中国商业银行内部欺诈风险度量研究

作为巴塞尔新资本协议规定的七种操作风险损失类型之一,内部欺诈问题是中国商业银行的一个重大风险来源。以部分国内商业银行内部欺诈数据为样本,针对内部欺诈具有的低频率高损失的特点,借助广义Pareto分布（GPD）和对数正态分布对内部欺诈建立了一个风险度量模型,然后通过对尾部分布何时服从GPD进行检验,得到了精确的门限值,最后利用所建立的分布模型对内部欺诈类操作风险在险风险值、经济资本和最大可能损失进行了估计,说明了中国商业银行防范内部欺诈风险的重要性。     

Optimal investment and life insurance strategies in a mixed jump-diffusion framework

Abstract

This article investigates an optimal investment and life insurance strategies in a mixed jump-diffusion framework. The individual life insurance policyholder who has CRRA preferences. The market consists of riskless asset, a zero-coupon bond, a stock and life insurance. The instantaneous interest rate is modeled as the O-U model, while a zero-coupon bond with credit risk follows a BSDE and a risky asset be driven by MJD-fBm model. The problem is solved by the mixed jump diffusion fractional HJB SDE which satisfied the admissible strategy, then the closed form solution and optimal strategies are derived and the simulation of the various parameters are also given.     

基于风险调整的运营效率研究——以台湾银行业为例

针对金融机构风险容忍度的关键指标:资本、获利、财务弹性、银行特许价值,以及《巴塞尔资本协议》III关注的表外资产与金融衍生品隐含嵌入杠杆,作为风险调整的投入和产出,构建台湾金控集团下属银行的效率评估体系。结果表明:第一,银行效率排名有强者恒强趋势,在拟定具有稳定性与一贯性的风险容忍度后,除了形成银行特有的风险文化与经营特色外,还能够维持稳定绩效,对于市场品牌价值将有显著的提升;第二,风险调整后的效率与监管指标相关程度较高,表示考虑风险后的运营更容易满足监管者管控要求;第三,低流动性风险(低贷存比)风险管理优势带来较高的风险调整后效率,然而贷款普遍存在流动性差的特征,银行应加强优质合格存款与资产的流动性管理,避免过度依靠贷款(高贷存比)而降低自身经营效率;最后,台湾利率市场化造成利差逐渐缩小,较快的放款增速却无法提高风险调整后的效率,资产管理与财务管理等中间业务收入将是台湾银行结构转型的重点业务。     

Robust optimal investment and proportional reinsurance toward joint interests of the insurer and the reinsurer

In this article, we study a robust optimal investment and reinsurance problem for a general insurance company which holds shares of an insurance company and a reinsurance company. Assume that the claim process described by a Brownian motion with drift, the insurer can purchase proportional reinsurance, and both the insurer and the reinsurer can invest in a risk-free asset and a risky asset. Besides, the general insurance company’s manager is an ambiguity-averse manager (AAM) who worries about model uncertainty in model parameters. The AAM’s objective is to maximize the minimal expected exponential utility of the weighted sum surplus process of the insurer and the reinsurer. By using techniques of stochastic control theory, we first derive the closed-form expressions of the optimal strategies and the corresponding value function, and then the verification theorem is given. Finally, we present numerical examples to illustrate the effects of model parameters on the optimal investment and reinsurance strategies, and analyze utility losses from ignoring model uncertainty.     

The entropic measure transform

We introduce the entropic measure transform (EMT) problem for a general process and prove the existence of a unique optimal measure characterizing the solution. The density process of the optimal measure is characterized using a semimartingale BSDE under general conditions. The EMT is used to reinterpret the conditional entropic risk-measure and to obtain a convenient formula for the conditional expectation of a process that admits an affine representation under a related measure. The EMT is then used to provide a new characterization of defaultable bond prices, forward prices and futures prices when a jump-diffusion drives the asset. The characterization of these pricing problems in terms of the EMT provides economic interpretations as maximizing the returns subject to a penalty for removing financial risk as expressed through the aggregate relative entropy. The EMT is shown to extend the optimal stochastic control characterization of default-free bond prices of Gombani & Runggaldier (2013). These methods are illustrated numerically with an example in the defaultable bond setting. The Canadian Journal of Statistics 48: 97–129; 2020 © 2020 Statistical Society of Canada     

A kind of stochastic recursive Zero-Sum differential game problem with double obstacles constraint

Abstract

This paper concerns a class of stochastic recursive zero-sum differential game problem with recursive utility related to a backward stochastic differential equation (BSDE) with double obstacles. A sufficient condition is provided to obtain the saddle-point strategy under some assumptions. In virtue of the corresponding relationship of doubly reflected BSDE and mixed game problem, a stochastic linear recursive mixed differential game problem is studied to apply our theoretical result, and here the explicit saddle-point strategy as well as the saddle-point stopping time for the mixed game problem are obtained. Besides, a numeral example is also given to demonstrate the result by virtue of partial differential equations (PDEs) computation method.     

Asset Prices Under Habit Formation and Reference-Dependent Preferences

This article explains the high level and the countercyclical variation of the equity premium in a consumption-based asset pricing model with low large-scale risk aversion. Investors have gain-loss utility over consumption relative to slowly time-varying habit. Stocks deliver low returns in recessions when consumption falls below habit; investors therefore require a high premium for holding stocks. The model's conditional moment restrictions are tested on consumption and asset returns data. The empirical estimate of large-scale risk aversion is low, whereas the estimate of loss aversion agrees with prior experimental evidence.     

资本监管约束下银行行为调整的动态特征分析

本文考虑巴塞尔协议Ⅲ对银行行为调整的影响,选用国内40家资本充足率达标的商业银行作为研究样本,以2007—2015年为样本期,建立联立方程组检验资本监管硬约束对银行资本、风险和绩效调整的短期效果。实证结果表明：资本监管要求的提高未能降低银行的实际风险,当面对资本监管压力时银行的主要应对策略是增加资本而非降低资产风险,资本充足的银行有更强的风险承担激励。超额贷款损失准备记入二级资本导致资本充足率和核心资本充足率表现出不同的调整特征。经济下行期货币政策的逆周期调控有助于银行通过增加“分母”平缓信贷风险的顺周期波动,但同时也增加了银行资本调整的难度。     

Optimal investment-consumption-insurance strategy in a continuous-time self-exciting threshold model

In this paper, we consider an optimal investment-consumption-insurance purchase problem for a wage earner. We assume that the price of the risky asset is governed by a continuous-time, finite state self-exciting threshold model. In this model, the state space of the price of the risky asset is partitioned by a set of thresholds and the parameters depend on the region which the current value of the price falls in. The wage earner’s objective is to find the optimal investment-consumption-insurance strategy that maximizes the expected discounted utilities. The optimal strategy for power utility function is derived by the martingale approach and the dynamic programming approach. Numerical examples are also provided to illustrate the effect of the thresholds.     

Optimal asset allocation for participating contracts with mortality risk under minimum guarantee

Abstract

We investigate an optimal investment problem of participating insurance contracts with mortality risk under minimum guarantee. The insurer aims to maximize the expected utility of the terminal payoff. Due to its piecewise payoff structure, this optimization problem is a non-concave utility maximization problem. We adopt a concavification technique and a Lagrange dual method to solve the problem and derive the representations of the optimal wealth process and trading strategies. We also carry out some numerical analysis to show how the portfolio insurance constraint impacts the optimal terminal wealth.     

Maximum likelihood estimation for generalized conditionally autoregressive models of spatial data

Conditionally autoregressive (CAR) models are often used to analyze a spatial process observed over a lattice or a set of irregular regions. The neighborhoods within a CAR model are generally formed deterministically using the inter-distances or boundaries between the regions. To accommodate directional and inherent anisotropy variation, a new class of spatial models is proposed that adaptively determines neighbors based on a bivariate kernel using the distances and angles between the centroid of the regions. The newly proposed model generalizes the usual CAR model in a sense of accounting for adaptively determined weights. Maximum likelihood estimators are derived and simulation studies are presented for the sampling properties of the estimates on the new model, which is compared to the CAR model. Finally the method is illustrated using a data set on the elevated blood lead levels of children under the age of 72 months observed in Virginia in the year of 2000.     

Practical implications of higher moments in risk management

In this paper the out-of-sample prediction of Value-at-Risk by means of models accounting for higher moments is studied. We consider models differing in terms of skewness and kurtosis and, in particular, the GARCHDSK model, which allows for constant and dynamic skewness and kurtosis. The issue of VaR prediction performance is approached first from a purely statistical viewpoint, studying the properties concerning correct coverage rates and independence of VaR violations. Then, financial implications of different VaR models, in terms of market risk capital requirements, as defined by the Basel Accord, are considered. Our results, based on the analysis of eight international stock indexes, highlight the presence of conditional skewness and kurtosis, in some case time-varying, and point out that asymmetry plays a significant role in risk management.     

Mean-variance problem for an insurer with default risk under a jump-diffusion risk model

Abstract

This paper considers an optimal investment-reinsurance problem with default risk under the mean-variance criterion. We assume that the insurer is allowed to purchase proportional reinsurance and invest his/her surplus in a risk-free asset, a stock and a defaultable bond. The goal is to maximize the expectation and minimize the variance of the terminal wealth. We first formulate the problem to stochastic linear-quadratic (LQ) control problem with constraints. Then the optimal investment-reinsurance strategies and the corresponding value functions are obtained via the viscosity solutions of Hamilton-Jacobi-Bellman (HJB) equations for the post-default case and pre-default case, respectively. Finally, we provide numerical examples to illustrate the effects of model parameters on the optimal strategies and value functions.     

Maximum likelihood estimation for directional conditionally autoregressive models

A spatial process observed over a lattice or a set of irregular regions is usually modeled using a conditionally autoregressive (CAR) model. The neighborhoods within a CAR model are generally formed using only the inter-distances or boundaries between the regions. To accommodate directional spatial variation, a new class of spatial models is proposed using different weights given to neighbors in different directions. The proposed model generalizes the usual CAR model by accounting for spatial anisotropy. Maximum likelihood estimators are derived and shown to be consistent under some regularity conditions. Simulation studies are presented to evaluate the finite sample performance of the new model as compared to the CAR model. Finally, the method is illustrated using a data set on the crime rates of Columbus, OH and on the elevated blood lead levels of children under the age of 72 months observed in Virginia in the year of 2000.     

Minimum Risk Invariant Estimators of a Continuous Cumulative Distribution Function

The problem of nonparametric minimum risk invariant estimation has engaged a good deal of attention in the literature and minimum risk invariant estimators (MRIE's) have been constructed for some special statistical models. We present a new and simple method of obtaining the MRIE's of a continuous cumulative distribution function (cdf) under a general invariant loss function. All the MRIE's, which are known from the literature, can be constructed by the method presented in the article, in particular, under the weighted quadratic, LINEX and entropy loss functions. This method enables also to construct the MRIE's in nonparametric statistical models which have not been considered until now. In particular, considering a family of nonparametric precautionary loss functions, a new class of MRIE's of the cdf has been found. We also give some general remarks on obtaining the MRIE's and a review concerning minimaxity and admissibility of MRIE's.     

Robust portfolio choice for a defined contribution pension plan with stochastic income and interest rate

This paper considers a robust portfolio choice problem for a defined contribution pension plan with stochastic income and stochastic interest rate. The investment objective of the pension plan is to maximize the expected utility of the wealth at the retirement time. We assume that the financial market consists of a stock, a zero-coupon bond and a risk-free asset. And the member of defined contribution pension plan is ambiguity-averse, which means that the member is uncertain about the expected return rate of the bond and stock. Meanwhile, the member's ambiguity-aversion level toward these two financial assets is quite different. The closed-form expressions of the robust optimal investment strategy and the corresponding value function are derived by adopting the stochastic dynamic programming approach. Furthermore, the sensitive analysis of model parameters on the optimal investment strategy are presented. We find that the member's aversion on model ambiguity increases her hedging demand and has remarkable impact on the optimal investment strategy. Moreover, we demonstrate that ignoring model uncertainty will lead to significant utility loss for the ambiguity-averse member, and the model uncertainty about the stock dynamics implies greater effect on the outcome of the investment than the bond.     

The geography of Spanish bank branches

This article analyzes the determinants of bank branch location in Spain taking the role of geography explicitly into account. After a long period of intense territorial expansion, especially by savings banks, many of these firms are now involved in merger processes triggered off by the financial crisis, most of which entail the closing of many branches. However, given the contributions of this type of banks to limit financial exclusion, this process might exacerbate the consequences of the crisis for some disadvantaged social groups. Related problems such as new banking regulation initiatives (Basel III), or the current excess capacity in the sector add further relevance to this problem. We address this issue from a Bayesian perspective, using a Poisson regression model within the framework of generalized linear mixed models. This proposal allows us to assess whether over-branching or under-branching has taken place. Our results suggest, among other findings, that both phenomena are present in the Spanish banking sector, although the implications for the three types of banks in the industry, namely commercial banks, savings banks or credit unions, vary a great deal.     

Assessing the discriminatory power of loss given default models

For banks using the Advanced Internal Ratings-Based Approach in accordance with Basel III requirements, the amount of required regulatory capital relies on the banks'' estimates of the probability of default, the loss given default and the conversion factor for their credit risk portfolio. Therefore, for both model development and validation, assessing the models'' predictive and discriminatory abilities is of key importance in order to ensure an adequate quantification of risk. This paper compares different measures of discriminatory power suitable for multi-class target variables such as in loss given default (LGD) models, which are currently used among banks and supervisory authorities. This analysis highlights the disadvantages of using measures that solely rely on pairwise comparisons when applied in a multi-class setting. Thus, for multi-class classification problems, we suggest using a generalisation of the well-known area under the receiver operating characteristic (ROC) curve known as the volume under the ROC surface (VUS). Furthermore, we present the R-package VUROCS, which allows for a time-efficient computation of the VUS as well as associated (co)variance estimates and illustrate its usage based on real-world loss data and validation principles.     

Optimal investment strategy for a DC pension plan with mispricing under the Heston model

Abstract

In this article, we consider the optimal investment problem for a defined contribution (DC) pension plan with mispricing. We assume that the pension funds are allowed to invest in a risk-free asset, a market index, and a risky asset with mispricing, i.e. the prices are inconsistent in different financial markets. Assuming that the price process of the risky asset follows the Heston model, the manager of the pension fund aims to maximize the expected utility for the power utility function of terminal wealth. By applying stochastic control theory, we establish the corresponding Hamilton-Jacobi-Bellman (HJB) equation. And the optimal investment strategy is obtained for the power utility function explicitly. Finally, numerical examples are provided to analyze effects of parameters on the optimal strategy.     

Risk minimization for an insurer with investment and reinsurance via g-expectation

Abstract

This paper is devoted to the study of a risk-based optimal investment and proportional reinsurance problem. The surplus process of the insurer and the risky asset process in the financial market are assumed to be general jump-diffusion processes. We use a convex risk measure generated by g-expectation to describe the risk of the terminal wealth with investment and reinsurance. Under the aim of minimizing the risk, the problem is solved by using techniques of stochastic maximum principles. Two interesting special cases are studied and the explicit expressions for optimal strategies and corresponding minimal risks are derived.