基于VaR和集中度约束的贷款组合优化模型

资产负债管理是把资产与负债组合视为有机整体,协调流动性、安全性和赢利性,本文通过资产的集中度约束把银行资产合理分配在不同行业中,有效降低银行资产集中度风险,通过能反映银行风险承受能力的VaR约束控制了贷款组合风险,应用实例的结果表明,本模型能够谋求"三性"的最佳配置,有效降低银行经营过程中的集中度风险和流动性风险,并实...     

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.     

Climate change and optimal energy technology R&D policy

Public policy response to global climate change presents a classic problem of decision making under uncertainty. Theoretical work has shown that explicitly accounting for uncertainty and learning in climate change can have a large impact on optimal policy, especially technology policy. However, theory also shows that the specific impacts of uncertainty are ambiguous. In this paper, we provide a framework that combines economics and decision analysis to implement probabilistic data on energy technology research and development (R&D) policy in response to global climate change. We find that, given a budget constraint, the composition of the optimal R&D portfolio is highly diversified and robust to risk in climate damages. The overall optimal investment into technical change, however, does depend (in a non-monotonic way) on the risk in climate damages. Finally, we show that in order to properly value R&D, abatement must be included as a recourse decision.     

Tracking error: a multistage portfolio model

We study multistage tracking error problems. Different tracking error measures, commonly used in static models, are discussed as well as some problems which arise when we move from static to dynamic models. We are interested in dynamically replicating a benchmark using only a small subset of assets, considering transaction costs due to rebalancing and introducing a liquidity component in the portfolio. We formulate and solve a multistage tracking error model in a stochastic programming framework. We numerically test our model by dynamically replicating the MSCI Euro index. We consider an increasing number of scenarios and assets and show the superior performance of the dynamically optimized tracking portfolio over static strategies.     

基于离散近似迭代法的多阶段M-V投资组合优化

提出了离散近似迭代方法,并用该方法求解具有交易成本和交易量限制的多阶段均值-方差(M-V)投资组合模型.离散近似迭代方法的基本思路为:首先,将连续型状态变量离散化,根据网络图的构造方法将上述模型转化多阶段赋权有向图;其次,运用嘉量原理求出起点至终点的最长路程,即获得模型的一个可行解;最后,以该可行解为基础,继续迭代直到前后两个可行解非常接近.还证明了该方法的收敛性和复杂性.     

一类终端财富期望效用最大化问题: 通货膨胀情形

本文研究了一类受通货膨胀影响的终端财富期望效用最大化问题.对常数相对风险厌恶(CRRA) 情形的效用函数,用直接构造的方法得到了代理人的显式最优投资策略和最大期望效用,并给出其经济含义. 该思想来自线性二次最优控制问题中的完全平方技术.根据股票价格和通货膨胀率的历史数据,我们用SAS软件估计出模型中参数的近似值,并给出代理人的最优投资策略和最大期望效用.     

Affordable and adequate annuities with stable payouts: Fantasy or reality?

This paper introduces a class of unit-linked annuities that extends existing annuities by allowing portfolio shocks to be gradually absorbed into the annuity payouts. Consequently, our new class enables insurers to offer an affordable and adequate annuity with a stable payout stream. We show how to price and adequately hedge the annuity payouts in a general financial environment. In particular, our model accounts for various stylized facts of stock returns such as asymmetry and heavy-tailedness. Furthermore, the generality of our framework makes it possible to explore the impact of a parameter misspecification on the annuity price and the hedging performance.     

基于矩分析的资产组合选择

在风险资产收益分布为非正态的情景下,通过矩分析,研究其收益的高阶矩对资产组合选择的影响.首先,假设风险资产收益存在有限阶矩,泰勒展开边际财富期望效用,获得静态资产组合选择的近似解;其次,假设收益过程的跳跃产生收益分布的非正态性,运用随机控制方法获得动态资产组合选择的近似解析解,从高阶矩角度解释其特征。分析表明,超出峰度的存在导致减少风险资产投资,正(负)的偏度导致增加(减少)风险资产投资,该影响性随着它们及风险规避系数的增大而增强;可预测性导致资产组合存在正或负的对冲需求,取决于相关系数的符号和风险规避系数;跳跃性总体上减少风险资产投资;可预测性和跳跃性对动态资产组合选择的影响具有内在关联性。     

具有Pareto最优性的风险投资项目组合选择方法

为解决现有风险投资项目组合选择方法未考虑资本不可细分和投资收益率难以预测的问题,首先在借鉴MV模型思想的基础上结合风险投资项目评价指标体系定义了项目组合偏好率及其方差,并将二者分别视为项目组合的产出与投入,然后基于DEA相对效率评价原理构建了能够评价出具有Pareto最优性的项目组合优选模型即VCP-DEA/AR模型,最后通过一个数值验证案例证明了该模型的科学有效性和应用可行性。     

基于免疫记忆克隆算法的指数化投资组合优化构建策略

本文基于克隆选择学说及基于克隆选择学说及生物免疫响应过程的相关机理,提出用于指数化投资的免疫记忆克隆算法,并将其应用于指数化投资组合优化构建模型的求解,旨在探索指数化投资的优化构建策略。文章首先提出多目标的指数化投资组合构建模型。其次,分别设计了适用于指数化投资组合构建策略的抗原、抗体、亲和度函数、克隆选择算子、免疫记忆算子和相应的进化算法。该算法有效避免了传统遗传算法所存在的计算后期解的多样性差、易早熟以及收敛速度慢等缺点。同时,提出了限制投资组合中股票数量的启发式算法。最后,使用包括上证180指数在内的6组世界主要股票市场指数及其成份股的历史数据对模型及算法进行测算,结果表明算法具有良好的求解能力和收敛速度,所建模型的合理性和有效性亦被论证,模型和算法均具有很强的实践价值;