具边信息的最优效用及其影响

利用测度变换及随机滤波考察了$Q$\,-鞅$\{\wt{\Lambda}_t:=\ep^Q[\Lambda_T|{\cal G}_t]\}$的分解. 然后利用这种分解考察了受随机因素影响的股票价格模型中投资者存在边信息和不存在边信息时的效用问题, 给出了最优效用的一种形式, 从而证明了边信息的影响有限.     

政府购买公共服务的三边匹配决策模型

针对政府购买公共服务中供应商及评估方的选择决策问题,从政府服务购买、服务供应、监管评估三方的匹配视域,利用三边匹配决策与多属性决策方法,构建基于各方评价的三边匹配模型.首先,对政府购买公共服务的三边匹配问题进行了描述,并给出了三边匹配的相关概念.然后,在三边主体多属性评价信息的基础上,定义匹配效用函数,给出了标准加权效用矩阵的计算方法.进一步地,在考虑三方加权匹配效用最优的基础上,建立了累加最优效用三边匹配模型.最后,对模型进行了算例应用及分析,研究表明模型对政府选择服务供应商及监管评估机构有实践的指导意义.     

第三方监管机制下PPP项目的三边匹配决策模型

以第三方监管机制下PPP项目匹配供应商和第三方监管机构为研究背景,基于多指标方向偏好评价信息,构建PPP项目的三边非循环最优稳定匹配模型,并给出匹配决策的步骤及方法.首先,基于主体间多指标方向偏好评价信息,给出了主体间方向偏好效用函数的定义及计算方法;其次,以方向偏好效用函数为基础,研究了PPP项目匹配系统总偏好效用,同时,从系统稳定性视角,给出了三边非循环匹配系统下稳定匹配的定义;然后,基于系统稳定性和总偏好效用,建立了PPP项目三边匹配的最优稳定匹配模型,并给出了求解模型的决策方法;最后,通过算例验证最优稳定匹配模型对PPP项目匹配决策过程的可行性和有效性.     

部分信息下多个寿险购买与投资消费问题

考虑了部分信息下工资收入者的最优消费、投资和多个寿险选择与购买的问题,目标是使工资收入者的消费、遗产和退休时的终端财富的期望效用最大化,求得了幂效用和对数效用下的最优值函数和相应的最优策略,并给出了一个数值例子及相应的结果分析.     

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.     

带预期的最优消费选择：鞅方法

本文研究了投资者最优消费投资问题,这类投资者拥有Brown运动的终端信息,但该信息可能受噪声干扰,在对证券价格过程和投资者偏好作极其一般的假设条件下,我们利用鞅和对偶技术建立了最优策略的存在性,并就对数效用投资者,我们建立了 最优消费投资公式。     

部分信息下期望消费效用最大的优化问题

研究了部分信息下期望消费效用最大的优化问题.利用凸分析理论,非线性滤波和Malliavin导数技术,得到了最优投资-消费策略和代价泛函.对于对数效用函数情形,给出了一个估算信息价值的公式,它是完全信息下和部分信息下所对应的最优代价泛函的差值.     

具有随机保费和交易费用的最优投资-再保险策略

本文研究具有随机保费和交易费用的最优投资和再保险策略选择问题.保险公司的盈余通过跳-扩散过程来模拟,假设保费收入是随机的.我们的研究目标是寻找一个最优再保险和投资策略,最大化投资终止时刻财富的期望效用.应用随机控制理论,我们得到最优投资-再保险策略和值函数的显式解.通过数值计算,我们给出模型参数对最优策略的影响.结果揭示了一些令人感兴趣的现象,它们可以对实际中的再保险和投资予以指导.     

Heston随机波动率模型下的动态投资组合

应用随机最优控制方法对Heston随机波动率模型下的动态投资组合问题进行了研究,得到了幂效用和指数效用下最优投资策略的显示解,并给出一些数值计算结果分析了市场参数对最优投资策略的影响.     

奈特不确定和部分信息下的最优交易策略

本文研究了在奈特不确定和部分信息下的最优交易策略.考虑一个多种股票模型,股票价格过程满足随机微分方程,股票价格的瞬时收益率由有限状态连续时间的马尔科夫链刻画.在奈特不确定投资者α-极大极小期望效用最大化目标下,利用隐马尔科夫模型(HMM)滤波理论和Maliavin分析,导出最优交易策略的显式表达式.文中模型的特点是使用了区别含糊和含糊态度的α-极大极小期望效用,并且从最优投资策略显式解中可以得知含糊和含糊态度会明显影响投资者的行为.所以本文结论具有实际经济意义.     

HARA frontiers of optimal portfolios in stochastic markets

In this paper, we consider the optimal portfolio selection problem in continuous-time settings where the investor maximizes the expected utility of the terminal wealth in a stochastic market. The utility function has the structure of the HARA family and the market states change according to a Markov process. The states of the market describe the prevailing economic, financial, social and other conditions that affect the deterministic and probabilistic parameters of the model. This includes the distributions of the random asset returns as well as the utility function. We analyzed Black–Scholes type continuous-time models where the market parameters are driven by Markov processes. The Markov process that affects the state of the market is independent of the underlying Brownian motion that drives the stock prices. The problem of maximizing the expected utility of the terminal wealth is investigated and solved by stochastic optimal control methods for exponential, logarithmic and power utility functions. We found explicit solutions for optimal policy and the associated value functions. We also constructed the optimal wealth process explicitly and discussed some of its properties. In particular, it is shown that the optimal policy provides linear frontiers.     

Portfolio selection in stochastic markets with HARA utility functions

In this paper, we consider the optimal portfolio selection problem where the investor maximizes the expected utility of the terminal wealth. The utility function belongs to the HARA family which includes exponential, logarithmic, and power utility functions. The main feature of the model is that returns of the risky assets and the utility function all depend on an external process that represents the stochastic market. The states of the market describe the prevailing economic, financial, social, political and other conditions that affect the deterministic and probabilistic parameters of the model. We suppose that the random changes in the market states are depicted by a Markov chain. Dynamic programming is used to obtain an explicit characterization of the optimal policy. In particular, it is shown that optimal portfolios satisfy the separation property and the composition of the risky portfolio does not depend on the wealth of the investor. We also provide an explicit construction of the optimal wealth process and use it to determine various quantities of interest. The return-risk frontiers of the terminal wealth are shown to have linear forms. Special cases are discussed together with numerical illustrations.     

Utility maximization problem with random endowment and transaction costs: when wealth may become negative

In this article, we study the problem of maximizing expected utility from the terminal wealth with proportional transaction costs and random endowment. In the context of the existence of consistent price systems, we consider the duality between the primal utility maximization problem and the dual one, which is set up on the domain of finitely additive measures. In particular, we prove duality results for utility functions supporting possibly negative values. Moreover, we construct a shadow market by the dual optimal process and consider the utility-based pricing for random endowment.     

Optimal investment and risk control policies for an insurer: Expected utility maximization

Motivated by the AIG bailout case in the financial crisis of 2007–2008, we consider an insurer who wants to maximize his/her expected utility of terminal wealth by selecting optimal investment and risk control strategies. The insurer’s risk process is modeled by a jump-diffusion process and is negatively correlated with the capital gains in the financial market. We obtain explicit solutions of optimal strategies for various utility functions.     

Power Utility Maximization in an Exponential Levy Model Without a Risk-free Asset

We consider the problem of maximizing the expected power utility from terminal wealth in a market where logarithmic securities prices follow a Levy process. By Girsanov's theorem, we give explicit solutions for power utility of undiscounted terminal wealth in terms of the Levy-Khintchine triplet.     

Portfolio selection in stochastic markets with exponential utility functions

We consider the optimal portfolio selection problem in a multiple period setting where the investor maximizes the expected utility of the terminal wealth in a stochastic market. The utility function has an exponential structure and the market states change according to a Markov chain. The states of the market describe the prevailing economic, financial, social and other conditions that affect the deterministic and probabilistic parameters of the model. This includes the distributions of the random asset returns as well as the utility function. The problem is solved using the dynamic programming approach to obtain the optimal solution and an explicit characterization of the optimal policy. We also discuss the stochastic structure of the wealth process under the optimal policy and determine various quantities of interest including its Fourier transform. The exponential return-risk frontier of the terminal wealth is shown to have a linear form. Special cases of multivariate normal and exponential returns are disussed together with a numerical illustration.     

Optimal Investment Strategies for an Insurer with SAHARA Utility

In this paper, we consider the optimal investment strategy which maximizes the utility of the terminal wealth of an insurer with SAHARA utility functions. This class of utility functions has non-monotone absolute risk aversion, which is more flexible than the CARA and CRRA utility functions. In the case that the risk process is modeled as a Brownian motion and the stock process is modeled as a geometric Brownian motion, we get the closed-form solutions for our problem by the martingale method for both the constant threshold and when the threshold evolves dynamically according to a specific process. Finally, we show that the optimal strategy is state-dependent.     

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??In this paper, we consider the optimal investment strategy which maximizes the utility of the terminal wealth of an insurer with SAHARA utility functions. This class of utility functions has non-monotone absolute risk aversion, which is more flexible than the CARA and CRRA utility functions. In the case that the risk process is modeled as a Brownian motion and the stock process is modeled as a geometric Brownian motion, we get the closed-form solutions for our problem by the martingale method for both the constant threshold and when the threshold evolves dynamically according to a specific process. Finally, we show that the optimal strategy is state-dependent.     

具有共同冲击相依性的跳扩散金融市场中有着延迟和违约风险的鲁棒最优再保险和投资策略

在本文中,我们考虑跳扩散模型下具有延迟和违约风险的鲁棒最优再保险和投资问题,保险人可以投资无风险资产,可违约的债券和两个风险资产,其中两个风险资产遵循跳跃扩散模型且受到同种因素带来共同影响而相互关联.假设允许保险人购买比例再保险,特别地再保险保费利用均值方差保费原则来计算.在考虑与绩效相关的资本流入/流出下,保险公司的财富过程通过随机微分延迟方程建模.保险公司的目标是最大程度地发挥终端财富和平均绩效财富组合的预期指数效用,以分别研究违约前和违约后的情况.此外,推导了最优策略的闭式表达式和相应的价值函数.最后通过数值算例和敏感性分析,表明了各种参数对最优策略的影响.另外对于模糊厌恶投资者,忽视模型模糊性风险会带来显著的效用损失.