一类推广的奇异型最佳随机控制问题

§1.引言设 W_t,t≥0为概率空间(Ω,(?),P)上的标准 Wiener 过程,{(?)_t}为由之所产生的上升σ-域族,以(?)表所有{(?)_t}适应左连续0初值有限变差过程的全体.对每个ξ={ξ_t,t≥0}∈(?),熟知有正规分解ξ_t=ξ_t~ -ξ_t~-,而(?)_t(?)ξ_t~ ξ_t~-为ξ_t 的全变差过程,当然ξ_t~ 及ξ_t~-皆为(?)中的单调非降过程。     

"边信息"的效用优化及其影响

本文考虑受随机因素影响的股票价模型 ,投资者仅知道的股价信息 (公共信息 )和“边信息”的效用优化问题 .我们利用测度的变换和投影 ,给出了具有“边信息”和不具“边信息”两种情况下的最优财富形式 .对于对数效用函数 ,我们比较最优效用 ,讨论了“边信息”的影响     

均值-CVaR零售商的供应链服务决策及协调契约

研究零售商具有风险偏好行为下,同时考虑价格、质量和服务水平的供应链联合决策问题。运用均值-CVaR准则来刻画零售商风险偏好行为,它包括风险厌恶、风险中性和风险追求,同时具有损失规避的特性。首先得到供应链集中系统、制造商提供服务（模型$\mbox{I}$）和零售商提供服务（模型$\mbox{II}$）下的最优决策和最优利润（期望效用）。其次,证明了成本共担契约在零售商风险厌恶时可以实现供应链协调.第三,对模型$\mbox{I}$和模型$\mbox{II}$协调后的最优利润（期望效用）进行比较,证明两种模型下制造商利润相同,而与模型$\mbox{I}$相比,模型$\mbox{II}$下零售商获得更多的期望效用。最后,数值例子证明了得到的研究结果。     

完全图中的正常染色的路和圈

令$K_{n}^{c}$表示$n$ 个顶点的边染色完全图.
令 $\Delta^{mon}
(K_{n}^{c})$表示$K^c_{n}$的顶点上关联的同种颜色的边的最大数目.
如果$K_{n}^{c}$中的一个圈（路）上相邻的边染不同颜色,则称它为正常染色的.
B. Bollob\'{a}s和P. Erd\"{o}s (1976) 提出了如下猜想：若 $\Delta^{{mon}}
(K_{n}^{c})<\lfloor \frac{n}{2} \rfloor$, 则$K_{n}^{c}$中含有一个正常染
色的Hamilton圈. 这个猜想至今还未被证明.我们研究了上述条件下的正常染色的路和圈.     

复数星图与单路的多染色拉姆齐数

对给定的简单图$H_1,H_2,\ldots,H_c$, 我们将使完全图$K_n$的任意边分解$\{G_i\}^c_{i=1}$都存在至少一个$G_i$有子图同构于$H_i$的最小正整数$n$称为多染色拉姆齐数 $R(H_1,H_2,\ldots,$ $H_c)$. 对正整数$m,n_1,n_2,\ldots,n_c$, 令$\Sigma=\sum_{i=1}^{c}(n_i-1)$. 在文献中,我们已经获得了$R(K_{1,n_1},\ldots,K_{1,n_c},P_m)$ 的一些界和精确值.Wang推测若$\Sigma\not\equiv 0\pmod{m-1}$且$\Sigma+1\ge (m-3)^2$, 则有$R(K_{1,n_1},\ldots, K_{1,n_c}, P_m)=\Sigma+m-1.$ 本文中, 我们给出了一个新的下界并给出$R(K_{1,n_1},\ldots,K_{1,n_c},P_m)$在$m\leq\Sigma$, $\Sigma\equiv k\pmod{m-1}$且$2\leq k \leq m-2$情况下的部分精确值. 这些结果部分证实了Wang的猜想.     

对流扩散方程的解

关注如下的对流扩散方程 $$ u_{t}=\text{div}(|\nabla u^{m}|^{p-2}\nabla u^{m})+\sum_{i=1}^{N}\frac{\partial b_{i}(u^{m})}{\partial x_{i}} $$ 的初边值问题. 若 $p>1+\frac{1}{m}$, 通过考虑正则化问题的解 $u_{k}$, 利用 Moser 迭代技巧, 得到了$u_{k}$ 的 $L^{\infty}$ 模与 梯度 $\nabla u_{k}$ 的 $L^{p}$ 模的局部有界性. 利用紧致性定理, 得到了对流扩散方程本身解的存在性. 若 $p<1+\frac{1}{m},\ p>2$ 或者 $p=1+\frac{1}{m}$, 利用类似的方法可以得到解的存在性. 证明了解的唯一性, 同时讨论了正性和熄灭性等解的性质.     

增益图与其底图的正惯性指数之间的关系

设$\mathbb{T}$是模为1的复数乘法子群.图$G=(V,E)$,这里$V,E$分别表示图的点和边.增益图是将底图中的每条边赋于$\mathbb{T}$中的某个数值$\varphi(v_iv_j)$,且满足$\varphi(v_iv_j) =\overline{\varphi(v_jv_i)}$.将赋值以后的增益图表示为$(G,\varphi)$.设$i_+(G,\varphi)$和$i_+(G)$分别表示增益图与底图的正惯性指数,本文证明了如下结论: $$ - c( G ) \le {i_ + } ( {G,\varphi } ) - {i_ + }( G ) \le c( G ), $$ 这里$c(G)$表示圈空间维数,并且刻画了等号成立时候的所有极图.     

平面图和系列平行图的无圈边染色

图$G$的正常边染色称为无圈的, 如果图$G$中不含2-色圈, 图$G$的无圈边色数用$a''(G)$表示, 是使图$G$存在正常无圈边染色所需要的最少颜色数. Alon等人猜想: 对简单图$G$, 有$a''(G)\leq{\Delta(G)+2}$. 设图$G$是围长为$g(G)$的平面图, 本文证明了: 如果$g(G)\geq3$, 则$a''(G)\leq\max\{2\Delta(G)-2,\Delta(G)+22\}$; 如果 $g(G)\geq5$, 则$a''(G)\leq{\Delta(G)+2}$; 如果$g(G)\geq7$, 则$a''(G)\leq{\Delta(G)+1}$; 如果$g(G)\geq16$并且$\Delta(G)\geq3$, 则$a''(G)=\Delta(G)$; 对系列平行图$G$, 有$a''(G)\leq{\Delta(G)+1}$.     

图的{P4}-分解

一个图G的路分解是指一路集合使得G的每条边恰好出现在其中一条路上.记Pl长度为l-1的路,如果G能够分解成若干个Pl,则称G存在{Pl}—分解.关于图的给定长路分解问题主要结果有:(i)连通图G存在{P3}—分解当且仅当G有偶数条边(见[1]);(ii)连通图G存在{P3,P4}—分解当且仅当G不是C3和奇树,这里C3的长度为3的圈而奇树是所有顶点皆度数为奇数的树(见[3]).本文讨论了3正则图的{P4}—分解情况,并构造证明了边数为3k(k热∈Z且k≥2)的完全图Kn和完全二部图Kr,s存在{P4}—分解.     

一类双重时间序列模型的预报

满足 x_t-A_0=(θ_t+α)x_t-1+α_t的时间序列模型称为双重时序模型.其中{α_t}是正态平稳白噪声序列,{θ_t}为一个随机序列.本文给出了当{θt}服从 AR(1)或 MA(1)模型时,{x_t}的多步最小方差预报及其与适时线性最小方差预报的计算机模拟对比。     

Utility maximization under risk constraints and incomplete information for a market with a change point

In this article, we consider an optimization problem of expected utility maximization of continuous-time trading in a financial market. This trading is constrained by a benchmark for a utility-based shortfall risk measure. The market consists of one asset whose price process is modelled by a Geometric Brownian motion where the market parameters change at a random time. The information flow is modelled by initially and progressively enlarged filtrations which represent the knowledge about the price process, the Brownian motion and the random time. We solve the maximization problem and give the optimal terminal wealth depending on these different filtrations for general utility functions by using martingale representation results for the corresponding filtration.     

Optimal investment under partial information

We consider the problem of maximizing terminal utility in a model where asset prices are driven by Wiener processes, but where the various rates of returns are allowed to be arbitrary semimartingales. The only information available to the investor is the one generated by the asset prices and, in particular, the return processes cannot be observed directly. This leads to an optimal control problem under partial information and for the cases of power, log, and exponential utility we manage to provide a surprisingly explicit representation of the optimal terminal wealth as well as of the optimal portfolio strategy. This is done without any assumptions about the dynamical structure of the return processes. We also show how various explicit results in the existing literature are derived as special cases of the general theory.     

Portfolio optimization for a large investor under partial information and price impact

This paper studies portfolio optimization problems in a market with partial information and price impact. We consider a large investor with an objective of expected utility maximization from terminal wealth. The drift of the underlying price process is modeled as a diffusion affected by a continuous-time Markov chain and the actions of the large investor. Using the stochastic filtering theory, we reduce the optimal control problem under partial information to the one with complete observation. For logarithmic and power utility cases we solve the utility maximization problem explicitly and we obtain optimal investment strategies in the feedback form. We compare the value functions to those for the case without price impact in Bäuerle and Rieder (IEEE Trans Autom Control 49(3):442–447, 2004) and Bäuerle and Rieder (J Appl Prob 362–378, 2005). It turns out that the investor would be better off due to the presence of a price impact both in complete-information and partial-information settings. Moreover, the presence of the price impact results in a shift, which depends on the distance to final time and on the state of the filter, on the optimal control strategy.     

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.     

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.     

Dynamic utility maximization with bounded shortfall risks

We address the dynamic portfolio optimization problem where the expected utility from terminal wealth has to be maximized. The special feature of this paper is an additional constraint on the portfolio strategy modeling bounded shortfall risks. We consider the risk, that the terminal wealth of the portfolio falls short of a certain benchmark. This benchmark is chosen to be proportional to the stock price. The risk is measured by the Expected Utility Loss. Using a continuous-time model of a complete financial market and applying martingale methods, analytic expressions for the optimal terminal wealth and the optimal portfolio strategies are given. (© 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Power Utility Maximization Problems Under Partial Information and Information Sufficiency in a Brownian Setting

We consider the problem of expected power utility maximization from terminal wealth in diffusion market models under partial information. After obtaining novel neat expressions for the value-process and for the optimal strategy, the issue of information sufficiency is addressed. In particular, necessary and sufficient conditions that guarantee that the partial information optimal strategy is still optimal when having access to all market information, are provided.     

A General Stochastic Calculus Approach to Insider Trading

The purpose of this paper is to present a general stochastic calculus approach to insider trading. We consider a market driven by a standard Brownian motion $B(t)$ on a filtered probability space $\displaystyle (\Omega,\F,\left\{\F\right\}_{t\geq 0},P)$ where the coefficients are adapted to a filtration ${\Bbb G}=\left\{\G_t\right\}_{0\leq t\leq T}$, with $\F_t\subset\G_t$ for all $t\in [0,T]$, $T>0$ being a fixed terminal time. By an {\it insider} in this market we mean a person who has access to a filtration (information) $\displaystyle{\Bbb H}=\left\{\H_t\right\}_{0\leq t\leq T}$ which is strictly bigger than the filtration $\displaystyle{\Bbb G}=\left\{\G_t\right\}_{0\leq t\leq T}$. In this context an insider strategy is represented by an $\H_t$-adapted process $\phi(t)$ and we interpret all anticipating integrals as the forward integral defined in [23] and [25]. We consider an optimal portfolio problem with general utility for an insider with access to a general information $\H_t \supset\G_t$ and show that if an optimal insider portfolio $\pi^*(t)$ of this problem exists, then $B(t)$ is an $\H_t$-semimartingale, i.e. the enlargement of filtration property holds. This is a converse of previously known results in this field. Moreover, if $\pi^*$ exists we obtain an explicit expression in terms of $\pi^*$ for the semimartingale decomposition of $B(t)$ with respect to $\H_t$. This is a generalization of results in [16], [20] and [2].     

Utility maximization with partial information: Hamilton-Jacobi-Bellman equation approach

This paper deals with the problem of maximizing the expected utility of the terminal wealth when the stock price satisfies a stochastic differential equation with instantaneous rates of return modelled as an Ornstein-Uhlenbeck process. Here, only the stock price and interest rate can be observable for an investor. It is reduced to a partially observed stochastic control problem. Combining the filtering theory with the dynamic programming approach, explicit representations of the optimal value functions and corresponding optimal strategies are derived. Moreover, closed-form solutions are provided in two cases of exponential utility and logarithmic utility. In particular, logarithmic utility is considered under the restriction of short-selling and borrowing.