scholarly journals Asset correlation, portfolio diversification and regulatory capital in the Basel Capital Accord

2011 ◽  
Vol 1 (3) ◽  
pp. 31-39 ◽  
Author(s):  
Sylvia Gottschalk
Keyword(s):  
Basel Ii ◽  
Capital Adequacy ◽  
Probability Of Default ◽  
Regulatory Capital ◽  
Kmv Model ◽  
High Quantiles ◽  
Portfolio Loss Distribution ◽  
Credit Portfolio ◽  
Portfolio Loss ◽  
Asset Correlation

In this paper, we analyze the properties of the KMV model of credit portfolio loss. This theoretical model constitutes the cornerstone of Basel II’s Internal Ratings Based(IRB) approach to regulatory capital. Our results show that this model tends to overestimate the probability of portfolio loss when the probability of default of a single firm and the firms’ asset correlations are low. On the contrary, probabilities of portfolio loss are underestimated when the probability of default of a single firm and asset correlations are high. Moreover, the relationship between asset correlation and probability of loan portfolio loss is only consistent at very high quantiles of the portfolio loss distribution. These are precisely those adopted by the Basel II Capital Accord for the calculations of capital adequacy provisions. So, although the counterintuitive properties of the KMV model do not extend to Basel II, they do restrict its generality as a model of credit portfolio loss.

scholarly journals REGULATORY CAPITAL MODELING FOR CREDIT RISK

2015 ◽  
Vol 18 (05) ◽  
pp. 1550034 ◽  
Author(s):  
MAREK RUTKOWSKI ◽  
SILVIO TARCA
Keyword(s):  
Credit Risk ◽  
Banking Sector ◽  
General Setting ◽  
Capital Adequacy ◽  
Dependence Structure ◽  
Regulatory Capital ◽  
Loss Distribution ◽  
Portfolio Loss Distribution ◽  
Portfolio Loss ◽  
Irb Approach

The Basel II internal ratings-based (IRB) approach to capital adequacy for credit risk plays an important role in protecting the banking sector against insolvency. We outline the mathematical foundations of regulatory capital for credit risk, and extend the model specification of the IRB approach to a more general setting than the usual Gaussian case. It rests on the proposition that quantiles of the distribution of conditional expectation of portfolio percentage loss may be substituted for quantiles of the portfolio loss distribution. We present a more compact proof of this proposition under weaker assumptions. Then, constructing a portfolio that is representative of credit exposures of the Australian banking sector, we measure the rate of convergence, in terms of number of obligors, of empirical loss distributions to the asymptotic (infinitely fine-grained) portfolio loss distribution. Moreover, we evaluate the sensitivity of credit risk capital to dependence structure as modeled by asset correlations and elliptical copulas. Access to internal bank data collected by the prudential regulator distinguishes our research from other empirical studies on the IRB approach.

Basel regulatory capital formula revised

2021 ◽  
pp. 2142006
Author(s):  
Yimin Yang ◽  
Min Wu
Keyword(s):  
Additional Data ◽  
Capital Adequacy ◽  
Capital Requirement ◽  
Regulatory Capital ◽  
New Approach ◽  
Internal Rating ◽  
Loss Experience ◽  
As Stress ◽  
Risk Parameters ◽  
Asset Correlation

Credit capital requirement is a key component of Basel implementation to assess a bank’s capital adequacy. Under the Internal Rating-Based approach, some risk parameters, including Asset Correlation, are implicit assumptions that cannot be observed directly. While some heuristic formulae of Asset Correlation for different business segments are provided by Basel, they may not be fully consistent with each bank’s loss experience and thus may cause systematic underestimation of banks’ capital requirement. To address this issue, we derive an equivalent capital formula in such way that the unobservable Asset Correlation is replaced by an observable and well-understood parameter called Default Volatility, which can be calibrated based on banks’ historical loss experience. This new approach simplifies parameter estimation process without requiring additional data, as well as making risk analysis such as stress testing more credible.

The Value-at-Risk Methodology of Basel II and Basel III

2014 ◽  
pp. 100-114 ◽  
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Basel Ii ◽  
Risk Measurement ◽  
Capital Adequacy ◽  
Basel Iii ◽  
Regulatory Capital ◽  
Advantages And Disadvantages ◽  
Risk Methodology

This chapter examines the advantages and disadvantages of the risk estimate approach—Value-at-Risk (VaR) which has been extensively embraced by regulators and practitioners in financial markets under the Basel II & III framework as the basis of risk measurement, both for the purpose of ensuring regulatory capital adequacy, and risk management and strategic planning at industry level.

T-Vasicek Credit Portfolio Loss Distribution

2018 ◽  
Keyword(s):  
Default Probability ◽  
Additional Parameter ◽  
Fat Tails ◽  
Probability Estimate ◽  
Loss Distribution ◽  
Uncertainty Factor ◽  
Portfolio Loss Distribution ◽  
Credit Portfolio ◽  
Portfolio Loss ◽  
T Distribution

We derive and discuss a new analytical credit loss distribution. This new model, T-Vasicek, is a variant of the well-known and highly useful Vasicek distribution. We inject a t-distribution extension into Vasicek that preserves the analytical convenience of Vasicek while providing a richer credit loss framework with fat tails and an additional user-specified parameter. This additional parameter is directly tied to the t-distribution and represents the uncertainty in the default probability estimate. The classical Vasicek limit, then, is the case in which the analyst knows the pool default probability with certainty. We show how one may impose desired correlation among all debt instruments in the t-distribution framework. We derive closed-form, numerical, and analytical forms for T-Vasicek and check the numerical results with Monte Carlo simulation. We also determine suitable maximum likelihood estimators for the T-Vasicek parameters of default probability (PD), correlation (ρ), and PD-uncertainty factor (ν).

scholarly journals A Critical Review Of The Basel Margin Of Conservatism Requirement In A Retail Credit Context

2017 ◽  
Vol 16 (4) ◽  
pp. 257-274 ◽  
Author(s):  
Riaan De Jongh ◽  
Tanja Verster ◽  
Elzabe Reynolds ◽  
Morne Joubert ◽  
Helgard Raubenheimer
Keyword(s):  
Risk Factor ◽  
Financial Institutions ◽  
Basel Ii ◽  
Probability Of Default ◽  
Regulatory Capital ◽  
Loss Given Default ◽  
Asymptotic Risk ◽  
Retail Credit ◽  
Complex Models ◽  
Irb Approach

The Basel II accord (2006) includes guidelines to financial institutions for the estimation of regulatory capital (RC) for retail credit risk. Under the advanced Internal Ratings Based (IRB) approach, the formula suggested for calculating RC is based on the Asymptotic Risk Factor (ASRF) model, which assumes that a borrower will default if the value of its assets were to fall below the value of its debts. The primary inputs needed in this formula are estimates of probability of default (PD), loss given default (LGD) and exposure at default (EAD). Banks for whom usage of the advanced IRB approach have been approved usually obtain these estimates from complex models developed in-house. Basel II recognises that estimates of PDs, LGDs, and EADs are likely to involve unpredictable errors, and then states that, in order to avoid over-optimism, a bank must add to its estimates a margin of conservatism (MoC) that is related to the likely range of errors. Basel II also requires several other measures of conservatism that have to be incorporated. These conservatism requirements lead to confusion among banks and regulators as to what exactly is required as far as a margin of conservatism is concerned. In this paper, we discuss the ASRF model and its shortcomings, as well as Basel II conservatism requirements. We study the MoC concept and review possible approaches for its implementation. Our overall objective is to highlight certain issues regarding shortcomings inherent to a pervasively used model to bank practitioners and regulators and to potentially offer a less confusing interpretation of the MoC concept.

Islamic Banking Regulations in Light of Basel II

2010 ◽  
Vol 27 (1) ◽  
pp. 74-101 ◽  
Author(s):  
M. Kabir Hassan ◽  
Muhammad Abdul Mannan Chowdhury
Keyword(s):  
Financial Institutions ◽  
Banking Regulation ◽  
Capital Requirements ◽  
Basel Ii ◽  
Capital Adequacy ◽  
Regulatory Agencies ◽  
Islamic Banking ◽  
Islamic Banks ◽  
Minimum Capital ◽  
Regulatory Standards

This paper seeks to determine whether the existing regulatory standards and supervisory framework are adequate to ensure the viability, strength, and continued expansion of Islamic financial institutions. The reemergence of Islamic banking and the attention given to it by regulators around the globe as to the implications of a recently issued Basel II banking regulation makes this article timely. The Basel II framework, which is based on minimum capital requirements, a supervisory review process, and the effective use of market discipline, aligns capital adequacy with banking risks and provides an incentive for financial institutions to enhance risk management and their system of internal controls. Like conventional banks, Islamic banks operate under different regulatory regimes. The still diverse views held by the regulatory agencies of different countries on Islamic banking and finance operations make it harder to assess the overall performance of international Islamic banks. In light of the increased financial innovation and diversity of instruments offered in Islamic finance, the need to improve the transparency of bank operations is particularly relevant for Islamic banks. While product diversity is important in maintaining their competitiveness, it also requires increased transparency and disclosure to improve the understanding of markets and regulatory agencies. The governance of Islamic banks is made even more complex by the need for these banks to meet a set of ethical and financial standards defined by the Shari`ah and the nature of the financial contracts banks use to mobilize deposits. Effective transparency in this area will greatly enhance their credibility and reinforce their depositors and investors’ level of confidence.

scholarly journals Modeling Recoveries of US Leading Banks Based on Publicly Disclosed Data

Mathematics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 188
Author(s):  
Pawel Siarka
Keyword(s):  
Recovery Rate ◽  
Credit Card ◽  
Factor Model ◽  
Critical Element ◽  
Federal Reserve Bank ◽  
Rate Analysis ◽  
Industry Standards ◽  
Risk Management Process ◽  
Credit Portfolio ◽  
Asset Correlation

The credit risk management process is a critical element that allows financial institutions to withstand economic downturns. Unlike the methods regarding the probability of default, which have been deeply addressed after the financial crisis in 2008, recovery rate models still need further development. As there are no industry standards, leading banks are modeling recovery rates using internal models developed with different assumptions. Therefore, the outcomes are often incomparable and may lead to confusion. The author presents the concept of a unified recovery rate analysis for US banks. He uses data derived from FR Y-9C reports disclosed by the Federal Reserve Bank of Chicago. Based on the historical recoveries and credit portfolio book values, the author examines the distribution function of recoveries. The research refers to a credit card portfolio and covers nine leading US banks. The author leveraged Vasicek’s one-factor model with the asset correlation parameter and implemented it for recovery rate analysis. This experiment revealed that the estimated latent correlation ranges from 0.2% to 1.5% within the examined portfolios. They are large enough to impact the recovery rate volatility and cannot be treated as negligible. It was shown that the presented method could be applied under US Comprehensive Capital Analysis and Review exercise.

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