Timing Prediction Error Volatility and Dynamic Asset Allocation

We solve a portfolio selection,problem in which,return predictability,risk predictability and transaction cost are incorporated.In the problem,both expected return,prediction error volatility,and transaction cost are time-varying.Our optimal strategy suggests trading partially toward a dynamic aim portfolio,which is a weighted average of expected future tangency portfolio and is highly influenced by the common fluctuation of prediction error volatility(CPE).When CPE is high,the investor would invest less and trade less frequently to avoid risk and transaction cost.Moreover,the investor trades more closely to the aim portfolio with a more persistent CPE signal.We also conduct an empirical analysis based on the commodities futures in Chinese market.The results reveal that by timing prediction error volatility,our strategy outperforms alternative strategies.     

VARIABLE SELECTION FOR COVARIATE ADJUSTED REGRESSION MODEL

This paper employs the SCAD-penalized least squares method to simultaneously select variables and estimate the coefficients for high-dimensional covariate adjusted linear regression models. The distorted variables are assumed to be contaminated with a multiplicative factor that is determined by the value of an unknown function of an observable covariate. The authors show that under some appropriate conditions, the SCAD-penalized least squares estimator has the so called ＂oracle property＂. In addition, the authors also suggest a BIC criterion to select the tuning parameter, and show that BIC criterion is able to identify the true model consistently for the covariate adjusted linear regression models. Simulation studies and a real data are used to illustrate the efficiency of the proposed estimation algorithm.     

The Stability of Imitation Dynamics with Continuously Distributed Delays

This paper investigates imitation dynamics with continuously distributed delay. In realistic technological, economic, and social environments, individuals are involved in strategic interactions simultaneously while the influences of their decision-making may not be observable instantaneously.It shows that there exists a time delay effect. Different distributions of delay are further considered to efficiently lucubrate the stability of interior equilibrium in the imitation dynamics with continuou...     

Integrated dynamic shared protection algorithm for GMPLS networks

The path protection approach is widely investigated as a survivability solution for GMPLS networks, which has the advantage of efficient capacity utilization. However, there is a problem of the path protection approach that searching a disjoint backup path for a primary path is often unsuccessful. In order to resolve this problem, an integrated dynamic shared protection （IDSP） algorithm is proposed. The main idea of the proposed algorithm is that the path protection approach is first used to establish a backup path for the primary path; if the establishment is unsuccessful, then the primary path is dynamically divided into segments whose hop count are not fixed but not more than the limitation calculated by the equations introduced. In this proposal, backup bandwidth sharing is allowed to improve the capacity utilization ratio, which makes the link cost function quite different from previous ones. Simulation experiments are presented to demonstrate the efficiency of the proposed method compared with previous methods. Numerical results show that IDSP can not only achieve low protection failure probability but can also gain a better tradeoff between the protection overbuild and the average recovery time.     

Research on secure buyer-seller watermarking protocol

A new buyer-seller watermarking protocol is proposed by applying a double encryption method and a novel mechanism of embedding a buyer＇s watermark. The protocol can effectively prevent against collusion attacks and the man in the middle attack if the third party is not trusted. Also, based on the proposed scheme for the first-hand transaction, a new buyer-reseller watermarking protocol and a formal multi-party watermarking protocol are also proposed. The proposed buyer-resell watermarking protocol only needs the original seller to provide transfer certificate and encryption-decryption service to support the second-hand transaction, and the multi-party watermarking protocol with distributed certificate authorities can overcome the difficulty in the combination of multicast mechanism with multiple unique watermarks and allow a seller to multicast the watermarked digital contents and key transaction information to n buyers. Furthermore, the idea of zero knowledge proof is also applied into the proposed scheme to allow the seller to take an effective control on the task performed by the third party.     

A price-setting newsvendor model under CVaR decision criterion with emergency procurement

<正>In this paper,we consider a newsvendor model in which a risk-averse manager faces a stochastic price-dependent demand in either an additive or a multiplicative form.An emergency purchase option is allowed after the realization of demand to satisfy the units that are short.By adopting conditional value-at-risk(CVaR) as the decision criterion,we aim to investigate the optimal pricing and ordering decisions,and the effects of parameter changes in such a setting.We provide sufficient conditions for the uniqueness of the optimal policy for both demand models.We perform comparative statics analysis to show how the optimal pricing and ordering decision behaves when changing parameters.We also compare our results with those of the newsvendor with a general utility function and with CVaR criterion under lost sales assumption.Our key results include:(i) For both demand models,the optimal selling price is decreasing in risk aversion.Hence,the optimal price of a risk-averse newsvendor is not greater than the optimal price of a risk-neutral newsvendor.(ii) In contrary to the lost sales case,for the multiplicative demand model,the optimal order quantity may not be monotonic in risk aversion. Consequently,the optimal risk-averse order quantity may be lower or higher than the optimal risk-neutral counterpart.(iii) For the additive model,the optimal order quantity is strictly increasing in the emergency purchase price,while for the multiplicative model the optimal order quantity has no such a monotonic property.Some numerical examples are conducted to verify our claims and gain more insights about the risk-averse decision-making behaviors.     

Data crystallization applied for designing new products

It is only the observable part of the real world that can be stored in data. For such incomplete and ill-structured data, data crystallizing aims at presenting the hidden structure among events including unobservable events. This is realized by data crystallization, where dummy items, corresponding to potential existence ofunobservable events, are inserted to the given data. These dummy items and their relations with observable events are visualized by applying KeyGraph to the data with dummy items, like the crystallization of snow where dusts are involved in the formation of crystallization of water molecules. For tuning the granularity level of structure to be visualized, the tool of data crystallization is integrated with human＇s process of understanding significant scenarios in the real world. This basic method is expected to be applicable for various real world domains where previous methods of chance-discovery lead human to successful decision making. In this paper, we apply the data crystallization with human-interactive annealing （DCHA） to the design of products in a real company. The results show its effect to industrial decision making.     

Learning Bayesian networks using genetic algorithm

A new method to evaluate the fitness of the Bayesian networks according to the observed data is provided. The main advantage of this criterion is that it is suitable for both the complete and incomplete cases while the others not. Moreover it facilitates the computation greatly. In order to reduce the search space, the notation of equivalent class proposed by David Chickering is adopted. Instead of using the method directly, the novel criterion, variable ordering, and equivalent class are combined,moreover the proposed mthod avoids some problems caused by the previous one. Later, the genetic algorithm which allows global convergence, lack in the most of the methods searching for Bayesian network is applied to search for a good model in this space. To speed up the convergence, the genetic algorithm is combined with the greedy algorithm. Finally, the simulation shows the validity of the proposed approach.     

Dynamics in small worlds of tree topologies of wireless sensor networks

Tree topologies, which construct spatial graphs with large characteristic path lengths and small clustering coefficients,are ubiquitous in deployments of wireless sensor networks. Small worlds are investigated in tree-based networks. Due to link additions, characteristic path lengths reduce rapidly and clustering coefficients increase greatly. A tree abstract, Cayley tree, is considered for the study of the navigation algorithm, which runs automatically in the small worlds of tree-based networks. In the further study, epidemics in the small worlds of tree-based wireless sen-sor networks on the large scale are studied, and the percolation threshold is calculated, at which the outbreak of the epidemictakes place. Compared with Cayley tree, there is a smaller percolation threshold suffering from the epidemic.     

Further results on limitations of sampled-data feedback

To control continuous-time uncertain dynamical systems with sampled data-feedback is prevalent today,but the sampling rate is usually not allowed to be arbitrarily fast due to various physical and/or computational constrains.In this paper,the authors examine the limitations of sampled-data feedback control for a class of uncertain systems in continuous-time,with sampling rate not necessary fast enough and with the unknown system structure confined to a set of functions with both linear and nonlinear growth.The limitations of the sampled-data feedback control for the uncertain systems are established quantitatively,which extends the existing related results in the literature.     

基于可变安全第一准则和交易约束的投资组合调整模型

结合证券市场的实际情况,通过加入最小交易单位及交易费用约束改进了基于可变安全第一准则的风险定义,将风险表示成为与投资者意愿和交易约束相关的一条曲线。提出了一个新的基于可变安全第一准则的具有一般交易费用函数的投资组合调整优化模型,并给出求解该模型的基于遗传算法和随机模拟的混合智能算法步骤。然后,结合现实中交易费用的实际情况,分别建立了具有线性交易费用和二次分段凹型交易费用的投资组合调整模型。最后,依据上海证券市场的实际数据,通过两个实例验证模型的可行性和有效性。     

股票交易时间间隔分布特征的实证研究

通过对中国股票市场中大量投资者的股票交易数据进行统计分析,发现个体买入和卖出股票的时间间隔分布具有幂律分布的特征,均能通过阈值为0.9的Kolmogorov-Smirnov统计性假设检验且幂指数几乎一致,可能体现着人类买卖这种相对应行为的相关性。股票交易次数和交易金额的分布也具有明显的胖尾现象,但并不具有幂律分布的特征。结果表明中国股市仍以小投资者居多,而且投资者的平均交易次数偏少。     

PLS路径模型在建立综合评价指数中的应用

提出将PLS(partialleastsquare)路径模型和复数据表分析相结合,建立多指标系统评估指数的方法.该方法一方面可以方便地研究每一个隐变量与其显变量集合之间的关系,并可以分析各隐变量与综合评估指数之间的联系;另一方面,还可以充分提取原始变量中有效信息,得到一个既能够综合各隐变量、又能很好地代表系统中所有指标变量的综合指数.论文以中国城市发展水平评估为例,采用了反映经济水平、生活水平和城市化水平的三个变量组,将PLS路径模型用于建立城市综合评估指数,对不同城市进行综合评价排名,得到的结果与一般的经济地理知识是十分吻合的.     

一种改进的自组织映射树算法及在组织际关系分类中的应用

分析了自组织映射树各种改进算法的优缺点,改进和实现了一种基于动态二叉树的自组织神经网络(Improved dynamicalbinary-tree based self-organizing neural network, DBTSONN).在改进动态二叉树中神经元节点可以自动生长和剪除,无需在训练前预先确定网络结构.DBTSONN1算法采用单路径搜索最匹配叶节点(获胜神经元),DBTSONN2算法考虑了获胜神经元节点所在自组织二叉树的层次,采用双路径搜索获胜叶节点, 提高了搜索效率.以交易关系的经济和行为维度建立起来的关键中介 变量集为度量指标,使用该算法把组织际关系分为四种类型:双边关系、周期性关系、层级关系以及分散关系, 验证该算法的效率,并分析这种组织际关系分类的实际意义.     

分数布朗运动下带交易费用的期权定价

通过引入交易费用,构建合理的证券组合并采用求解偏微分方程的方法,推导出分数布朗运动下的期权定价公式,消除了分数Black-Scholes市场存在套利,分析了带交易费用的分数布朗运行环境下的避险误差。进一步的数值例子给出了不同定价模型下的定价结果,比较了自融资策略路径、分数布朗运行下期权价格路径以及带交易费用分数布朗运行下期权价格路径,说明了交易费用的引入对消除分数布朗运动金融环境套利的可行性。     

是否应提高高价股的最小报价单位?——基于人工股票市场的实验研究

采用人工股市模拟的方式探讨了不同价位股票最小报价单位变动对市场质量的影响.首先, 以中国股市实际交易机制和交易行为作为输入变量, 构造了基于改进的混合策略三因素预期模型、 前景理论价值函数与风险偏好和交易意愿更新机制的有限理性agent模拟股票市场.然后, 分别对三种价位股票采用不同最小报价单位进行了重复仿真实验.实验结果表明: 不同于相对低价股, 如果提高相对高价股的最小报价单位, 虽然不可避免地会使价差显著增大, 但可在不显著增加波动性的同时, 使市场深度、交易量和市场效率都得到明显改善, 从而显著提高了市场质量.因而, 建议中国股市应当根据股价水平而灵活采取不同的最小报价单位, 即针对高价股适当提高最小报价单位.     

住房租赁占线算法及其竞争策略

研究一个住房租赁占线算法问题.不同于Karp[1]研究的雪橇,住房具有价值昂贵、使用寿命长的特征,因此模型引入＂买卖存在交易成本,价格高于交易成本＂的假设,描述一个可二手交易的住房租赁问题的占线决策过程.在该过程中,理性的决策者在住房使用结束后会权衡住房市值与交易成本变卖住房以降低居住成本.我们对这一问题展开了竞争分析,获得了一个反映交易环境、行业竞争水平与占线策略及竞争比的等式.等式说明在对未来需求信息了解相同的情况下,交易市场、行业竞争水平等环境因素决定占线策略及竞争比,模型对类似环境条件下租赁问题的决策具有借鉴意义.     

研究具H∞范数摄动系统绝对稳定性的频域算法

利用Popov判据和圆判据，给出了判断一类非线性摄动系统鲁棒绝对稳定性的条件，当系统的前馈通道存在未建模动态摄动而反馈通道存在扇区非线性时，通过频域作图的方法，得到动态不确定性的范数界限，最后，举例比较了这两种频域判据在判断时不变非线性时的结果。     

网络结点流量控制的非线性模型分析

针对网络中海量数据传输的网络拥塞控制问题,对网络流量稳定性控制的非线性模型进行了分析和模拟。结合网络中产生拥塞的原因(控制信息与数据沿同一链路传输且具有相同的时延,而每一个用户都试图最大限度地利用网络),给出了利用TurboC模拟不同带宽利用率、不同工具函数、不同经验因子情况下的网络传输情况。验证了模型的科学性、问题所在及建立脱离网络拓扑和网络协议的通用结点流量控制模型的可行性。     

证券投资者交易行为的进化博弈

应用进化博弈方法,建立了证券投资者交易行为演化的进化博弈模型,分析了在长时期内投资者交易行为的动态演化过程。结果表明,投资者交易行为的演化存在多重均衡的特征,且其演化的路径选择和均衡与投资者的效用函数和证券市场的初始环境密切相关,并受到投资者对风险资产收益的不合理预期、噪声交易风险、基本面风险、理性交易成本等诸多因素的影响。