How do US credit supply shocks propagate internationally? A GVAR approach

We study how US credit supply shocks are transmitted to other economies. We use the recently developed GVAR approach to model financial variables jointly with macroeconomic variables in 33 countries for the period 1983–2009. We experiment with inter-country links based on bilateral trade, portfolio investment, foreign direct investment and banking exposures. Capturing both bilateral trade and financial exposures in a GVAR fits the data better than using trade weights only. We use sign restrictions on the short-run impulse responses in the US model to identify the credit supply shocks. We find that negative credit supply shocks have strong negative effects on US and foreign GDP. Credit and equity markets in several countries respond clearly to the shocks. Exchange rate responses are consistent with a “flight to quality” to the US dollar. The credit supply shocks explain about a fifth of one-year-ahead output forecast error variance in the US and about a tenth in the euro area and the UK, but considerably less elsewhere.     

Do we need a global VAR model to forecast inflation and output in South Africa?

This study determines whether the global vector autoregressive (GVAR) approach provides better forecasts of key South African variables than a vector error correction model (VECM) and a Bayesian vector autoregressive (BVAR) model augmented with foreign variables. The article considers both a small GVAR model and a large GVAR model in determining the most appropriate model for forecasting South African variables. We compare the recursive out-of-sample forecasts for South African GDP and inflation from six types of models: a general 33 country (large) GVAR, a customized small GVAR for South Africa, a VECM for South Africa with weakly exogenous foreign variables, a BVAR model, autoregressive (AR) models and random walk models. The results show that the forecast performance of the large GVAR is generally superior to the performance of the customized small GVAR for South Africa. The forecasts of both the GVAR models tend to be better than the forecasts of the augmented VECM, especially at longer forecast horizons. Importantly, however, on average, the BVAR model performs the best when it comes to forecasting output, while the AR(1) model outperforms all the other models in predicting inflation. We also conduct ex ante forecasts from the BVAR and AR(1) models over 2010:Q1–2013:Q4 to highlight their ability to track turning points in output and inflation, respectively.     

A capital adequacy buffer model

We develop a new capital adequacy buffer model (CABM) that is sensitive to dynamic economic circumstances. The model, which measures additional bank capital required to compensate for fluctuating credit risk, is a novel combination of the Merton structural model, which measures distance to default and the timeless capital asset pricing model (CAPM), which measures additional returns to compensate for additional share price risk. We apply the model to a portfolio of mid-cap loan assets over a 10-year period that includes pre-GFC (global financial crisis), GFC and post-GFC. An analysis of actual defaults over this period shows the model to be far more accurate in determining the capital adequacy levels needed to counter credit risk than an unresponsive ratings model such as the Basel standardized approach.     

综合收益最优的贷款组合鲁棒优化模型

商业银行信贷经营的基本目标是资金来源与运用在效益性、安全性和流动性上的“三性”平衡,而贷款组合优化配置是商业银行维持或达到资金“三性”平衡的有效方式,也是商业银行信贷经营管理中的重要内容.而贷款的预期收益具有不确定性,如果简单地假设其预期收益率往往会出现与实际脱节的情况,因此需要考虑贷款期间可能出现的变化.针对这一特征,考虑构建风险调整后资本收益率(RAROC)最优的贷款组合鲁棒优化模型.根据某商业银行实际经营数据进行数值分析,结果表明该模型具有鲁棒性,不仅能够兼顾贷款组合综合收益以及未来收益的不确定性因素,同时还可以在贷款组合风险约束范围内获得最大收益,为商业银行贷款优化配置管理提供有效可行的决策依据.     

Momentum crash,credit risk and optionality effects in bear markets and crisis periods: evidence from the US stock market

This study explores whether the credit risk anomaly exhibits option-like behaviour similar to the momentum anomaly. It finds that the inverted credit risk spread indeed displays option-like behaviour in bear market states. Unlike a momentum portfolio, which is effectively a short call option on the market, an inverted credit risk portfolio appears to be a long call option on the market.     

Even more on monetary policy in a small open economy

It is well known that in a small open economy with full capital mobility and a fixed exchange rate, monetary policy is ineffective in influencing real output (e.g. the works of Fleming [Int. Monetary Fund Staff Pap. 9 (1962) 369.] and Mundell [Can. J. Econ. Polit. Sci. 29 (1963) 475.]). However, Wu [Int. Rev. Econ. Finance 8 (1999) 223.] finds that when the credit channel is added to this model, monetary policy can have real effects under a fixed exchange rate system. This conclusion hinges on the assumption that open market operations have no effect on foreign exchange reserves of the central bank when evaluating how a change in monetary policy affects the loan market. This assumption is incorrect because under a fixed exchange rate regime, the quantity of foreign reserves becomes endogenous in the model. It is shown that when this assumption is relaxed, monetary policy is still ineffective in influencing output under a fixed exchange regime, even with an operative credit channel.     

我国企业债券信用利差宏观决定因素研究

文章以Merton(1974)的结构化模型为基础,基于2000年2月至2010年9月的面板数据,对影响我国沪深债市企业债券信用利差因素进行了实证研究。研究结果表明,GDP指数和M1发行量对企业债券信用利差的影响为正,无风险利率和收益率曲线斜率的影响为负。此外,模型的解释力明显随信用级别的降低而提高,且加入非线性变量和前期变量后模型的拟合度大幅提高,说明新模型更加符合实际情况。     

Credit booms and busts in emerging markets

We investigate to what extent corporate governance and risk management mitigate the involvement of banks in credit boom and bust cycles. We study a unique, hand‐collected dataset covering 156 banks from Central and Eastern Europe during 2005–2012. We document that stronger risk management is associated with more moderate pre‐crisis credit growth but not with fewer credit losses in the crisis. With respect to bank governance, we find that a higher share of foreign members on the supervisory board is associated with less rapid credit growth in the pre‐crisis period and a lower level of credit losses during the crisis period.     

商业银行信用风险与宏观经济——基于压力测试的研究

本文采用压力测试框架,研究了宏观经济波动对商业银行信用风险的影响。文章以不良贷款率度量信用风险,以名义GDP增长率、广义货币供应量（M2）增速、居民消费价格指数（CPI）以及房地产销售价格指数作为宏观经济变量,建立了合适的宏观压力测试模型。在GDP增速放缓、CPI上升、M2增速下降的压力情景下,预测了2011年第一季度到第四季度的不良贷款率的变化路径。实证结果表明在压力情景下商业银行的不良贷款率将会显著上升。     

中国公司债券的信用利差与流动性风险

利用主成分分析法构造公司债券流动性风险测度指标,引入M-Copula函数和Markov机制转换模型实证分析中国公司债券的流动性风险与信用利差的关系。结果表明,M-Copula函数与Markov机制转换模型的实证结果一致。具体如下:公司债券的流动性风险对信用利差的影响是一个动态的非线性过程;两者之间存在显著的非对称尾部相关性,其中上尾相关性较高,即熊市时期流动性风险和信用利差同时增大的概率高于牛市时期,且熊市时期流动性风险对信用利差的影响程度显著高于其他时期。     

商业银行信用卡业务发展与风险管理

回顾信用卡业务在我国的发展历程、分析信用卡业务的发展现状,不难发现中国已成为全球信用卡业务增长最快、发展潜力最大的市场。作为未来消费信贷的重要增长点,在金融行业民间资本准入制度的放开、全球化进程不断深入、移动互联快速普及的大数据时代,民间资本、外资银行对信用卡业务的广泛渗透,以及互联网金融的创新发展,必将导致国内信用卡业务参与方关系日趋复杂,信用卡市场竞争日趋激烈。因此,信用卡业务发展过程中所面临的问题及发行风险不容忽视。文中采用行为概率及效用函数的方法对信用卡消费行为进行博弈分析,应用行为分析的结果,对信用卡业务中诸如个人信用登记评估制度,发卡机构营销、审批机制和产品附加值,消费管理和奖惩制度及法律法规制定等相关问题进行了剖析,系统分析了银行信用卡发行过程中的风险,并对信用卡市场的健康发展提出了几点建议。     

Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach

We use regular vine (r-vine), canonical vine (c-vine) and drawable vine (d-vine) copulas to examine the dependence risk characteristics of three 20-stock portfolios from the retail, manufacturing and gold-mining equity sectors of the Australian market in periods before, during and after the 2008–2009 global financial crisis (GFC). Our results indicate that the retail portfolio is less risky than the manufacturing counterpart in the crisis period, while the gold-mining portfolio is less risky than both the retail and manufacturing sector portfolios. Both the retail and gold stocks display a higher propensity to yield positively skewed returns in the crisis periods, contrary to the manufacturing stocks. The r-vine is found to best capture the multivariate dependence structure of the stocks in the retail and gold-mining portfolios, while the d-vine does it for the manufacturing stock portfolio. These findings could be used to develop dependence risk- and investment risk-adjusted strategies for investment, rebalancing and hedging which more adequately account for the downside risk in various market conditions.     

Unprotected resources and voracious world markets: A proof of losses in North–South Trade

This paper develops a generalization of Chichilnisky's [Chichilnisky, G., 1994. North–South Trade and the global environment. American Economic Review 84 (4), 851–874.] model of North–South Trade, making use of the dual theory of international trade. The central purpose is to provide rigorous proof of the previously unproven assertion that the South can lose from trade and from price changes that normally constitute terms-of-trade improvements.     

Spillover across Eurozone credit market sectors and determinants

We examine spillover and its determinants among Eurozone sector level credit markets using time and frequency domain spillover approaches. Based on network theory and connectedness analysis, we identify the sectors that are major transmitters and receivers of spillover during normal and crisis periods. The rolling window analysis shows that short-run spillover among credit market sectors intensifies during global and Eurozone crisis periods. Further, using Bayesian model averaging, we find that overall financial conditions and stock market volatility are the main drivers of total and sector-level spillover. Our findings have important implications for policymakers and investors interested in Euro-area credit risk at the sector level.     

中国银行业构建现代信用风险管理模式的思考

针对信用风险的复杂特征,按照比较完善的市场风险管理模型方法可以构建现代信用风险管理模型。同时,在信息系统和内部风险评级逐步完善、信用衍生工具广泛使用的前提下,可以引入现代资产组合管理理论的思想、方法与技术,实施信用风险管理的资产组合管理方法,进而实现现代信用风险管理。重点研究现代信用风险管理的一般模式,并在此模式下,探讨中国实际背景下银行业的战略选择问题,指出完善信息管理信息系统和内部评级体系以及进一步研究信用衍生工具等金融创新的具体思路。     

我国林业上市公司信用风险研究——基于KMV模型

文章以我国沪深两市A股林业上市公司为研究对象,选取2007-2012年首次成为ST的8家公司和对应的8家非ST公司为研究样本,运用KMV模型研究我国林业上市公司信用风险。实证过程中,文章根据我国林业公司特点研究确定KMV模型中各参数的计算方法,计算出在不同违约点下各个样本的违约距离,主要结论:财务危机前非ST公司与ST公司的违约距离表现出显著差异,运用KMV模型能够有效识别我国林业上市公司的信用风险状况;我国林业上市公司的违约点应设定为短期负债加上50%长期负债;在研究连续两年违约距离的基础上,构建了我国林业上市公司两级信用风险预警体系。     

A small forward-looking inter-country model (Belarus, Russia and Ukraine)

The paper describes an inter-country model developed on the New Keynesian Phillips curve principle for the economies of Belarus, Russia and Ukraine. Technically the modelling idea has been grounded within the concept of the infinite dimensional vector autoregressive models by Chudik and Pesaran [Chudik A., Pesara M.H., 2007. Infinite-dimensional VAR's and factor models. IZA; DP No. 3206]. The main developments are such that the model is 1) interdependent rather than vector autoregressive, 2) estimated by the generalised method of moments and 3) forward-looking. The primary linkage of the country models is provided through the real effective exchange rates of particular countries, while the secondary linkages are through the Chudik and Pesaran cross-sectional augmentations. A series of Monte Carlo experiments confirms that the small cross-dimension of the model and a possible dominance of one country in the panel (Russia) should not distort the results in a significant way. A series of stochastic simulation experiments made with and without the assumption of observational equivalence principle shows a possible spread of the Dutch Disease from Russia to other countries in the model.     

信用悖论及其解决

信用悖论是银行业在其信用风险管理过程存在的较大问题:保持良好的客户关系与分散信用风险之间的矛盾。笔者考察和研究了运用现代资产组合理论进行风险分散化贷款组合管理的KMV模型和以金融创新——信用衍生品进行对冲组合管理的理论和实践。     

基于SV-KMV模型的信用风险度量研究

KMV模型是度量信用风险的主要模型,股权价值波动率是KMV模型的重要参数,应用改进KMV模型GARCH-KMV模型与SV-KMV模型对中国上市公司信用质量的实证研究表明:股权价值波动与KMV模型的结果违约距离高度负相关;GARCH-KMV与SV-KMV模型均能度量上市公司信用状况,但SV-KMV模型比GARCH-KMV模型度量效果更好。     

Measuring and Optimizing Portfolio Credit Risk: A Copula‐based Approach*

In this work, we present a methodology for measuring and optimizing the credit risk of a loan portfolio taking into account the non‐normality of the credit loss distribution. In particular, we aim at modelling accurately joint default events for credit assets. In order to achieve this goal, we build the loss distribution of the loan portfolio by Monte Carlo simulation. The times until default of each obligor in portfolio are simulated following a copula‐based approach. In particular, we study four different types of dependence structure for the credit assets in portfolio: the Gaussian copula, the Student's t‐copula, the grouped t‐copula and the Clayton n‐copula (or Cook–Johnson copula). Our aim is to assess the impact of each type of copula on the value of different portfolio risk measures, such as expected loss, maximum loss, credit value at risk and expected shortfall. In addition, we want to verify whether and how the optimal portfolio composition may change utilizing various types of copula for describing the default dependence structure. In order to optimize portfolio credit risk, we minimize the conditional value at risk, a risk measure both relevant and tractable, by solving a simple linear programming problem subject to the traditional constraints of balance, portfolio expected return and trading. The outcomes, in terms of optimal portfolio compositions, obtained assuming different default dependence structures are compared with each other. The solution of the risk minimization problem may suggest us how to restructure the inefficient loan portfolios in order to obtain their best risk/return profile. In the absence of a developed secondary market for loans, we may follow the investment strategies indicated by the solution vector by utilizing credit default swaps.