Stochastic reserve losses and bank credit expansion

This paper addresses the issue of bank credit expansion when reserve and deposit flows are stochastic. For a risk-neutral bank able to lend and borrow at fixed interest rates, and incurring a lump sum transaction cost when short of reserves, it is found that if deposit flows are normally distributed — essentially the Orr-Mellon model — the distribution of new reserves among banks does not affect credit expansion. An explanation for this counter-intuitive result is given by establishing a parallel between the model and the literature on portfolio theory. The implications for credit expansion of more general assumptions is discussed.     

Modelling the economic value of credit rating systems

In this paper we develop a model of the economic value of credit rating systems. Increasing international competition and changes in the regulatory framework driven by the Basel Committee on Banking Supervision (Basel II) called forth incentives for banks to improve their credit rating systems. An improvement of the statistical power of a rating system decreases the potential effects of adverse selection, and, combined with meeting several qualitative standards, decreases the amount of regulatory capital requirements. As a consequence, many banks have to make investment decisions where they have to consider the costs and the potential benefits of improving their rating systems. In our model the quality of a rating system depends on several parameters such as the accuracy of forecasting individual default probabilities and the rating class structure. We measure effects of adverse selection in a competitive one-period framework by parameterizing customer elasticity. Capital requirements are obtained by applying the current framework released by the Basel Committee on Banking Supervision. Results of a numerical analysis indicate that improving a rating system with low accuracy to medium accuracy can increase the annual rate of return on a portfolio by 30–40 bp. This effect is even stronger for banks operating in markets with high customer elasticity and high loss rates. Compared to the estimated implementation costs banks could have a strong incentive to invest in their rating systems. The potential of reduced capital requirements on the portfolio return is rather weak compared to the effect of adverse selection.     

Cyclical correlations, credit contagion, and portfolio losses

We model aggregate credit losses on large portfolios of financial positions contracted with firms subject to both cyclical default correlation and direct default contagion processes. Cyclical correlation is due to the dependence of firms on common economic factors. Contagion is associated with the local interaction of firms with their business partners. We provide an explicit normal approximation of the distribution of portfolio losses. We quantify the relation between the variability of global economic fundamentals, strength of local firm interaction, and the fluctuation of losses. We find that cyclical oscillations in fundamentals dominate average losses, while local interaction causes additional fluctuations of losses around their average. The strength of the contagion-induced loss variability depends on the complexity of the business partner network.     

Interacting particle systems for the computation of rare credit portfolio losses

In this paper, we introduce the use of interacting particle systems in the computation of probabilities of simultaneous defaults in large credit portfolios. The method can be applied to compute small historical as well as risk-neutral probabilities. It only requires that the model be based on a background Markov chain for which a simulation algorithm is available. We use the strategy developed by Del Moral and Garnier in (Ann. Appl. Probab. 15:2496–2534, 2005) for the estimation of random walk rare events probabilities. For the purpose of illustration, we consider a discrete-time version of a first passage model for default. We use a structural model with stochastic volatility, and we demonstrate the efficiency of our method in situations where importance sampling is not possible or numerically unstable.      

Modelling credit in the transmission mechanism of the United Kingdom

Studies have focused heavily on money in the transmission mechanism of monetary policy. In this article we explore the empirical importance of credit. The paper provides a framework in which to analyse the balance sheets of, and financial flows between, different sectors of the UK economy, and an econometric model of the interactions between non-financial firms, households and credit offered by banks and non-bank financial intermediaries. The paper also provides a dynamic structural model of bank and building society credit, money and decisions to consume and invest and then adds credit from non-bank financial intermediaries. Our bottom line is that credit is an important part of the transmission process of UK monetary policy.     

Stochastic reserve losses,bank credit expansion and Bayesian information

In standard bank credit expansion models the optimal amount of new demand deposits to create is derived for a given level of uncertainty of reserves losses. In this paper, I analyze in detail, the microeconomics of bank credit expansion in which the degree of uncertainty is a decision variable for the bank to determine. First, the role of information in adjusting the bank's expected profit is established and its impact on demand deposit creation is discussed. I then derive the optimal demand for information and its comparative static behavior is examined. Finally, I discuss the major implications of considering the level of uncertainty as a decision variable in the bank credit expansion literature.     

Modelling bonds and credit default swaps using a structural model with contagion

This paper develops a two-dimensional structural framework for valuing credit default swaps and corporate bonds in the presence of default contagion. Modelling the values of related firms as correlated geometric Brownian motions with exponential default barriers, analytical formulae are obtained for both credit default swap spreads and corporate bond yields. The credit dependence structure is influenced by both a longer-term correlation structure as well as by the possibility of default contagion. In this way, the model is able to generate a diverse range of shapes for the term structure of credit spreads using realistic values for input parameters.     

Interaction of credit and liquidity risks: Modelling and valuation

In this paper we discuss the interaction of default risk and liquidity risk on pricing financial contracts. We show that two risks are almost indistinguishable if the underlying contract has non-negative values; however, if it can take both positive and negative values then these two risks demand different risk premiums depending on their loss rates and distributions. We discuss a structural default model and a discrete time default model with exponentially distributed liquidity shocks. We show that short-term yield spreads are dominated by liquidity risk rather than credit risk. We suggest a two-stage procedure to calibrate the model with one scalar optimization problem and one linear programming problem.     

多因素驱动信用卡业务 加速回归信用消费本源

继网络购物兴盛之后,越来越多的金融工具被引入消费支付场景,特别是京东白条、蚂蚁花呗等类信用卡消费金融产品的广泛普及以及传统信用卡业务向场景消费的迅速转型,有力助推我国经济步入信用消费新时代。信用消费是指消费者借助金融借款等工具提前享用所购商品或服务的消费形式。     

小企业信用影响要素分析

在国际金融危机肆虐和国内外经济急剧变化的大背景下,我国许多小企业遭遇"钱荒",进入困难期和阵痛期.为保证小企业的健康发展,国家相继出台和调整了金融、财政等相关政策,在一定程度上缓解了小企业的生存压力.出于规避风险和挖掘高质量客户的需要,许多商业银行对于加大小企业信贷投放仍比较审慎.由于缺少科学的小企业信用评价指标体系,大多数中资银行机构的信贷人员一般采用担保、抵押、质押等方式控制风险,使得小企业融资较为困难.     

Sovereign credit ratings: Discovering unorthodox factors and variables

The presence of different rating agencies and nuanced viewpoints on the determinants of sovereign credit ratings has led to convoluted and contested narratives; hence a need to arrive at common ground on both the significant and prioritised factors important in sovereign rating assessments. Furthermore, much research has focused on a regression analysis of variables which were determined as important to sovereign ratings on an a priori theoretical basis, while excluding a factor analysis which integrates variables within a multifaceted framework. This paper argues that the variables used in existing research are subject to a priori theoretical selection rather than being selected empirically. There has also been an insufficient utilisation of rating agencies' methodology papers in assisting with the selection of variables, and a lack of analysis of the rating agencies' application of factors. Hence, this paper unearths both new factors and variables relevant to assessing sovereign ratings. The findings suggest that there needs to be a broadened understanding of indicators used to analyse and assign sovereign ratings, and a prioritisation of analysed aspects following the inclusion of unorthodox factors and variables.     

Modelling the distribution of the extreme share returns in Singapore

This study aims to model the probability distribution of the extreme daily share returns in Singapore Stock Exchange over the period 1973 to 2005. For that reason the suitability of the Generalized Extreme Value (GEV), Generalized Pareto (GP) and Generalized Logistic (GL) distributions are investigated. The empirical results indicate that the GL distribution best fitted the empirical data over the period of study. Using the too much celebrated GEV and GP distributions for risk assessment could, therefore, lead to underestimation of the extreme risk which could potentially lead to inadequate protection against catastrophic losses.     

On the nature of credit demand and credit rationing in competitive credit markets

Conventional analyses of the credit rationing problem seek to explain that problem within the context of classic demand analysis. In this paper we demonstrate that it is generally inappropriate to apply the notion of classic demand to credit markets, consequently, conventional notions of credit rationing must be rejected. In providing a new definition of credit rationing we also establish the previously rejected characterized by credit rationing.     

The role of non-financial factors in internal credit ratings

Internal credit ratings are expected to gain in importance because of their potential use for determining regulatory capital adequacy and banks' increasing focus on the risk–return profile in commercial lending. Whereas the eligibility of financial factors as inputs for internal credit ratings is widely accepted, the role of non-financial factors remains ambiguous. Analyzing credit file data from four major German banks, we find evidence that the combined use of financial and non-financial factors leads to a more accurate prediction of future default events than the single use of each of these factors.     

Psycho-social factors impacting credit acquisition and use by college students

This research develops and tests two models using a range of psychological and sociological antecedents of credit card acquisition, spending practices and debt accumulation by college students. Six psycho-social dimensions were investigated: parental involvement, locus of control, compulsivity, impulsivity, debt anxiety and social status. Multivariate regression analysis using two dependent variables was conducted: the number of credit cards and total credit card debt. Although the multivariate model was highly significant, considerable variation emerged that best explained the number of credit cards students owned and the total credit card debt carried. The results offer insights in future research needs and consumer protection issues.     

Psychological and demographic factors influencing responsible credit card debt payment

Journal of Financial Services Marketing - The objective of this study is to examine whether individuals’ level of time preference, materialism, risk-taking, optimism, and intuitiveness along...     

A semiparametric model for the systematic factors of portfolio credit risk premia

The aim of this paper is to investigate the empirical relationship between daily fluctuations in the risk premium for holding a large diversified credit portfolio, which we approximate by a benchmark credit index, and some tradeable market factors which capture systematic risk. The analysis is based on an adaptive nonparametric modelling approach which allows for the data-driven estimation of the nonlinear dynamic relationship between portfolio credit risk premia and their hypothetical components. Our main finding is that the empirical weights of the systematic factors display sudden jumps during market crises and a less intense time-dependent behaviour during normal market conditions. In addition, we find that during market crises the directions of the empirical relationships are often inconsistent with ordinary economic intuition, as they are influenced by the specific circumstances of financial markets distress.     

Counterparty credit risk and the credit default swap market

Counterparty credit risk has become one of the highest-profile risks facing participants in the financial markets. Despite this, relatively little is known about how counterparty credit risk is actually priced. We examine this issue using an extensive proprietary data set of contemporaneous CDS transaction prices and quotes by 14 different CDS dealers selling credit protection on the same underlying firm. This unique cross-sectional data set allows us to identify directly how dealers' credit risk affects the prices of these controversial credit derivatives. We find that counterparty credit risk is priced in the CDS market. The magnitude of the effect, however, is vanishingly small and is consistent with a market structure in which participants require collateralization of swap liabilities by counterparties.     

A re-examination of the impact of credit ratings and economic factors on state bond yields

In this article we re-examine the impact of credit ratings and economic factors on state bond yields using a two-step model. In the first step, we adopt an ordered probit technique to obtain consistent estimates of state bond default risk. In the second step, we estimate state bond risk premiums using a regression analysis with a categorized risk variable obtained from the first step. Similar to Terza (1987) and Hsiao (1983), the model involves a categorized ordinal explanatory (rating) variable. However, our two-step model deals with a case where category thresholds are unknown and dependent on economic factors. The model provides consistent estimates for the effects of ratings and economic factors on state bond yields. Contrary to previous findings, we find that state bond yields are mainly affected by fundamental economic variables.