Market Viability and Martingale Measures under Partial Information

We consider a financial market model with a single risky asset whose price process evolves according to a general jump-diffusion with locally bounded coefficients and where market participants have only access to a partial information flow. For any utility function, we prove that the partial information financial market is locally viable, in the sense that the optimal portfolio problem has a solution up to a stopping time, if and only if the (normalised) marginal utility of the terminal wealth generates a partial information equivalent martingale measure (PIEMM). This equivalence result is proved in a constructive way by relying on maximum principles for stochastic control problems under partial information. We then characterize a global notion of market viability in terms of partial information local martingale deflators (PILMDs). We illustrate our results by means of a simple example.     

具有信息的最优投资组合

证券市场的将来是未知的.投资者只能依据所掌握的信息作出相应的投资策略.事实上,信息对投资组合的影响是各种各样的.考虑多个时期有信息作用的投资组合策略问题,建立了有信息影响的最优投资组合的凸规划模型,得到了模型的最优解及其极限,并给出了一些投资组合受信息作用的情形.     

不完全信息和模糊厌恶下DC型养老金最优投资策略

在信息部分可观测的金融市场中,参与者可投资于一个无风险资产、一个滚动债券和一支股票。其中,股票的预期收益率由一个服从均值-回复过程的预测因子预测。参与者是模糊厌恶的,只能观测到股票价格和利率,却无法观测到预测因子。利用滤波技术和动态规划原理,得到了不完全信息和模糊厌恶下DC型养老金最优投资策略的解析式。进一步,利用敏感性分析和比较静态分析,对比仅考虑不完全信息、仅考虑模糊厌恶以及同时考虑不完全信息和模糊厌恶三种情形下的最优投资策略。结果表明同时考虑不完全信息和模糊厌恶时的最优投资策略最保守,仅考虑不完全信息时的最优投资策略对风险厌恶系数的变化最敏感。     

部分信息下均值-方差准则下的投资组合问题研究

研究了部分信息下,投资组合效用最大化的问题.在风险资产(股票)价格满足跳扩散过程,对同时该过程中的系数受马尔科夫调制参数的影响.通过运用非线性滤波技术,将部分信息的问题转化完全信息的问题.并运用随机优化与倒向随机微分方程得到在均值-方差准则的最优投资策略.     

Time-consistent reinsurance and investment strategies for mean–variance insurer under partial information

In this paper, based on equilibrium control law proposed by Björk and Murgoci (2010), we study an optimal investment and reinsurance problem under partial information for insurer with mean–variance utility, where insurer’s risk aversion varies over time. Instead of treating this time-inconsistent problem as pre-committed, we aim to find time-consistent equilibrium strategy within a game theoretic framework. In particular, proportional reinsurance, acquiring new business, investing in financial market are available in the market. The surplus process of insurer is depicted by classical Lundberg model, and the financial market consists of one risk free asset and one risky asset with unobservable Markov-modulated regime switching drift process. By using reduction technique and solving a generalized extended HJB equation, we derive closed-form time-consistent investment–reinsurance strategy and corresponding value function. Moreover, we compare results under partial information with optimal investment–reinsurance strategy when Markov chain is observable. Finally, some numerical illustrations and sensitivity analysis are provided.     

部分信息下股票付息的Black-Scholes期权定价公式和一类最优投资问题

假定金融市场中的投资者仅掌握部分信息,即投资者仅能观测到股票和债券价格,而股票的瞬时回报率和市场的噪声源不能观测.对存款利率和贷款利率不相等的情形,运用凸分析和滤波技术得到了部分信息下股票付红利的Black-Scholes期权定价公式.对部分信息下最大化终端财富的问题,获得了最优投资策略.     

部分信息情形下利率非零时的最优消费投资模型研究

考虑了部分信息情形下市场利率非零时的最优消费投资模型,讨论了相应的最优消费投资策略.最后探讨了当扩散系数可逆且漂移系数服从已知分布时的贝叶斯特例,给出了最优交易策略的明确表达式.     

突发事件下需求信息不对称时的供应链协调应对

协调供应链系统使其具有抗突发事件性的研究是供应链管理的核心议题之一。为了分析突发事件下需求信息不对称时的供应链协调问题,考虑由一个制造商和一个零售商组成的供应链,在随机市场需求下,首先分析了数量折扣契约对供应链的协调作用;然后探讨了突发事件导致市场需求发生变化且变化后的需求信息是不对称信息时数量折扣契约对供应链的协调作用,研究表明:基准的数量折扣契约对突发事件下的供应链不再发挥协调作用,为此,给出了供应链应对突发事件的最优应对策略,并调整了原来的数量折扣契约使其具有抗突发事件性。最后,应用一个算例对比加以说明。     

Optimal investment in markets with over and under-reaction to information

In this paper we introduce a jump-diffusion model of shot-noise type for stock prices, taking into account over and under-reaction of the market to incoming news. We work in a partial information setting, by supposing that standard investors do not have access to the market direction, the drift, (modeled via a random variable) after a jump. We focus on the expected (logarithmic) utility maximization problem by providing the optimal investment strategy in explicit form, both under full (i.e., from the insider point of view, aware of the right kind of market reaction at any time) and under partial information (i.e., from the standard investor viewpoint, who needs to infer the kind of market reaction from data). We test our results on market data relative to Enron and Ahold. The three main contributions of this paper are: the introduction of a new market model dealing with over and under-reaction to news, the explicit computation of the optimal filter dynamics using an original approach combining enlargement of filtrations with Innovation Theory and the application of the optimal portfolio allocation rule to market data.     

Optimal portfolio policies under bounded expected loss and partial information

In a market with partial information we consider the optimal selection of portfolios for utility maximizing investors under joint budget and shortfall risk constraints. The shortfall risk is measured in terms of expected loss. Stock returns satisfy a stochastic differential equation. Under general conditions on the corresponding drift process we provide the optimal trading strategy using Malliavin calculus. We give extensive numerical results in the case that the drift is modeled as a continuous-time Markov chain with finitely many states. To deal with the problem of time-discretization when applying the results to market data, we propose a method to detect and correct possible tracking errors.