Embedded options in commercial banking and their impact on asset liability management

Commercial bankers sell—more often give away—options to their clients like the prepayment facility attached to a mortgage or the right to obtain a credit at a prespecified interest rate which is associated in France with specific term deposits. This paper aims to present the financial consequences of these options from a microeconomic point of view and on the scale of the French banking system. We first example our valuation techniques and then analyse the impact on the balance sheet of a typical commercial bank, both in terms of value and sensitivity. Securitization is presented in this context as a way to monitor risk exposure. Finally the global impact of these embedded options in the French banking system is estimated and briefly discussed.     

尾部风险网络视角下的金融机构系统性风险贡献研究

金融机构的尾部风险关联模式及结构在金融系统性风险的形成演化中发挥重要作用。利用CoVaR指标及分位数回归方法,衡量金融机构之间的尾部风险传染强度,进而建立金融机构尾部风险动态网络。分析全连接网络及阈值法下过滤网络的全局和局部拓扑结构特征及其动态演化规律。建立面板数据回归模型,研究网络拓扑结构特征对金融机构系统性风险贡献的影响。实证研究发现,全连接网络的节点强度,能有效地衡量金融机构尾部风险传染强度及承受强度,并揭示其动态变化规律;各机构的尾部风险传染强度及承受强度排序匹配性存在差异;随着时间推进,各金融机构间的平均尾部风险传染路径缩短、系统性风险更易迅速累积和爆发;滞后一期的节点出度、节点入度及聚集系数越大,相应金融机构的系统性风险贡献越小;滞后一期的节点介数和节点接近中心度越大,相应金融机构的系统性风险贡献越大。研究结果对于金融机构的宏观审慎监管及系统性风险管理,提供了一个全新的基于金融机构尾部风险网络的视角。     

Default probabilities in a corporate bank portfolio: A logistic model approach

Analysis and management of credit risk has taken on an increased importance in recent years. New regulations force banks and other financial institutions to make a credible effort to chart and manage the risk associated with their client portfolio. Increased competition in the financial market has also improved the motivation of monitoring the risk/reward relationship on various clients. Modern risk measures such as Credit Risk Capital (CRC) and Risk Adjusted Return On Capital (RAROC) are now well established among banks. One problem in such risk frameworks is to find the expected loss (EL) of the bank portfolio. The EL is based on assumptions regarding the estimated default frequency (EDF) for each client or group of clients. Benchmark models for CRC calculations treat EDFs as exogenous and do not devote much attention to how they can be obtained. This article presents a method of estimating such rates for a retail bank portfolio. The analysis is based on a logistic regression model where financial variables as well as other firm characteristics affect the default probability.     

Integrated bank risk modeling: A bottom-up statistical framework

In the last few years, according to the evolution of financial markets and the enforcement of international supervisory requirements, an increasing interest has been devoted to risk integration. The original focus on individual risk estimation has been replaced by the growing prominence of top-down and bottom-up risk integration perspectives. Following this latter way, we bring together different approaches developed in the recent literature elaborating a general model to assess banking solvency in both the long-run (economic capital) as well as in the short period (liquidity mismatching). We consider banking capability to face credit, interest rate and liquidity risks associated to macro-economic shocks affecting both assets and liabilities. Following the perspective of commercial banks, we concentrate on information available in the risk management practice to propose an easy to implement statistical framework. We put in place this framework estimating its scenario generation parameters on Italian macro-economic time series from 1990 to 2009. Once applied to a stylized commercial bank, we compare the results of our approach to regulatory capital requirements. We emphasize the need for policy makers as well as risk managers, to take into account the entire balance sheet structure to assess banking solvency.     

复杂环境下银行业多指标风险评估方法及防控策略研究——基于中国省际面板数据的分析

在目前国内外复杂金融环境下,有效识别金融风险及其变化趋势有助于防范和化解金融危机,筑牢国家金融安全屏障。特别是在大数据金融蓬勃发展的背景下,应用数据信息监控金融风险的状况和趋势更具重要的现实意义。以下首先依托已有经验数据提出度量极大经验风险曲面和极小经验风险曲面的方法。其次,根据极大风险曲面提出计算决策单元综合风险指数的模型,以及相应的决策单元投影公式。同时,依据极小风险曲面估计决策单元风险降低的程度和策略。最后,应用这些方法分析了中国31个省区市2013~2017年银行业的风险状况,并提出了相应的改进策略。     

On the regulator–insurer interaction in a structural model

In this paper, we provide a new insight to the previous work of Briys and de Varenne [E. Briys, F. de Varenne, Life insurance in a contingent claim framework: Pricing and regulatory implications, Geneva Papers on Risk and Insurance Theory 19 (1) (1994) 53–72], Grosen and Jørgensen [A. Grosen, P.L. Jørgensen, Life insurance liabilities at market value: An analysis of insolvency risk, bonus policy, and regulatory intervention rules in a barrier option framework, Journal of Risk and Insurance 69 (1) (2002) 63–91] and Chen and Suchanecki [A. Chen, M. Suchanecki, Default risk, bankruptcy procedures and the market value of life insurance liabilities, Insurance: Mathematics and Economics 40 (2007) 231–255]. We show that the particular risk management strategy followed by the insurance company can significantly change the risk exposure of the company, and that it should thus be taken into account by regulators. We first study how the regulator establishes regulation intervention levels in order to control for instance the default probability of the insurance company. This part of the analysis is based on a constant volatility. Given that the insurance company is informed of regulatory rules, we study how results can be significantly different when the insurance company follows a risk management strategy with non-constant volatilities. We thus highlight some limits of the prior literature and believe that the risk management strategy of the company should be taken into account in the estimation of the risk exposure as well as in that of the market value of liabilities.     

Assessing the asymmetric effects on branch rivalry of Spanish financial sector restructuring

Spanish financial institutions have been heavily affected by the banking crisis that began in 2008. Many of them, especially Spanish savings banks (or Cajas), had to merge with other institutions or had to be rescued. We address the question of up to what point the nature of competition in this sector has changed as a result of the crisis. Although institutions compete in many ways, we concentrate on their presence in the main street through bank branches open to the public (i.e., retail banking competition). Our measure of inter-firm rivalry is based on a geographical proximity measure that we calculate for the years 2008 (before the crisis) and 2012 (the last available data set). The technical approach is based on multidimensional unfolding, a methodology which allows us to graphically represent the asymmetric nature of such rivalry. These maps visualise the salient aspects of the system during the two dates analysed, and can be understood without a detailed technical knowledge.

     

Networth exposure to interest rate risk: An empirical analysis of Indian commercial banks

In the Basel II era, management of interest rate risk in the banking book has become significant. In the first study of its kind, we develop a simulation based driver-driven approach to estimate the impact of interest rate volatility on the networth of Indian banks during the period 2002–2004. We derive the interest rates that drive changes in deposit and prime lending rates (PLR). Then we perform Monte Carlo simulation and multiple regressions, on these driver rates, to obtain simulated shocks to deposit rates and PLR. We use these simulated shocks to get the 99% worst EVE loss for the sample banks. These losses are much larger than what the existing literature suggests. This is because, apart from repricing risk, we are the first to find evidence of significant basis risk. Our results have important policy implications both for banks and regulators.     

An enhanced DEA model for decomposition of technical efficiency in banking

Past studies about the application of data envelopment analysis (DEA) to banking performance often follow the concept of technical efficiency (TE) and/or the productivity defined by the TE. In this paper, we propose an enhanced DEA model, based on a modification of the directional distance function by simultaneously but disproportionately seeking the maximum expansion of each desirable output and contraction of each undesirable output for efficiency measurement, which allows us to decompose the TE into operating efficiency (OPE) and risk management efficiency (RME). The OPE characterizes the ability of a bank to expand the room for profits through its regular business activities, while the RME describes a bank’s ability in risk management activities for sustaining operations. To illustrate the usefulness of the proposed model, a case study of Taiwan’s domestic commercial banks is presented. The major findings are that operating inefficiency is the main source of technical inefficiency, although banks with a higher OPE generally also have a higher RME. Banks subordinate to financial holding companies are more efficient in both OPE and RME than stand-alone banks.     

广义双曲线分布模型在我国证券市场风险度量中的应用研究

经济的全球化、衍生产品的大量出现以及因此导致的金融市场的动荡使得金融机构越来越需要更有效的风险管理方法。而如何精确度量风险是风险管理的关键问题。本文试图从金融收益分布假设着手改善风险度量的精度。国外学者研究发现广义双曲线分布比其它分布形式可以更好地拟合实际收益分布特征。本文首次把广义双曲线分布应用到VaR的分析方法中计算我国股票指数的VaR。实证结果表明，基于广义双曲线分布的方法得到了较好的预测结果。     

Bayesian kernel based classification for financial distress detection

Corporate credit granting is a key commercial activity of financial institutions nowadays. A critical first step in the credit granting process usually involves a careful financial analysis of the creditworthiness of the potential client. Wrong decisions result either in foregoing valuable clients or, more severely, in substantial capital losses if the client subsequently defaults. It is thus of crucial importance to develop models that estimate the probability of corporate bankruptcy with a high degree of accuracy. Many studies focused on the use of financial ratios in linear statistical models, such as linear discriminant analysis and logistic regression. However, the obtained error rates are often high. In this paper, Least Squares Support Vector Machine (LS-SVM) classifiers, also known as kernel Fisher discriminant analysis, are applied within the Bayesian evidence framework in order to automatically infer and analyze the creditworthiness of potential corporate clients. The inferred posterior class probabilities of bankruptcy are then used to analyze the sensitivity of the classifier output with respect to the given inputs and to assist in the credit assignment decision making process. The suggested nonlinear kernel based classifiers yield better performances than linear discriminant analysis and logistic regression when applied to a real-life data set concerning commercial credit granting to mid-cap Belgian and Dutch firms.     

微信社群互动行为对用户理财产品投资组合风险决策的影响

微信社群如何影响用户理财产品购买决策是当下金融产品营销的一个重要理论问题。本研究依据效价理论提出感知风险、感知收益与用户理财产品的投资组合风险决策的关系模型,并将用户的微信社群互动纳入模型。基于287个用户问卷数据,129个微信社群的互动行为数据,以及用户理财产品实际购买行为的数据分析,发现用户购买理财产品的投资组合风险决策受到其感知风险与感知收益的影响,而且微信社群的互动频率负向影响用户感知风险与用户投资组合风险决策之间的负向关系、微信社群的消极情绪会加强感知风险对用户投资组合风险决策的负向影响并削弱感知利益对于用户投资组合风险决策的正向影响。本研究扩展了有关用户理财产品决策影响因素的分析视角,并对理财产品的用户管理有借鉴价值。     

Structure and dynamics of the global financial network

In this paper, we study the evolution of the network topology for the global financial market. We evaluate the level of diversification and participation of developed and emerging economies in cross-border exposures and find that the gross exposure network is dense, the vulnerability matrix is sparse, and the network’s fragility changes over time. Prior to the financial crisis in 2008, the network was relatively fragile, whereas it became more resilient afterwards, showing a reduction in financial institutions’ risk appetite. Our results suggest that financial regulators should track down the network evolution in their systemic risk assessment.     

Optimal intervention under stress scenarios: A case of the Korean financial system

We consider optimal intervention methods under budget constraints when financial systems face economic shocks. We propose two policies formulated by mixed-integer linear programs where regulators inject cash into institutions. One is to minimize systemic losses, and the other is to minimize the number of defaulting institutions. Using publicly available data on the Korean financial system, we construct its entire network and apply stress scenarios to the system to compare the performances of intervention strategies and derive insights on their workings.     

The efficiency effects of a single market for financial services in Europe

This paper examines the potential efficiency effects of a single market for financial services in Europe. The topics covered include universal banking, the merger and acquisition process itself, cross-border ownership and management of financial institutions, and the effects of consolidation of financial institutions on the supply of relationship lending services to informationally opaque small businesses. The research reviewed here suggests that the creation of a single market for the European financial services industry is not likely to bring about strong efficiency gains and that cross-border efficiency barriers may prevent the single market from becoming a reality.     

Financial contagion: extending the exposures network of the Mexican financial system

Direct contagion has been widely studied in recent years and little evidence has been found to be relevant to the study of systemic risk. However, we argue that this limited contagion effect might be associated with a lack of relevant data. A common assumption for the estimation of the matrices of exposures is to apply the maximum entropy principle to deal with data gaps; such an assumption might lead to an underestimation of contagion risk. In this paper, there are no data gaps and the information set is extended from interbank exposures alone to exposures among most of the financial intermediaries in the Mexican financial system (we even include exposures to some international foreign banks). Naturally, the contagion risk of an extended network of exposures changes with respect to the interbank exposures network, as there are many more institutions which can be the source of contagion and there are more institutions which can fail due to contagion. The most important contribution of this paper is that it provides evidence on financial contagion with an extended exposures network under stressful conditions. The results presented here support the international efforts by the Bank for International Settlements, the International Monetary Fund and the Financial Stability Board to increase the amount of information available which can be used to assess systemic risk and contagion based on exposures and funding data.     

基于合作博弈的移动支付商业模式动态联盟企业利益分配研究

移动支付是近年来的热门发展方向,但是目前我国还没有形成统一的移动支付商业模式,已有研究没有量化各参与主体的价值贡献,导致利益分配产生冲突。针对这一问题,采用合作博弈理论系统分析通信运营商、金融机构、第三方支付平台在移动支付商业模式中的价值贡献,在基于Shapley值法量化的基础上引入资源投入、风险分担、创新能力三要素进行改进,计算得到各参与主体在合作联盟中的综合量化值。研究结果表明,将改进的Shapley值法应用于移动支付商业模式利益分配研究更能体现公平性和科学性,为解决各参与主体合作冲突、构建协同创新与利益共享的移动支付商业模式提供理论借鉴与参考。     

An integrated pricing model for defaultable loans and bonds

In recent years, credit risk has played a key role in risk management issues. Practitioners, academics and regulators have been fully involved in the process of developing, studying and analysing credit risk models in order to find the elements which characterize a sound risk management system. In this paper we present an integrated model, based on a reduced pricing approach, for market and credit risk. Its main features are those of being mark to market and that the spread term structure by rating class is contingent on the seniority of debt within an arbitrage-free framework. We introduce issues such as, the integration of market and credit risk, the use of stochastic recovery rates and recovery by seniority. Moreover, we will characterize default risk by estimating migration risk through a “mortality rate”, actuarial-based, approach. The resultant probabilities will be the base for determining multi-period risk-neutral transition probability that allow pricing of risky debt in the trading and banking book.     

Heterogeneous trading agents

In this article, we present a multiagent system (MAS) simulation of a financial market and investigate the requirements to obtain realistic data. The model consists of autonomous, interactive agents that buy stock on a financial market. Transaction decisions are based on a number of individual and collective elements, the former being risk aversion and a set of decision rules reflecting their anticipation of the future evolution of prices and dividends and the latter the information arriving on the market influencing the decision making process of each trader. We specifically look at this process and the following observations hold: The market behavior is determined by the information arriving at the market and agent heterogeneity is required in order to obtain the right statistical properties of the price and return time series. The observed results are not sensitive to changes in the parameter values. © 2003 Wiley Periodicals, Inc.