An optimal investment strategy in bank management

This paper considers the application of stochastic optimization theory to asset and capital adequacy management in banking. The Basel II Capital Accord lays down regulations to control bank behaviour, and relies on regulatory ratios such as the capital adequacy ratio (CAR). In an attempt to address the problem of compliance to minimum CAR and under assumptions about retained earnings, loan‐loss reserves, the market and shareholder‐bank owner relationships, we construct a continuous‐time model of the Basel II CAR which is computed from the total risk‐weighted assets (TRWAs) and bank capital in a stochastic setting. In particular, we derive an optimal equity allocation strategy for the bank and monitor the performance of the Basel II CAR under the allocation strategy. Copyright © 2011 John Wiley & Sons, Ltd.     

Continuous‐time stochastic modelling of capital adequacy ratios for banks

Regulation related to capital requirements is an important issue in the banking sector. In this regard, one of the indices used to measure how susceptible a bank is to failure, is the capital adequacy ratio (CAR). We consider two types of such ratios, viz. non‐risk‐based (NRBCARs) and risk‐based (RBCARs) CARs. According to the US Federal Deposit Insurance Corporation (FDIC), we can further categorize NRBCARs into leverage and equity capital ratios and RBCARs into Basel II and Tier 1 ratios. In general, these indices are calculated by dividing a measure of bank capital by an indicator of the level of bank risk. Our primary objective is to construct continuous‐time stochastic models for the dynamics of each of the aforementioned ratios with the main achievement being the modelling of the Basel II capital adequacy ratio (Basel II CAR). This ratio is obtained by dividing the bank's eligible regulatory capital (ERC) by its risk‐weighted assets (RWAs) from credit, market and operational risk. Mainly, our discussions conform to the qualitative and quantitative standards prescribed by the Basel II Capital Accord. Also, we find that our models are consistent with data from FDIC‐insured institutions. Finally, we demonstrate how our main results may be applied in the banking sector. Copyright © 2005 John Wiley & Sons, Ltd.     

中国银行系统的宏观审慎监管研究

全球金融危机爆发后,对银行系统实行审慎监管已成为国内外学者及相关监管机构的共识。但目前银行系统的监管研究多为微观审慎监管,宏观审慎监管研究缺乏,尤其是对中国银行网络系统进行动态建模并进行宏观审慎监管的定量研究未见。本文首先利用中国2008至2015年16家上市银行的实际数据构建动态的中国银行网络系统模型,然后使用Component VaR、Incremental VaR、Shapley value EL以及ΔCoVaR四种风险分配机制研究中国银行网络系统的宏观审慎监管方法。研究表明:对中国银行网络系统进行宏观审慎监管能够有效提升其稳定性,并且四种机制相比之下,ΔCoVaR的监管效果最为显著,而Incremental VaR则相对较差。此外,通过宏观审慎资本与银行指标之间的相关性分析,发现Incremental VaR、Shapley value EL以及Component VaR机制下的宏观审慎资本与银行的总资产具有一定的相关性,此时宏观审慎资本可以根据银行的总资产来设置;而ΔCoVaR机制下则不相关,因此宏观审慎资本可以依据各银行的系统性风险贡献大小来设置。     

Capital adequacy and risk management in banking industry

The present paper deals with the issue of bank capital adequacy and risk management within a stochastic dynamic setting. In particular, an explicit risk aggregation and capital expression is provided regarding the portfolio choice and capital requirements special context. Such a framework leads to a nonlinear stochastic optimal control problem whose solution may be determined by means of dynamic programming algorithm. The pertaining analysis relies heavily on the stochastic dynamic modeling of such balance sheet items as securities, loans, and regulatory capital with stochastic interest rates. In this respect, the special Kalman filter approach is used for the purpose of estimating the model parameters. The reached findings reveal well that the Tunisian bank, subject of study, generally exceeds the minimum requirements and is adequately capitalized to maintain the appropriate capital amount level commensurate with the aggregate risk. Besides, empirical evidence on the regulations' impact on driving bank capitalization and risk‐taking behavior has also been highlighted. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Estimation error in regulatory capital requirements: theoretical implications for consumer bank profitability

Despite the topic's societal importance and despite progress in bank research, a lack of consensus exists concerning either the desirability of bank regulation or its optimal design. Enforcement of minimum bank capital standards has been shown to enhance bank stability, but also serves as a potential source of incremental costs, some of which are subtle. Such widely ambiguous research results point to the need for theoretical research regarding capital regulation across diverse banking systems. Along the latter lines, consumer bank issues have been generally neglected. This paper theoretically examines the performance implications of misestimating the regulatory capital requirement for a stylised consumer bank. For our stylised consumer bank, we prove that misestimation, irrespective of its direction, results in lower economic profits and, hence, value. Conclusions and implications for future work are drawn.     

基于随机久期利率免疫的银行资产负债优化模型

银行资产负债管理是指商业银行在负债数量和结构一定的条件下、对资产进行优化配置,通过平衡资产的流动性、盈利性和安全性,以实现银行收益的最大化。本文通过Vasicek动态期限结构模型推导出随机久期,以包括存量与增量在内的全部资产随机久期等于全部负债随机久期为约束条件、控制利率风险,辅以现行法律法规等其他约束条件,建立全部资产负债组合的随机久期利率风险免疫模型,并通过算例说明本模型构建过程。本文的创新与特色有三:一是通过建立全部资产负债组合的利率免疫条件,对包括存量与增量在内的全部资产组合利率风险进行控制。改变了现有研究在进行资产配置时,仅对增量组合风险控制的弊端。二是通过资产负债的随机久期缺口等于0的利率风险免疫条件建立资产负债优化模型,确保在利率发生变化时,银行股东的所有者权益不受损失。三是以银行各项资产组合收益率最大化为目标函数,通过随机久期的利率免疫条件控制利率风险,建立了全部资产负债组合的随机久期利率风险免疫模型。改变了现有研究的资产负债管理模型忽略随机久期变动的影响。     

基于动态利率风险免疫的银行资产负债优化模型

本文以CIR动态久期缺口的免疫条件为约束进行多资产和多负债的利率风险控制,通过建立线性规划模型来进行银行资产的最优配置。本文的创新与特色:一是通过引进随时间变化的动态利率久期参数构造利率风险控制条件,建立了控制利率风险的资产负债优化模型。改变了现有研究忽略利率动态变化、进而忽略平均久期动态变化的弊端。事实上,利率的动态变化必然引起平均久期的变动,忽略利率变动的控制条件是无法高精度地控制资产配置的利率风险的。二是通过以银行资产收益最大为目标函数,以动态利率久期缺口免疫为主要约束条件,辅以监管的流动性约束匹配银行的资产负债,回避了利率风险对银行所有者权益的影响,避免了利率变动对银行资产所有者带来的损害。     

存款保险费率的敏感性分析及实证检验

资本充足率、存款保险费率是发达国家普遍采用的维持银行稳定的基本措施,一般来说资本充足率越高,则所需的存款保险费率越低,银行为减小成本,都希望在合理控制风险的前提下减少所缴纳的存款保险.本文使用根据期权思想建立的存款保险定价模型,推导了存款保险费率对资本充足率的敏感性系数;其次根据中国上市银行的数据进行测算,分别计算了14家银行每增加一个单位的资本充足率可降低存款保险费率的数额,并对实证的结果进行比较;最后给出相关结论.     

Optimal allocation between bank loans and treasuries with regret

The main categories of assets held by banks are loans, Treasuries (bonds issued by the national Treasury), reserves and intangible assets. In our contribution, we investigate the investment of bank funds in loans and Treasuries with the aim of generating an optimal final fund level. Our results take behavioral aspects such as risk and regret into account. More specifically, we apply a branch of optimization theory that enables us to consider a regret attribute alongside a risk component as an integral part of the utility function. In this case, regret-aversion corresponds to the convexity of the regret function and the bank’s preference is assumed to be representable by optimization subject to the utility. In addition, we provide a comparison between risk- and regret-averse banks in terms of optimal asset allocation between loans and Treasuries. A feature of our contribution is that these and other optimization issues are analyzed briefly and, where possible, represented graphically. Furthermore, we comment on the claim that an investment away from loans towards Treasuries is responsible for credit crunches in the banking industry.     

The optimal operational risk capital requirement by applying the advanced measurement approach

The purpose of this paper is to construct a risk quantification model to achieve the accurate operational risk management and gain the satisfying estimation and control of future possible extreme losses by using capital charges to assess operational risk. The paper takes a case bank as the research object and compares the differences under various circumstances engaging the Basic Indicator Approach, the Standardized Approach, and the Advanced Measurement Approach for the operational risk capital requirement of a bank. The results indicate that it is more appropriate to adopt the Advanced Measurement Approach to estimate the operational risk capital requirement; this way can help a bank enjoy a much lessened capital charge required and subsequently its available capital increases. Hence, it allows a bank to have sufficient funds in operations and reduce the burden of capital costs. Therefore, it will bring the positive benefits to the whole banking industry when enforcing the Advanced Measurement Approach.     

Precautionary measures for credit risk management in jump models

Sustaining efficiency and stability by properly controlling the equity to asset ratio is one of the most important and difficult challenges in bank management. Due to unexpected and abrupt decline of asset values, a bank must closely monitor its net worth as well as market conditions, and one of its important concerns is when to raise more capital so as not to violate capital adequacy requirements. In this paper, we model the trade-off between avoiding costs of delay and premature capital raising, and solve the corresponding optimal stopping problem. In order to model defaults in a bank's loan/credit business portfolios, we represent its net worth by Lévy processes, and solve explicitly for the double exponential jump-diffusion process and for a general spectrally negative Lévy process.     

A multiperiod model for estimating the cost of deposit insurance under the Basel III minimum capital requirement

Under the Basel III regime, a commercial bank is considered adequately capitalized if it maintains a ratio of capital to total risk-weighted assets or capital adequacy ratio (CAR) of at least 8%. We model a commercial bank that complies with Basel III's minimum capital requirement on an interval $[0,T]$ for $T>0$. The bank model is achieved via a specific rate of capital influx that fixes the bank's CAR at the minimum prescribed level of 8%. On the basis of this capital influx rate, we derive models for the bank's asset portfolio and capital dynamics required for maintaining the CAR at the minimum prescribed level. For the aforementioned bank, we further study a deposit insurance (DI) pricing problem with a coverage horizon equal to $T$ years. More specifically, we employ a multiperiod DI pricing model to approximate the cost of DI for the bank on the interval $[0,T]$, where the constant (minimum) CAR is maintained. We study the behaviours of the models leading to the constant (minimum) CAR, and the behaviour of the DI premium estimate by means of numerical simulations. In the simulation study pertaining to the DI premium estimate specifically, we determine the effects of changes in the bank's initial leverage level (deposit-to-asset ratio), the DI coverage horizon, and the volatility of the asset portfolio on the DI premium estimate.     

基于流动性风险约束的我国商业银行资产负债随机规划模型

通过以资产负债管理合理匹配银行资产、负债,可以防范银行流动性风险.为此,建立了一个带有简单补偿的两阶段多期随机规划,在满足相关政策、法规约束和流动性风险V aR随机机会约束条件下,以银行的盈利最大化为目标,对银行主要资产、负债进行动态的优化匹配.     

A dynamic bank portfolio planning model with multiple scenarios,multiple goals and changing priorities

The paper discusses a practical application of a two-stage linear goal programming model to the management of the domestic and foreign currency denominated assets and liabilities of a large bank in Finland. The planning horizon includes three one-year planning periods. A number of alternative scenarios are used to describe uncertainty concerning future developments in these periods. The scenarios are related to general economic conditions as well as the state of the domestic and foreign financial markets. The bank is assumed to have multiple conflicting goals with different and changing priorities. The goals deal with expected profits, risk, liquidity, capital adequacy, growth, customer relationships and several other aspects of the bank's operations.     

Stochastic equity volatility related to the leverage effect II: valuation of European equity options and warrants

We propose a general framework to assess the value of the financial claims issued by the firm, European equity options and warrantsin terms of the stock price. In our framework, the firm's asset is assumed to follow a standard stationary lognormal process with constant volatility. However, it is not the case for equity volatility. The stochastic nature of equity volatility is endogenous, and comes from the impact of a change in the value of the firm's assets on the financial leverage. In a previous paper we studied the stochastic process for equity volatility, and proposed analytic approximations for different capital structures. In this companion paper we derive analytic approximations for the value of European equity options and warrants for a firm financed by equity, debt and warrants. We first present the basic model, which is an extension of the Black-Scholes model, to value corporate securities either as a function of the stock price, or as a function of the firm's total assets. Since stock prices are observable, then for practical purposes, traders prefer to use the stock as the underlying instrument, we concentrate on valuation models in terms of the stock price. Second, we derive an exact solution for the valuation in terms of the stock price of (i) a European call option on the stock of a levered firm, i.e. a European compound call option on the total assets of the firm, (ii) an equity warrant for an all-equity firm, and (iii) an equity warrant for a firm financed by equity and debt. Unfortunately, to compute these solutions we need to specify the function of the stock price in terms of the firm's assets value. In general we are unable to specify this expression, but we propose tight bounds for the value of these options which can be easily computed as a function of the stock price. Our results provide useful extensions of the Black-Scholes model.     

Modeling company failure: a longitudinal study of Turkish banks

Determining the factors related to the financial failure of a company is important. In this paper, we extend literature on bank failure prediction by modelling bank failures in Turkey from 1998 to 2000 using three statistical models combined with a principal component analysis on financial ratios. The three statistical models employed are a logistic regression, a logistic regression that takes serial correlation into account via generalized estimating equations and a marginalized transition model (MTM). Time and financial ratios that are related with capital adequacy and profitability, risk, non-interest income and Fx assets to Fx liabilities are found to be significant in classifying failed banks. Each of our methods achieves a correct classification rate of 93.3%. Among the three models, MTM, which is the soundest model in terms of statistical assumptions, shows slightly better model fit properties.     

Optimal Liquidity management and Hedging in the presence of a non-predictable investment opportunity

In this paper, we develop a dynamic model that captures the interaction between a firm’s cash reserves, the risk management policy and the profitability of a non-predictable irreversible investment opportunity. We consider a firm that has assets in place generating a stochastic cash-flow stream. The firm has a non-predictable growth opportunity to expand its operation size by paying a sunk cost. When the opportunity is available, the firm can finance it either by cash or by costly equity issuance. We provide an explicit characterization of the firm strategy in terms of investment, hedging, equity issuance and dividend distribution.     

An optimal investment strategy for a stream of liabilities generated by a step process in a financial market driven by a Lévy process

In this paper we investigate an asset–liability management problem for a stream of liabilities written on liquid traded assets and non-traded sources of risk. We assume that the financial market consists of a risk-free asset and a risky asset which follows a geometric Lévy process. The non-tradeable factor (insurance risk or default risk) is driven by a step process with a stochastic intensity. Our framework allows us to consider financial risk, systematic and unsystematic insurance loss risk (including longevity risk), together with possible dependencies between them. An optimal investment strategy is derived by solving a quadratic optimization problem with a terminal objective and a running cost penalizing deviations of the insurer’s wealth from a specified profit-solvency target. Techniques of backward stochastic differential equations and the weak property of predictable representation are applied to obtain the optimal asset allocation.     

An optimal investment strategy for a stream of liabilities generated by a step process in a financial market driven by a Lévy process

In this paper we investigate an asset-liability management problem for a stream of liabilities written on liquid traded assets and non-traded sources of risk. We assume that the financial market consists of a risk-free asset and a risky asset which follows a geometric Lévy process. The non-tradeable factor (insurance risk or default risk) is driven by a step process with a stochastic intensity. Our framework allows us to consider financial risk, systematic and unsystematic insurance loss risk (including longevity risk), together with possible dependencies between them. An optimal investment strategy is derived by solving a quadratic optimization problem with a terminal objective and a running cost penalizing deviations of the insurer’s wealth from a specified profit-solvency target. Techniques of backward stochastic differential equations and the weak property of predictable representation are applied to obtain the optimal asset allocation.