联贷联保信用风险集中度定量分析北大核心CSCD

利用约化方法实现贷款组合渐进单因子模型,得到渐进单因子约化模型.为刻画联贷联保业务中联保体内的违约传染,又构建渐进单因子传染模型,使联保体内的违约相关由因子依赖和交叉强度共同体现,联保体间的违约相关只由因子依赖体现.通过模型求解得到联贷联保组合以及对比组合的违约概率,预期损失,非预期损失和集中度调整.数值分析比较了不同市场环境下联贷联保的风险,并据此建议商业银行限制担保链条长度和担保体内放贷额度,增加联保体数量,缩短贷款期限,在市场恶化时慎用联贷联保.     

Quantitative analysis of concentration risk of joint loan business

利用约化方法实现贷款组合渐进单因子模型,得到渐进单因子约化模型.为刻画联贷联保业务中联保体内的违约传染,又构建渐进单因子传染模型,使联保体内的违约相关由因子依赖和交叉强度共同体现,联保体间的违约相关只由因子依赖体现.通过模型求解得到联贷联保组合以及对比组合的违约概率,预期损失,非预期损失和集中度调整.数值分析比较了不同市场环境下联贷联保的风险,并据此建议商业银行限制担保链条长度和担保体内放贷额度,增加联保体数量,缩短贷款期限,在市场恶化时慎用联贷联保.     

基于动态损失厌恶投资组合优化模型及实证研究

为了研究行为金融学中损失厌恶的心理特征对投资决策的影响,建立预期效用最大化的动态损失厌恶投资组合优化模型。以我国股票市场为依托进行实证研究,将市场分为上升、下降和盘整三种状态,研究动态损失厌恶投资组合模型的表现,与静态损失厌恶投资组合模型、均值-方差投资组合模型和CVaR投资组合模型进行比较。通过改变参照点对动态模型进行稳健性检验。得出动态损失厌恶投资组合模型优于静态模型、均值-方差投资组合模型和CVaR投资组合模型的结论。     

贷款组合的“均值-方差-偏度”三因素优化模型

以银行各项资产组合收益率最大化为目标函数,以收益率偏度大于零控制银行重大损失发生的概率,以组合风险价值VaR风险限额为约束条件控制资产组合风险的大小,建立了贷款组合的"均值-方差-偏度"三因素优化模型.本模型的创新与特色一是通过偏度约束减少了组合收益率小于其均值的可能性,并增加了组合收益率大于其均值的概率.这在均值-方差模型的基础上,增加了偏度参数,建立了收益率均值-方差-偏度模型,开拓了资产组合优化的新思路.二是以组合风险价值VaR建立了约束条件,通过在一定置信水平下的最大损失限额来制约贷款组合的违约风险,使贷款配给的风险限定在银行的承受能力和贷款准备金的范围之内,解决了整体风险的控制问题.     

基于动态参照点的损失厌恶投资组合优化模型

在连续时间下,考虑损失厌恶投资者参照点的动态调整特征,构建基于动态参照点的损失厌恶投资组合模型,使用鞅方法对模型进行求解,得到最优风险资产权重的解析表达式。并计算损失厌恶投资者在参照点动态调整条件下的预期最优期末财富。进一步应用数值算例,分析投资者的参照点动态调整幅度和损失厌恶水平对模型最优风险资产权重和预期最优期末财富的影响。     

资本充足率控制预留缺口的资产负债优化模型

以利率变化后的资本充足率满足商业银行法要求的≥8%为约束条件,以资产组合的利息收入最大为目标函数,建立资产负债组合优化模型.本文的创新与特色一是通过预设持续期缺口使银行的资产组合在利率变动的有利条件下增加银行净值.这弥补了现有的零缺口免疫条件的资产组合不能使银行股东权益在利率变化中增加的缺陷.二是通过对预设持续期缺口的控制使银行的资产组合在利率变动的不利条件下满足资本充足率的法律要求.这种优化配给控制了资本损失,保护了股东权益,保证了在银行净值发生变化时资本充足率仍满足法律要求.     

政府促进银行实施绿色信贷的多目标优化策略研究

传统的绿色信贷研究中存在着模型简单、非动态参数以及只能获取纳什均衡点的局限性。为改善这些局限性,研究了一种基于数据驱动多目标优化算法的政府促进银行实施绿色信贷的策略计算方法。首先针对绿色信贷的最优策略求解问题建立数据驱动的多目标优化算法框架,再基于历史数据建立算法框架中的最优策略马可夫状态转移模型,最后使用多目标粒子群优化算法对政府和银行的长远总收益进行最优策略求解。与传统的基于近似模型及博弈论的方法不同,本文提出的方法可以获得历史数据中的经验,从而制定出具有更加长远收益的策略,避免了传统方法中的“短视”现象。分析结果表明,绿色信贷的收益不会在短时间内显现,因此政府在做决策时,必须根据绿色信贷收益的回报周期作出长远的判断。     

损失厌恶偏好与资产组合选择研究

在不确定性条件下,期望的不可计算性、行动结果比较的局限性以及投资个体选择的非理性使理性假定的选择理论脱离现实,因此重新探讨决策选择准则是必要的.以行为金融理论中不确定性状态下的有限理性与满意准则为依据,引入与满意准则一致且体现损失厌恶偏好的VaR作为风险指标,构建行为资产组合模型,在一种简单新颖的M-V模型的矩阵解法基础上,探寻了正态与部分非正态性假设下VaR-BPT模型的显性最优解或有效前沿,解决了现实中最优投资组合选择的可操作性难题,并在中国股票市场验证了正态性转换方法是处理非正态分布下资产组合选择问题的一种优秀方法.     

考虑风险规避的供应链融资与信用保险组合模型研究

针对供应链的资金约束问题,考虑了由一个资金约束的零售商、资金充足的供应商、风险规避型银行以及保险公司组成的供应链融资系统,分别构建了风险规避型银行融资模型以及银行融资与信用保险的组合模型,给出了两种模型中供应链融资系统成员的最优决策。研究表明:与传统风险规避型的银行融资模型相比,银行融资与信用保险的组合模型能够有效地增加零售商的融资规模,并降低银行的损失风险,从而信用保险能够给整个供应链融资系统带来严格帕累托改进。最后,通过数值算例说明了研究结论的有效性。     

多参数Archimedean Copula模型下的CDO定价

利用高维Archimedean Copula模型对合成CDO进行定价,在传统简单Archimedean Copula的基础上,基于三种不同的方式,引入多个参数,从而解决作为市场基准的Gaussian Copula模型下存在相关性微笑的问题.对于特殊的大样本同质资产组合,违约损失分布可以直接从违约概率得到.而对于一般性的资产组合,可以得到损失的特征函数,从而通过快速Fourier变换,计算出违约的分布.最后,给出了数值计算结果.     

Arbitrage and the tax code

We provide a detailed characterization of arbitrage-free asset prices in the presence of capital gains and income taxes. The distinguishing feature of our analysis is that we impose on the model two important features of the tax code: the limited use of capital losses and the inability to wash sell. We show that under remarkably mild conditions, the lack of pre-tax arbitrage implies the lack of post-tax arbitrage with the limited use of capital losses. The conditions are that the risk free interest rate be positive and that tax rates on interest income exceed capital gains tax rates. The result also holds when only a wash sale constraint is imposed and no investor holds a portfolio with a large capital loss. We allow investors to face different tax rates and have different bases for the calculation of capital gains taxes. The characterizations we provide have important implications for both asset pricing and portfolio choice. Our results imply that models that use arbitrage-free pre-tax models continue for derivative pricing and hedging are also arbitrage free in a world with taxes. Similarly, portfolio choice models with taxes typically specify pre-tax arbitrage free price processes and then analyze portfolio choice in the presence of taxes. In these models, it is unclear if portfolio recommendations are based on risk-return tradeoffs or on the arbitrage opportunities present in the model. Our results imply that if the above features of the tax code are modeled explicitly, then we can isolate the post-tax risk-return tradeoffs.     

Regulatory capital decisions in the Context of consumer loan portfolios

A topic of interest in recent literature is regulatory capital requirements for consumer loan portfolios. Banks are required to hold regulatory capital for unexpected losses, while expected losses are to be covered by either provisions or future income. In this paper, we show the set of efficient operating points in the market share and profit space for a portfolio manager operating under Basel II capital requirement and under capital constraints are a union of single-cutoff-score and double-cutoff-score operating points. For a portfolio manager to increase market-share beyond the maximum allowable under a single-cutoff score policy (eg, with binding capital constraints) requires granting loans to higher than optimal risk applicants. We show this result in greater portfolio risk but without an increase in regulatory capital requirement amount. The increase in forecasted losses is assumed to be absorbed by provisions or future margin income. Given portfolio managers take on higher risk under the same regulatory capital amount, our findings call for greater focus on provision amounts and future margin income under the supervisory review pillar of Basel II. This research raises the issue of whether the design of the regulatory formula for consumer loan portfolios is flawed.     

Heterogeneous credit portfolios and the dynamics of the aggregate losses

We study the impact of contagion in a network of firms facing credit risk. We describe an intensity based model where the homogeneity assumption is broken by introducing a random environment that makes it possible to take into account the idiosyncratic characteristics of the firms. We shall see that our model goes behind the identification of groups of firms that can be considered basically exchangeable. Despite this heterogeneity assumption our model has the advantage of being totally tractable. The aim is to quantify the losses that a bank may suffer in a large credit portfolio. Relying on a large deviation principle on the trajectory space of the process, we state a suitable law of large numbers and a central limit theorem useful for studying large portfolio losses. Simulation results are provided as well as applications to portfolio loss distribution analysis.     

Tail behaviour of credit loss distributions for general latent factor models

Using a limiting approach to portfolio credit risk, we obtain analytic expressions for the tail behavior of credit losses. To capture the co‐movements in defaults over time, we assume that defaults are triggered by a general, possibly non‐linear, factor model involving both systematic and idiosyncratic risk factors. The model encompasses default mechanisms in popular models of portfolio credit risk, such as CreditMetrics and CreditRisk⁺. We show how the tail characteristics of portfolio credit losses depend directly upon the factor model's functional form and the tail properties of the model's risk factors. In many cases the credit loss distribution has a polynomial (rather than exponential) tail. This feature is robust to changes in tail characteristics of the underlying risk factors. Finally, we show that the interaction between portfolio quality and credit loss tail behavior is strikingly different between the CreditMetrics and CreditRisk⁺ approach to modeling portfolio credit risk.     

Use of DEA cross-efficiency evaluation in portfolio selection: An application to Korean stock market

We propose a way of using DEA cross-efficiency evaluation in portfolio selection. While cross efficiency is an approach developed for peer evaluation, we improve its use in portfolio selection. In addition to (average) cross-efficiency scores, we suggest to examine the variations of cross-efficiencies, and to incorporate two statistics of cross-efficiencies into the mean-variance formulation of portfolio selection. Two benefits are attained by our proposed approach. One is selection of portfolios well-diversified in terms of their performance on multiple evaluation criteria, and the other is alleviation of the so-called “ganging together” phenomenon of DEA cross-efficiency evaluation in portfolio selection. We apply the proposed approach to stock portfolio selection in the Korean stock market, and demonstrate that the proposed approach can be a promising tool for stock portfolio selection by showing that the selected portfolio yields higher risk-adjusted returns than other benchmark portfolios for a 9-year sample period from 2002 to 2011.     

含有背景风险的双目标投资组合模型研究

投资者进行投资实践时无不面临着背景风险。绝大多数以均值方差为框架的投资组合并没有考虑背景风险,其效用在实际应用中容易受到背景风险的影响。本文在含有交易费用的双目标函数模型中引入背景风险,从是否含有背景风险和背景风险偏好度大小两方面对投资组合问题展开研究,并使用智能算法得到模型的最优解,对模型进行实证分析。实证结果表明:1)当背景风险收益为0时,含有背景风险的投资组合比不含有背景风险的投资组合更能反映真实的投资环境。2) 当背景风险收益不为0时,含有背景风险的投资组合比不含有背景风险的投资组合得到更高的收益。因此,考虑背景风险后投资组合的构建优于不考虑背景风险投资组合的构建。     

Active allocation of systematic risk and control of risk sensitivity in portfolio optimization

Portfolio risk can be decomposed into two parts, the systematic risk and the nonsystematic risk. It is well known that the nonsystematic risk can be eliminated by diversification, while the systematic risk cannot. Thus, the portfolio risk, except for that of undiversified small portfolios, is always dominated by the systematic risk. In this paper, under the mean–variance framework, we propose a model for actively allocating the systematic risk in portfolio optimization, which can also be interpreted as a model of controlling risk sensitivity in portfolio selection. Although the resulting problem is, in general, a notorious non-convex quadratically constrained quadratic program, the problem formulation is of some special structures due to the features of the defined marginal systematic risk contribution and the way to model the systematic risk via a factor model. By exploiting such special problem characteristics, we design an efficient and globally convergent branch-and-bound solution algorithm, based on a second-order cone relaxation. While empirical study demonstrates that the proposed model is a preferred tool for active portfolio risk management, numerical experiments also show that the proposed solution method is more efficient when compared to the commercial software BARON.     

Behavioral portfolio selection with loss control

In this paper we formulate a continuous-time behavioral (à la cumulative prospect theory) portfolio selection model where the losses are constrained by a pre-specified upper bound. Economically the model is motivated by the previously proved fact that the losses occurring in a bad state of the world can be catastrophic for an unconstrained model. Mathematically solving the model boils down to solving a concave Choquet minimization problem with an additional upper bound. We derive the optimal solution explicitly for such a loss control model. The optimal terminal wealth profile is in general characterized by three pieces: the agent has gains in the good states of the world, gets a moderate, endogenously constant loss in the intermediate states, and suffers the maximal loss (which is the given bound for losses) in the bad states. Examples are given to illustrate the general results.     

带有模糊系数的投资组合模型研究

在证券市场,由于各种不确定因素的存在,证券的预期收益率是难以精确估算的。本文采用模糊数来处理不确定性,提出了一种基于模糊收益率的投资组合模型。为度量投资组合的风险,将绝对偏差扩展到模糊情形。通过引入模糊数绝对值的概念和不等关系的两种占优准则,将该模型转化为相应的确定性线性规划问题,投资者可根据自己的主观态度选择参数和投资策略。最后用一个具体例子验证了模型的合理性和有效性。