital; insolvency; financial crises; moral hazard; Basel III
    JEL: K2 E32 D8
    Date: 2011–08
  4. By: Alena Bicakova; Zuzana Prelcova; Renata Pasalicova
    Abstract: We use Household Budget Survey data to analyze the evolution of the household credit market in the Czech Republic over the period 2000–2008. We next merge our data with the Statistics on Income and Living Conditions in 2005–2008, in order to test the validity of the standard debt burden measure as a predictor of default. We propose an alternative indicator – the adjusted debt burden (ADB), defined as the ratio of loan repayments to discretionary income, constructed as net income minus the living minimum, which turns out to be a superior predictor of default risk. Limited by the data, we use a fairly broad concept of default, namely, the inability to make loan repayments on time. Based on the distribution of default risk across the levels of the adjusted debt burden, we suggest that a 30% ADB threshold should be used as the definition of overindebtedness, with an average default risk of 17%. Finally, we show that overindebtedness and local economic shocks are closely related, suggesting that default risk should be always considered in the context of regional economic conditions.
    Keywords: household credit; debt burden; repayment; regional default risk
    JEL: D12 D14 G21 R29
    Date: 2011–07
  5. By: Yuri A. Katz
    Abstract: Diffusion in a linear potential in the presence of position-dependent killing is used to mimic a default process. Different assumptions regarding transport coefficients, initial conditions, and elasticity of the killing measure lead to diverse models of bankruptcy. One "stylized fact" is fundamental for our consideration: empirically default is a rather rare event, especially in the investment grade categories of credit ratings. Hence, the action of killing may be considered as a small parameter. In a number of special cases we derive closed-form expressions for the entire term structure of the cumulative probability of default, its hazard rate and intensity. Comparison with historical data on global corporate defaults confirms applicability of the model-independent perturbation method for companies in the investment grade categories of credit ratings and allows for
    Date: 2011–08
  6. By: Bikramjit Das; Abhimanyu Mitra; Sidney Resnick
    Abstract: Multivariate regular variation plays a role assessing tail risk in diverse applications such as finance, telecommunications, insurance and environmental science. The classical theory, being based on an asymptotic model, sometimes leads to inaccurate and useless estimates of probabilities of joint tail regions. This problem can be partly ameliorated by using hidden regular variation [Resnick, 2002, Mitra and Resnick, 2010]. We offer a more flexible definition of hidden regular variation that provides improved risk estimates for a larger class of risk tail regions.
    Date: 2011–08
  7. By: Xibin Zhang; Maxwell L. King; Han Lin Shang
    Abstract: We approximate the error density of a nonparametric regression model by a mixture of Gaussian densities with means being the individual error realizations and variance a constant parameter. We investigate the construction of a likelihood and posterior for bandwidth parameters under this Gaussian-component mixture density of errors in a nonparametric regression. A Markov chain Monte Carlo algorithm is presented to sample bandwidths for the kernel estimators of the regression function and error density. A simulation study shows that the proposed Gaussian-component mixture density of errors is clearly favored against wrong assumptions of the error density. We apply our sampling algorithm to a nonparametric regression model of the All Ordinaries daily return on the overnight FTSE and S&P 500 returns, where the error density is approximated by the proposed mixture density. With the estimated bandwidths, we estimate the density of the one-step-ahead point forecast of the All Ordinaries return, and therefore, a distribution-free value-at-risk is obtained. The proposed Gaussian component mixture density of regression errors is also validated through the nonparametric regression involved in the state-price density estimation proposed by Aït-Sahalia and Lo (1998).
    Keywords: Bayes factors, Gaussian-component mixture density, Markov chain Monte Carlo, state-price density, value-at-risk.
    JEL: C11 C14 C15 G15
    Date: 2011–08–22
  8. By: Evzen Kocenda; Martin Vojtek
    Abstract: Credit to the private sector has risen rapidly in European emerging markets but its risk evaluation has been largely neglected. Using retail-loan banking data from the Czech Republic we construct two credit risk models based on logistic regression and Classification and Regression Trees. Both methods are comparably efficient and detect similar financial and socio-economic variables as the key determinants of default behavior. We also construct a model without the most important financial variable (amount of resources) that performs very well. This way we confirm significance of socio-demographic variables and link our results with specific issues characteristic to new EU members.
    Keywords: credit scoring, discrimination analysis, banking sector, pattern recognition, retail loans, CART, European Union
    JEL: B41 C14 D81 G21 P43
    Date: 2011–04–01

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.