Banks’ risk taking,financial innovation and macroeconomic risk

This paper shows how financial innovation in combination with the fall of macroeconomic risk can explain the strong growth of the primary and secondary credit markets in the U.S. economy. We document empirically the fall in macroeconomic risk, the expansion of the prime and secondary credit market and we provide evidence that changes in macroeconomic risk are closely related to the evolution of the prime market. In the theoretical part of the paper we study in a simple portfolio optimization framework the effect of financial innovation and macroeconomic risk on banks’ risk taking. The results of the model show that financial innovation increases bank appetite for risky investment both in the prime and secondary markets and that this effect is stronger in environments with low aggregate macroeconomic risk. In addition the banking system becomes less stable because of the portfolio risk of each individual bank increases.     

Measuring Credit Risk of a Bank's Corporate Loan Portfolio Using Advanced Internal Ratings Base Approach

Abstract

The use of technical and advanced approaches in the measurement of credit risk of banks' portfolios has nowadays become a very hot issue. The most recent technical report issued by the Basel Committee in May 2003 has concentrated heavily on the measurement of credit risk using either foundation or advanced Internal Ratings Base (IRB) approaches. This empirical research study attempts to measure credit risk of a bank's corporate loan portfolio, including firms from 10 different Turkish sectors. The monthly observations of the total amount of corporate loans and the total amount of corporate loans at default across various sectors are downloaded from the web page of Central Bank of Turkey (CBT) in a period of 1999-2002. This period covers 47 monthly observations since CBT has captured sectoral corporate loans beginning of 1999. Therefore, the observed sectoral default rates are needed to be simulated to obtain a nicely shaped distribution. Monte Carlo simulation is applied for 1,000 times. Based on the simulated default rates, the expected sectoral default rates are computed. Next, a credit quality rating scale is fitted into sectoral default rates distributions. Finally, the sectoral weights in the whole loan portfolio are multiplied by the expected sectoral default rates matrix, considering cross-sectoral correlations to get the total amount of the bank's credit risk and capital requirement. It is assumed that sectoral monthly default rates are a good representative of the default risk of a sample bank's corporate loan portfolio since no publicly available data on any particular bank's corporate loan portfolio composition exists. Nevertheless, this research may be a good application for measuring the credit risk of banks' corporate loan portfolios using advanced IRB approach.     

What drives credit risk in the Indian banking industry? An empirical investigation

Using a two-step system GMM approach on a unique bank-level dataset for the period 1998/99–2013/14, this paper tries to explore the key determinants of credit risk in the Indian banking industry. The main premise of this paper is that, along with regulatory and institutional factors, both macroeconomic and bank-specific variables influence the formation of credit risk in a banking system, and their influences vary across ownership groups. The empirical findings suggest that lower profitability, more diversification in the banking business, the large size of banks and a higher concentration of banks in lending increase the probability of defaults in India. We find a significant degree of persistence in credit risk, and the observed persistence is higher in the gross non-performing loans (NPLs) specification relative to what has been observed in the net NPLs specification. In the case of public sector banks, NPLs are more sensitive to internal bank-specific factors, while for private and foreign banks, macroeconomic and industry-related factors play a significant role in determining credit risk. Our results are robust for different panel data estimation models and sub-samples of ownership groups. The findings of this paper provide important insights into the formation of default risk in the banking system of an emerging market economy.     

Modeling frailty-correlated defaults using many macroeconomic covariates

We propose a novel time series panel data framework for estimating and forecasting time-varying corporate default rates subject to observed and unobserved risk factors. In an empirical application for a U.S. dataset, we find a large and significant role for a dynamic frailty component even after controlling for more than 80% of the variation in more than 100 macro-financial covariates and other standard risk factors. We emphasize the need for a latent component to prevent a downward bias in estimated default rate volatility and in estimated probabilities of extreme default losses on portfolios of U.S. debt. The latent factor does not substitute for a single omitted macroeconomic variable. We argue that it captures different omitted effects at different times. We also provide empirical evidence that default and business cycle conditions partly depend on different processes. In an out-of-sample forecasting study for point-in-time default probabilities, we obtain mean absolute error reductions of more than forty percent when compared to models with observed risk factors only. The forecasts are relatively more accurate when default conditions diverge from aggregate macroeconomic conditions.     

Financial stability indicators and public debt developments

This paper investigates the inter-linkages between financial stability and fiscal policy. It analyzes the effect of selected financial stability indicators on the probability of future debt deterioration, controlling for several macroeconomic variables. We find significant evidence that a fragile banking system can put at risk public finances. Weak bank profitability, low asset quality and a weak capital base increase the fragility of the banking system, thus, raising the probability of future fiscal troubles.     

An asset protection scheme for banks exposed to troubled loan portfolios

We examine a specific portfolio credit derivative, an Asset Protection Scheme (APS), and its applicability as a discretionary regulatory tool to reduce asymmetric information and help restore the capital base of troubled banks. The APS can be a fair-valued contract with an appropriate structure of incentives. We apply two alternative multivariate structural default risk models: the classical Gaussian Merton model and a model based on Normal Inverse Gaussian processes. Using a data set on annual farm level data from 1996 to 2009, we use the Danish agricultural sector as a case study and price an APS on an agricultural loan portfolio. We compute the economic capital for this loan portfolio with and without an APS. Moreover, we illustrate how model risk in the form of parameter uncertainty is reduced when an APS is attached to the loan portfolio.     

Financial Intermediaries,Credit Shocks and Business Cycles

We document the cyclical properties of aggregate balance sheet variables of the US commercial banks: (i) Bank credits and deposits are less volatile than output, while net worth and leverage ratio are several times more volatile, (ii) bank credits and net worth are procyclical, while deposits, leverage ratio and loan spread are countercyclical. We then present a real business cycle model with a financial sector to investigate how the dynamics of macroeconomic aggregates and balance sheet variables of the US banks are influenced by empirically disciplined shocks to bank net worth. Both calibrated and estimated versions of the model show that these financial shocks are important not only for explaining the dynamics of financial flows but also for the dynamics of macroeconomic variables. We find that the recent deterioration in aggregate net worth of the US banking sector contributed significantly to the 2007–09 recession.     

A novel profit cutting mechanism for Chinese Banks: Theory and Multi-dimensional evidence

As China’s macroeconomic growth faces increasing pressure from the global COVID-19 pandemic, a surprising and politically controversial phenomenon has emerged: the profitability of banks in China exceeded that of enterprises and non-financial industries. The People’s Bank of China and regulatory authorities have hence taken measures to incentivize banks to transfer part of their profits to enterprises, with the aim to stabilize enterprises and employment. This paper proposes a novel profit cutting mechanism focusing on loan structure adjustments to address the limitations of the current approach centering on lowering loan interest rates. The theoretical and empirical analysis show, at both the macro and micro level, that an increase in the proportion of credit loans can benefit the development of enterprises without weakening banks’ operating performance in the long term, leading to a Pareto improvement within enterprise-banking sectors. The findings suggest that banks in China should gradually adjust their loan structures by providing greater credit loan access to enterprises, either voluntarily or directed by policy.     

The Macroeconomic Effects of Shocks to Large Banks’ Capital

We propose a simple approach to quantifying the macroeconomic effects of shocks to large banks’ leverage. We first estimate a standard dynamic model of leverage targeting at the bank level and use it to derive an aggregate measure of the economic capital buffer of large US bank holding corporations. We then evaluate the response of key macro variables to a shock to this aggregate bank capital buffer using standard monetary VAR models. We find that shocks to the capital of large US banks explain a substantial share of the variance of credit to firms and real activity.     

基于省域视角的信用风险模型适应性分析

巴塞尔新资本协议在鼓励银行采用内部评级法评估信用风险以提取资本准备的同时也强化了各国监管机构对内部评级模型绩效检验与审查的要求.CreditMetrics和CreditRisk+是银行业信用风险评估的基准模型.从建模的数学方法看,CreditRisk+是基于违约的判断,而CreditMetrics则是根据等级变化评价.利用江苏省银监局的相关统计数据对信用风险评估模型进行参数特性审查与绩效检验,结果显示这两类常用模型都可以在江苏的商业银行经营实践中稳定地实现根据信贷组合的实际风险状况进行内部资本配置这一目标.     

Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model

This study employs a new GARCH copula quantile regression model to estimate the conditional value at risk for systemic risk spillover analysis. To be specific, thirteen copula quantile regression models are derived to capture the asymmetry and nonlinearity of the tail dependence between financial returns. Using Chinese stock market data over the period from January 2007 to October 2020, this paper investigates the risk spillovers from the banking, securities, and insurance sectors to the entire financial system. The empirical results indicate that (i) three financial sectors contribute significantly to the financial system, and the insurance sector displays the largest risk spillover effects on the financial system, followed by the banking sector and subsequently the securities sector; (ii) the time-varying risk spillovers are much larger during the global financial crisis than during the periods of the banking liquidity crisis, the stock market crash and the COVID-19 pandemic. Our results provide important implications for supervisory authorities and portfolio managers who want to maintain the stability of China’s financial system and optimize investment portfolios.     

Financial intermediation costs in low income countries: The role of regulatory,institutional, and macroeconomic factors

We analyze factors driving persistently higher financial intermediation costs in low-income countries (LICs) relative to emerging market (EM) country comparators. Using the net interest margin as a proxy for financial intermediation costs at the bank level, we find that within LICs a substantial part of the variation in interest margins can be explained by bank-specific factors: margins tend to increase with higher riskiness of credit portfolio, lower bank capitalization (or lower risk aversion), and smaller bank size. Overall, we find that concentrated market structures and lack of competition in LICs banking systems and institutional weaknesses constitute the key impediments preventing financial intermediation costs from declining. Our results provide strong evidence that policies aimed at fostering banking competition and strengthening institutional frameworks can reduce intermediation costs in LICs.     

商业银行国家助学贷款之风险分析

文章着重论述了国家助学贷款的信贷风险问题,指出国家助学贷款是一种财政贴息无担保的信用贷款,是一项公共政策;提出防范助学贷款的信贷风险,需要构建以国家征信体系为基础的社会诚信环境,完善全国性的个人征信信息系统,大力推广生源地贷款,创建助学贷款的风险管理系统。     

Bank asset structure,real-estate lending,and risk-taking

The banking industry changed substantially in the 1990s as the number of banks declined rapidly, and as we document, commercial banks dramatically shifted their assets to real-estate loans. The portfolio restructuring seems to be followed mainly by capital-constrained banks as real-estate banks have lower risk-based-capital ratios relative to those of our benchmark group. Trading off credit risk for interest-rate risk is only one of the ways to arbitrage regulatory capital. We also show that real-estate banks keep higher ratios of fixed-rate loans to total assets and face higher probabilities of insolvency. The increasing proportion of banks specializing in real-estate lending, the incentives of regulatory discipline, and the weaknesses of risk-management strategies could stress the condition of the banking system during periods of large unexpected increases in interest-rates and are important issues for regulators and bank managers.     

A through-the-cycle model for retail lending economic capital

Problems in the US mortgage industry have shown weaknesses in the standard regulatory and economic capital approaches. Although a significant amount of discussion is occurring around how to segment portfolios or predict key variables in order to better fit the existing formulas, we believe that a re-examination of existing capital formulas with respect to credit risk is required.In this paper we develop a formula which is specifically tuned to the dynamics of retail loan portfolios and which could be employed for either regulatory capital or economic capital. The key advantages of this approach are that it is based upon a much more accurate model of retail loan defaults, does not require any new data feeds, is based upon readily available modeling frameworks, and can adapt to portfolio changes such as those observed in the US mortgage crisis.     

我国银行体系的稳健性研究——基于面板VAR的实证分析

本文构建了我国银行稳健性指标体系的核心指标组,并合成银行稳健性指数BSI以综合评价我国银行体系的稳定性,检验了银行稳健性与经济增长、信贷规模扩张及资本市场价格之间的面板Granger因果关系。通过构建面板VAR模型度量了宏观经济与金融变量对银行稳定性的冲击。方差分解的结果显示,银行稳健性的波动主要受自身和GDP的影响,GDP增长率对BSI的波动的解释程度接近50%,说明银行的稳健性依赖于稳定的经济增长,受经济冲击的影响程度相当高。     

Forecasting and stress testing credit card default using dynamic models

We present discrete time survival models of borrower default for credit cards that include behavioural data about credit card holders and macroeconomic conditions across the credit card lifetime. We find that dynamic models which include these behavioural and macroeconomic variables provide statistically significant improvements in model fit, which translate into better forecasts of default at both account and portfolio levels when applied to an out-of-sample data set. By simulating extreme economic conditions, we show how these models can be used to stress test credit card portfolios.     

商业银行国家助学贷款之风险分析

文章着重论述了国家助学贷款的信贷风险问题,指出国家助学贷款是一种财政贴息无担保的信用贷款,是一项公共政策;提出防范助学贷款的信贷风险,需要构建以国家征信体系为基础的社会诚信环境,完善全国性的个人征信信息系统,大力推广生源地贷款,创建助学贷款的风险管理系统。     

Assessing optimal credit growth for an emerging banking system

The paper sets forth a novel way to estimate the optimal level of credit growth for an emerging banking system. Contrary to the traditional credit-to-GDP gap indicator, credit growth is considered to be optimal when it does not accelerate credit risk measured by loan loss provisions. We provide empirical support for modelling the provision charge ratio dynamic by the quadratic function of the credit growth deviation from its optimal level. The operational framework consists of a simplified financial satellite with two equations representing credit growth and change in the provision charge ratio. Our empirical results show that a 3 percent (±1 pp margin) quarterly increase in credit to the private sector is, in nominal terms, optimal for financial stability and sustainable growth in Romania.     

基于高阶矩风险防范的银行资产负债组合优化模型研究——以A银行为例

资产负债管理能力是现代商业银行的基本能力,其核心在于风险控制和价值创造。商业银行资产负债组合优化是现代商业银行信贷管理框架中的核心内容,它对于保持银行资产流动性、安全性和赢利性的＂三性＂的最佳组合、优化配置资源、提高银行的生存能力和竞争能力,具有重要的现实意义。本文通过以贷款组合的VaR约束控制贷款组合的二阶矩,即控制了资产组合的风险;以贷款组合收益率的偏度约束控制贷款组合的三阶矩,即控制了贷款组合收益率发生总体损失的可能性;以组合收益率的峰度约束控制贷款组合的四阶矩,即减少了组合收益率发生极端损失的可能性,建立了资产分配的收益率均值-方差-偏度-峰度模型。