中国商业银行声誉风险经济资本的度量

本文基于中国某大型商业银行2003~2012年的声誉风险损失数据,在对样本数据进行概率分布函数拟合的基础上,运用蒙特卡洛(Monte Carlo)模拟法计算该商业银行总的声誉风险经济资本需求。研究发现,该商业银行声誉风险发生频数符合Logistic分布,而声誉风险损失余额符合对数正态分布。文章认为,在使用蒙特卡洛模拟法计算商业银行声誉风险的经济资本需求时,很难排除分布函数选择上的主观性对结果的影响。因此,在完善中国商业银行声誉风险经济资本度量模型与方法的同时,应加强对声誉风险事件分级分类管理、建立起中国商业银行声誉风险损失数据库。     

组合风险管理视角下信贷结构的优化

本文通过构建组合管理模型,对信贷资产组合结构进行实证研究,计算各行业的组合损失分布和经济资本。研究表明,信贷资产组合损失呈现对数状态分布;各行业贷款的经济资本结构和贷款规模结构、收益结构之间存在巨大的差异。商业银行应该基于贷款的经济资本、贷款规模和收益等要素来制定信贷结构优化调整策略;商业银行在开展信贷结构调整的过程中,不仅要考虑各个行业的回报率和资产规模,还应该从风险调整收益角度进行"投入—产出"的对比分析,应按照风险收益相匹配的原则,增加风险调整收益较高的"高效能"领域信贷资产的规模水平。     

集成风险模型与经济资本计量研究

本文分析了商业银行资产组合含有信用风险、市场风险、操作风险中的一类风险损失分布模型以及三种不同类型风险损失的相关性,得到了信用风险损失、市场风险损失以及操作风险损失的对数组成的向量服从三维正态分布的结论。在此基础上,研究了包含信用风险、市场风险、操作风险的资产组合的经济资本计量方法。利用这一方法能够节约商业银行资本资源,提高资本利用效率。     

国外两种商业银行经济资本计量方法的比较分析

国外银行使用不同方法对经济资本进行计量,有的借助资本乘数计量经济资本,有的使用贷款组合的损失分布计量经济资本。本文对瑞士波士顿银行和美国银行采用的经济资本计量方法进行比较,分析这两种方法在我国商业银行运用的局限性以及改进的思路。     

数字经济

2008年,在国际金融危机的严峻形势下,我国中小商业银行各项业务实现平稳较快发展。截至2008年年末．中小商业银行资本充足率全部达标,其中：股份制商业银行平均资本充足率达到10．5％,城市商业银行平均资本充足率达到13％。贷款损失拨备覆盖率大幅提高,2008年年末．股份制商业银行拨备覆盖率达到了169％,城市商业银行贷款损失拨备覆盖率也达到114％。不良贷款率降至历史新低．2008年年末．中小商业银行不良贷款率降至17％,其中：股份制商业银行不良贷款率降至135％．城市商业银行不良贷款率降至23％,均为历史最好水平。     

中国商业银行通过贷款损失准备计提进行盈余平滑吗？

本文研究我国不同类型的商业银行计提贷款损失准备的影响因素及其盈余平滑行为。我们发现当期贷款损失准备的计提与下一期不良贷款的变动存在显著的正相关性,同时,贷款损失准备被用来作为盈余平滑的工具,城市商业银行和非上市银行的平滑盈余现象更为明显。对于非上市的城市商业银行,发行债券或发行总量越多,使用贷款损失准备进行盈余平滑的程度越大,而新会计准则的实施对商业银行使用贷款损失准备进行盈余平滑的行为没有显著影响。     

预期信用损失模型对银行资本计提的结构性影响研究——基于50家上市商业银行的实证分析

预期信用损失模型是一项新的贷款损失准备计提方法,对其经济后果的评估非常重要.关于预期信用损失模型的实施对我国商业银行资本计提的具体影响,目前还缺乏深入系统的研究.本文结合我国50家上市商业银行的公开数据,从监管资本、会计损益和资本计提前瞻性的角度分析了预期信用损失模型对我国商业银行资本计提的影响.研究结果表明:总体影响上,商业银行的贷款损失准备计提金额显著增加,利润波动增强,对资本充足率带来一定冲击;从不同特征商业银行看,小型商业银行、使用权重法商业银行、城市商业银行和H股上市商业银行受到的影响更为严重;从资本计提的前瞻性看,贷款损失准备的前瞻性得到加强,顺周期性效应得到一定程度缓解,但并不能完全消除.     

数字经济

2008年中小商业银行业务发展情况2008年,在国际金融危机的严峻形势下,我国中小商业银行各项业务实现平稳较快发展。截至2008年年末,中小商业银行资本充足率全部达标,其中:股份制商业银行平均资本充足率达到10.5%,城市商业银行平均资本充足率达到13%。贷款损失拨备覆盖率大幅提高,2008年年末,股份制商业银行拨备覆盖率达到了169%,城市商业银行贷款损失拨备覆盖率也达到114%。不良贷款率降至历史新低,2008年年末,中小商业银行不良贷款率降至1.7%,其中:股份制商业银行不良贷款率降至1.35%,城市商业银行不良贷款率降至2.3%,均为历史最好水平。数据来源:中国银行业监督管理委员会)     

商业银行贷款集中度对不良贷款率的影响

采用行业集中度、地区集中度和客户集中度三个变量来测算国有商业银行、股份制商业银行和城市商业银行三类银行的贷款集中度,并通过建立回归模型对比分析这三类银行的贷款集中对不良贷款率的影响。研究结果表明,商业银行的贷款集中与不良贷款率正相关,各类商业银行的贷款集中程度与不良贷款的相关程度不同,其中贷款集中度对国有商业银行资产质量的影响要大于股份制商业银行,降低贷款集中度是遏制不良贷款的有效方法。     

我国商业银行不良贷款的博弈分析

不良贷款是指借款人未能按原定的贷款协议按时偿还商业银行的贷款本息,或者已有迹象表明借款人不可能按原定的贷款协议按时偿还商业银行的贷款本息而形成的贷款。我国自2002年全面实行贷款五级分类制度,该制度按照贷款的风险程度,将银行信贷资产分为五类:正常、关注、次级、可疑和损失。不良贷款主要指次级、可疑和损失类贷款。据中国银行业监督管理委员会提供的数据,到2006年6月末,我国商业     

Economic capital for nonperforming loans

A portfolio of nonperforming loans requires economic capital. We present two models for forecasting the portfolio loss and its probability distribution. In the first model, the loss for each nonperforming loan entails a change in provision over the risk horizon. The risk determinants are the single-name concentration, measured by the Herfindahl–Hirschmann index, as well as a systematic factor and the idiosyncratic risk. Our second model allows for interportfolio diversification with a portfolio of performing loans because banks typically own both performing and nonperforming loans. In this model, the nonperforming loan is identified with its systematic risk. Both models allow for closed-form expressions of economic capital and for the capital charge of the single loan. We calibrate the macroeconomic model parameters statistically with a loss panel; the microeconomic parameters depend on the portfolio. The portfolio risk for nonperforming loans mainly depends on the volatility of the systematic economic factor. The dependence becomes more pronounced when interportfolio diversification is taken into account. The magnitude of interportfolio diversification is also marked. Finally, we calculate regulatory capital charges according to Basel II for past-due loans. The regulatory charges are on average smaller than our economic charges and, additionally, take the volatility of economic activity into account only implicitly.     

Risk-based capital requirements for mortgage loans

We contribute to the debate over the reform of the Basel Accord by developing risk-based capital requirements for mortgage loans held in portfolio by financial intermediaries. Our approach employs simulation of both economic variables that affect default incidence and conditional loss probability distributions. Results indicate that appropriate capital charges for credit risk vary substantially with loan characteristics and portfolio geographic diversification. Hence, rules that offer little risk differentiation, including the current Basel I regime and “standardized” approach proposed in Basel II result in significant divergence between regulatory and economic capital. These results highlight the incentive problems inherent in simplified methods of capital regulation.     

Extending the Basel II approach to estimate capital requirements for equity investments

Under the Basel II banking regulatory capital regime the capital requirements for credit exposures are calculated using the Asymptotic Single Risk Factor (ASRF) approach. The capital requirement is taken to be the contribution of an exposure to the unexpected loss on the bank’s diversified portfolio. Here we extend this approach to calculate capital requirements for equity investments. We show that in the case when asset values have a normal distribution an analytical formula for the unexpected loss contribution may be developed. We show that the capital requirements for equity investments are quite different to those of credit exposures, since equity investments can suffer substantial loss of value even when the underlying company has not defaulted.     

Credit Risk in Private Debt Portfolios

Default, loss severity, and average loss rates for a large sample of privately placed bonds are presented and compared with loss experience for publicly issued bonds. The chance of very large portfolio losses is estimated and some determinants of such losses are analyzed. Results show ex ante riskier classes of private debt perform better on average than public debt. Both diversification and the riskiness of individual portfolio assets influence the bad tail of the portfolio loss distribution. Private placements are similar to corporate loans in that both are monitored private debt. The results are thus relevant to management and securitization of private debt portfolios generally.     

Internal ratings systems,implied credit risk and the consistency of banks’ risk classification policies

This paper aims at improving our understanding of internal risk rating systems (IRS) at large banks, of the way in which they are implemented, and at verifying if IRS produce consistent estimates of banks’ loan portfolio credit risk. An important property of our work is that the size of our data set allows us to derive measures of credit risk without making any assumptions about correlations between loans, by applying Carey’s [Carey, Mark, 1998. Credit risk in private debt portfolios. Journal of Finance LIII (4), 1363–1387] non-parametric Monte Carlo re-sampling method.We find substantial differences between the implied loss distributions of two banks with equal “regulatory” risk profiles; both expected losses and the credit loss rates at a wide range of loss distribution percentiles vary considerably. Such variation will translate into different levels of required economic capital. Our results also confirm the quantitative importance of size for portfolio credit risk: for common parameter values, we find that tail risk can be reduced by up to 40% by doubling portfolio size.Our analysis makes clear that not only the formal design of a rating system, but also the way in which it is implemented (e.g. a rating grade composition; the degree of homogeneity within rating classes) can be quantitatively important for the shape of credit loss distributions and thus for banks’ required capital structure. The evidence of differences between lenders also hints at the presence of differentiated market equilibria, that are more complex than might otherwise be supposed: different lending or risk management “styles” may emerge and banks strike their own balance between risk-taking and (the cost of) monitoring (that risk).     

Does Regulatory Capital Arbitrage, Reputation, or Asymmetric Information Drive Securitization?

Banks can choose to keep loans on balance sheet as private debt or transform them into public debt via asset securitization. Securitization transfers credit and interest rate risk, increases liquidity, augments fee income, and improves capital ratios. Yet many lenders still retain a portion of their loans in portfolio. Do lenders exploit asymmetric information to sell riskier loans into the public markets or retain riskier loans in portfolio? If riskier loans are indeed retained in portfolio, is this motivated by regulatory capital incentives (regulatory capital arbitrage), or a concern for reputation? We examine these questions empirically and find that securitized mortgage loans have experienced lower ex-post defaults than those retained in portfolio, providing evidence consistent with either the capital arbitrage or reputation explanation for securitization.     

Hierarchical structures in the aggregation of premium risk for insurance underwriting

In the valuation of the Solvency II capital requirement, the correct appraisal of risk dependencies acquires particular relevance. These dependencies refer to the recognition of risk diversification in the aggregation process and there are different levels of aggregation and hence different types of diversification. For instance, for a non-life company at the first level the risk components of each single line of business (e.g. premium, reserve, and CAT risks) need to be combined in the overall portfolio, the second level regards the aggregation of different kind of risks as, for example, market and underwriting risk, and finally various solo legal entities could be joined together in a group.

Solvency II allows companies to capture these diversification effects in capital requirement assessment, but the identification of a proper methodology can represent a delicate issue. Indeed, while internal models by simulation approaches permit usually to obtain the portfolio multivariate distribution only in the independence case, generally the use of copula functions can consent to have the multivariate distribution under dependence assumptions too.

However, the choice of the copula and the parameter estimation could be very problematic when only few data are available. So it could be useful to find a closed formula based on Internal Models independence results with the aim to obtain the capital requirement under dependence assumption.

A simple technique, to measure the diversification effect in capital requirement assessment, is the formula, proposed by Solvency II quantitative impact studies, focused on the aggregation of capital charges, the latter equal to percentile minus average of total claims amount distribution of single line of business (LoB), using a linear correlation matrix.

On the other hand, this formula produces the correct result only for a restricted class of distributions, while it may underestimate the diversification effect.

In this paper we present an alternative method, based on the idea to adjust that formula with proper calibration factors (proposed by Sandström (2007)) and appropriately extended with the aim to consider very skewed distribution too.

In the last part considering different non-life multi-line insurers, we compare the capital requirements obtained, for only premium risk, applying the aggregation formula to the results derived by elliptical copulas and hierarchical Archimedean copulas.     

The effects of loan portfolio concentration on Brazilian banks’ return and risk

This paper tests whether diversification of the credit portfolio at the bank level leads to better performance and lower risk. We employ a new high frequency (monthly) panel data for the Brazilian banking system with information at the bank level for loans by economic sector. We find that loan portfolio concentration increases returns and also reduces default risk; the impact of concentration on bank’s return is decreasing on bank’s risk; there are significant size effects; foreign and state-owned banks seem to be less affected by the degree of diversification. An important additional finding is that there is an increasing concentration trend after the breakout of the recent international financial crisis, specially after the failure of Lehman Brothers.     

Value Creation through Securitization: Evidence from the CMBS Market

Despite recent volatility and constraints in secondary market funding, analysts have ascribed substantial value creation to the securitization of commercial mortgages. Such value creation likely emanates from liquidity enhancements, regulatory arbitrage, price discrimination and risk diversification by pooling and tranching, gains from specialization in origination, servicing, and holding of mortgages, and the like. Indeed, such value creation would be consistent with past accelerated growth in the mortgage- and asset-based securities markets and the sizable profits earned by secondary market intermediaries. In this paper, we estimate the pricing effects of commercial mortgage securitization. We do so by applying loan level data from 1992–2003 to compare the pricing of conduit and portfolio loans held in CMBS structures. In contrast to portfolio loans, which are held for investment by originating institutions, conduit loans are originated for the sole purpose of sale and securitization in the secondary market. If securitization creates value, it should be evidenced in the relative pricing of conduit loans sold into CMBS pools and in a lower cost of capital to loan originators. We estimate a reduced-form model, in which the interest rate spread between commercial mortgages and comparable-maturity treasury securities varies with loan characteristics, capital market conditions, and conduit loan status. Estimation results indicate that securitization of conduit loans leads to an 11 basis points reduction in commercial mortgage interest rates. We assess robustness of results via hazard model tests for omitted variables and originator-specific effects. We further estimate a simultaneous equations model that accounts for the potential endogeneity of mortgage loan terms to the mortgage-treasury rate spread. Results of that analysis suggest a larger 20 basis points reduction in loan pricing among conduit loans sold into CMBS structures.     

Do capital buffers matter? Evidence from the stocks and flows of nonperforming loans

This paper investigates the determinants of the stocks and flows (both in- and outflows) of nonperforming loans (NPLs) by considering a bank-specific factor that is not adequately analysed in the literature, namely, bank capital buffers. Using unbalanced panel data with 6,087 bank-year observations for the 2006–2018 period and a two-step system generalised method of moments (GMM) estimation, we find that banks with higher levels of capital buffers (both in terms of Tier 1 and total capital) have fewer NPL stocks and generate fewer NPL inflows. When we control for the characteristics of the loan portfolio, real guarantees collected by the bank increase the stocks and flows of new, impaired loans, while personal guarantees favour the outflow of bad loans.