On the equivalence of the static and dynamic asset allocation problems

A classic dynamic asset allocation problem optimizes the expected final-time utility of wealth, for an individual who can invest in a risky stock and a risk-free bond, trading continuously in time. Recently, several authors considered the corresponding static asset allocation problem in which the individual cannot trade but can invest in options as well as the underlying. The optimal static strategy can never do better than the optimal dynamic one. Surprisingly, however, for some market models the two approaches are equivalent. When this happens the static strategy is clearly preferable, since it avoids any impact of market frictions. This paper examines the question: when, exactly, are the static and dynamic approaches equivalent? We give an easily tested necessary and sufficient condition, and many non-trivial examples. Our analysis assumes that the stock follows a scalar diffusion process, and uses the completeness of the resulting market model. A simple special case is when the drift and volatility depend only on time; then the two approaches are equivalent precisely if (μ (t)? r)/σ²(t) is constant. This is not the Sharpe ratio or the market price of risk, but rather a nondimensional ratio of excess return to squared volatility that arises naturally in portfolio optimization problems.     

A new computational tool for analysing dynamic hedging under transaction costs

This paper highlights a framework for analysing dynamic hedging strategies under transaction costs. First, self-financing portfolio dynamics under transaction costs are modelled as being portfolio affine. An algorithm for computing the moments of the hedging error on a lattice under portfolio affine dynamics is then presented. In a number of circumstances, this provides an efficient approach to analysing the performance of hedging strategies under transaction costs through moments. As an example, this approach is applied to the hedging of a European call option with a Black–Scholes delta hedge and Leland's adjustment for transaction costs. Results are presented that demonstrate the range of analysis possible within the presented framework.     

Investment strategies in the long run with proportional transaction costs and a HARA utility function

We consider an agent who invests in a stock and a money market in order to maximize the asymptotic behaviour of expected utility of the portfolio market price in the presence of proportional transaction costs. The assumption that the portfolio market price is a geometric Brownian motion and the restriction to a utility function with hyperbolic absolute risk aversion (HARA) enable us to evaluate interval investment strategies. It is shown that the optimal interval strategy is also optimal among a wide family of strategies and that it is optimal also in a time changed model in the case of logarithmic utility.     

基于GM-DEA对天然气操作成本预测及投入产出优化研究

以气田的天然气操作成本预测与优化控制为研究对象,以HTB气田天然气成本为基础,采用GM(1,1)模型对天然气操作成本进行预测,并运用DEA(I-C2 R)技术对投入产出要素进行评价和优化,从而比较准确的为气田管理部门提供优化成本的措施,可帮助气田实现资源的优化配置,从而提高气田的整体经济效益。     

考虑风险间关联作用的项目风险应对策略优选方法

针对已有的项目风险应对策略选择方法对不同项目风险间的关联作用考虑不足的缺点,构建了考虑风险关联作用的项目风险应对策略选择模型。该模型以风险应对效果最大化为目标,综合考虑项目风险的期望损失、不同风险间的关联作用以及风险应对预算等因素,通过求解优化模型确定合适的风险应对策略集合。最后,运用实例验证了该方法的可行性。     

平面稀疏阵列天线的约束优化设计

针对有阵元数和阵列口径约束的矩形平面稀疏阵天线的综合问题,提出了一种基于整数编码的差分进化算法。该方法以每个阵元的栅格位置编号作为设计变量,使阵列的稀疏率满足约束条件,避免了优化过程中的不可行解,还减少了优化变量的个数。为了加速优化过程,采用快速傅里叶变化计算阵列的方向图。以改善阵列峰值副瓣电平为目的进行仿真试验,结果表明：优化后的稀疏天线阵峰值旁瓣电平比现有方法相比改善了1.2~1.7 dB,且具有收敛性和稳定性好的优点。     

混合智能算法在电子设备动态管理优化中的应用

应用微分进化算法（DEA）与字典排序算法（DSA）相结合的智能算法优化管理电子设备动态货位,研究了基于分拣选路径、存取效率、支架稳定性的动态管理多目标优化问题,并与采用遗传算法（GA）的动态管理优化进行了比对,发现字典排序算法能够按照数字顺序大小构建基于分拣选路径、存取效率、支架稳定性等因素重要程度的多目标函数,微分进化算法则能对多目标函数实施有效优化。仿真结果表明,混合智能算法迭代步数少,收敛速度快,具有更好的执行效率。     

基于感兴趣区域的HEVC压缩性能优化

根据人类视觉系统(HVS)对纹理复杂及运动区域具有较强感知度的特点,提出了一种基于感兴趣区域的高效率视频编码(HEVC)压缩性能优化算法。首先使用Sobel梯度检测算子和运动矢量分别检测纹理复杂区域和运动区域,把检测到的纹理复杂及运动区域定义为感兴趣区域;再对感兴趣区域分级,通过调整量化参数(QP),优化比特分配。实验结果表明,与HEVC标准算法相比,所提算法码率平均减少了15.29%,时间平均节省了11.38%。     

新型工业化道路和传统产业的优化升级

几十年来,我国传统产业的发展是以资源极度浪费和城乡差距进一步拉大为沉重代价,至今技术水平落后、经济效益低下、竞争力薄弱、环境污染严重。实证分析表明:传统产业的劣化和恶化状态正严重制约国民经济的健康与可持续发展,大力实施传统产业的升级改造,是我国新型工业化道路所面临的重大而迫切的战略任务。     

混合TOPSIS方法在货位优化方案选择中的应用

货位优化方案的选择是自动化立体仓库中的重要决策。货位布局合理关系着整个库内作业的效率。根据货位布局应遵循的原则。建立了选择方案的指标体系。考虑到信息的不确定性．以区间数形式表示定性指标值,应用混合型TOPSIS方法建立了目标优选的模型。最后通过实例对方法的有效性和实用性进行了验证。