基于投资者情绪的认知风险和认知收益

将投资者的情绪纳入到证券投资的风险度量,提出了两种基于行为金融的认知风险度量方法,并建立了基于投资者情绪的认知收益模型,研究了认知风险和认知收益之间的关系。研究结果表明：投资者的认知风险和认知收益都与投资者的情绪有关并且两者呈现负相关关系,与标准金融理论中风险和收益的正相关关系相反。     

基于MATLAB的多目标规划最优投资组合方法的探讨

目前投资种类繁多且风险各异,投资者很难选取收益较高而风险较低的可操作性投资组合.针对这一问题,利用多目标规划的方法建立投资组合优化问题的一般模型,在合理假设的基础上将多目标规划问题转化为单目标规划问题,使模型简化更具有可操作性.采用Matlab对实例进行计算,验证了所提方法的可行性和实效性.     

基于情绪的市场认知风险和市场认知收益

非理性投资者的认知风险和认知收益受投资者情绪的影响.基于投资者情绪的非理性认知风险度量模型,并利用理性和非理性投资者的相互作用,构建市场认知风险和认知收益度量模型,分别研究理性和非理性认知风险、认知收益对市场认知风险、认知收益的偏离问题.结果表明,非理性认知风险和认知收益的偏离程度与理性和非理性投资者的市场价值权重以及非理性投资者的情绪有关.     

决策投资模型

考虑保到守型，中间型，风险型三种不同类型投资者对风险程序的偏好不同，采用层次分析法对不同利润加权，加权后，根据希望收益达到最大，而风险尽可能最小的投资原则，建立一个双目标的优化模型，得到了满足不同类型的投资者的最优解。     

基于投资组合理论的房地产投资组合决策模型

现代投资组合理论具有分散风险、稳定收益的作用,被广泛地应用于房地产投资实践中。本文引入风险系数γp,以单位收益下风险最小为目标建立房地产投资组合决策模型,并用不可分散度量系数β将单项房地产投资的总风险分解为系统风险和非系统风险,进一步完善该模型,克服了传统决策方法的缺陷和不足,从理论角度解决了投资者的资金分配问题,以实现风险和收益的最佳组合。     

基于遗传算法的证券投资组合模型的优化及最优解的测定

本文基于遗传算法,建立多目标算法的基金投资组合模型,首先要对投资的资产进行分析,分析资产产生风险的因素,通过因素分析来提取指标,利用聚类分析的方法对指标进行筛选,建立股票资产风险指标体系,建立指标的权重集,客观地分析各指标对资产产生风险的影响程度,建立隶属度矩阵,通过隶属度的值来判断资产的类别。在遗传算法求解投资组合模型的过程中,首先是建立目标函数模型,将目标函数模型作为遗传操作的评估准则。和现有的目标函数模型相比有很多改进,现有的投资模型中采用了统计学中的二次规划模型,只将风险最小,或者收益最大作为评价的目标函数,基于遗传算法的投资组合模型用风险收益比来描述投资者的最终目标,更有利于统计上的应用,经济意义明确。     

基于遗传算法的VaR约束下证券组合模型仿真

在经典的Markowitz证券投资模型的基础上,加入目前在投资领域中广泛应用的风险价值VaR,建立一个以投资回报收益率标准差为目标,以VaR和收益为约束条件的投资组合模型.在正态分布的假设下,将目标函数中非线性约束进行简化.利用遗传算法对该模型进行计算机仿真,取得了良好的效果,解的结果既满足了VaR约束条件,又满足了不同投资者不同收益需求.     

证券投资的非线性认知期望收益

在行为金融的假设框架下,基于投资者的非理性认知分布和不确定风险厌恶特征,提出了刻画证券投资收益的非理性认知期望收益和非线性认知期望收益模型,研究了投资者的非理性特征对认知期望收益的影响。结果为,在现实的证券市场中,由于投资者的非理性认知和投资者对不确定投资的风险厌恶,投资者对证券投资收益的测算,不是传统金融理论所刻画的理性期望收益（基于历史数据决定或由经典的资本资产定价模型所决定）,而是由投资者的一些非理性特征来决定。     

基于限价指令的最优变现策略

最优变现策略是投资者指在一定时间内变现给定数量的头寸,并使其收益最大化的交易策略.以投资者最优卖价(限价单报价)高于市场实时一档买价的价差为变量,以收益最大化为目标建立随机控制模型,并采用HJB方程转换成一组常微分方程的求解,给出限价单的最优报价策略,利用蒙特卡洛模拟出限价指令策略的交易曲线.该模型同时考虑价格波动风险和未执行风险,并将买卖价差标准化后带入模型,避免了绝对价格的不同所带来的差异.     

基于单位风险收益的资产退出投资组合模型研究

投资者进入证券市场后决定退出的时间是不确定的,因此承担着退出风险,且风险资产退出时需要一定的费用.为此在摩擦市场环境下,提出了利用单位风险收益最大化作为目标函数,构建了基于单位风险收益的资产退出的投资组合模型,并把此模型转化为线性规划来解决.最后用实例说明了此模型的可行性.     

Characterization of Ordovician carbonate reservoirs, southeastern Saskatchewan, Canada

The discovery of the prolific Ordovician Red River reservoirs in 1995 in southeastern Saskatchewan was the catalyst for extensive exploration activity which resulted in the discovery of more than 15 new Red River pools. The best yields of Red River production to date have been from dolomite reservoirs. Understanding the processes of dolomitization is, therefore, crucial for the prediction of the connectivity, spatial distribution and heterogeneity of dolomite reservoirs.The Red River reservoirs in the Midale area consist of 3～4 thin dolomitized zones, with a total thickness of about 20 m, which occur at the top of the Yeoman Formation. Two types of replacement dolomite were recognized in the Red River reservoir: dolomitized burrow infills and dolomitized host matrix. The spatial distribution of dolomite suggests that burrowing organisms played an important role in facilitating the fluid flow in the backfilled sediments. This resulted in penecontemporaneous dolomitization of burrow infills by normal seawater. The dolomite in the host matrix is interpreted as having occurred at shallow burial by evaporitic seawater during precipitation of Lake Almar anhydrite that immediately overlies the Yeoman Formation. However, the low δ18O values of dolomited burrow infills (-5.9‰～ -7.8‰, PDB) and matrix dolomites (-6.6‰～ -8.1‰, avg. -7.4‰ PDB) compared to the estimated values for the late Ordovician marine dolomite could be attributed to modification and alteration of dolomite at higher temperatures during deeper burial, which could also be responsible for its 87Sr/86Sr ratios (0.7084～0.7088) that are higher than suggested for the late Ordovician seawaters (0.7078～0.7080). The trace amounts of saddle dolomite cement in the Red River carbonates are probably related to "cannibalization" of earlier replacement dolomite during the chemical compaction.     

A computer generator for randomly layered structures

AcomputergeneratorforrandomlylayeredstructuresYUJia shun1,2,HEZhen hua2(1.TheInstituteofGeologicalandNuclearSciences,NewZealand;2.StateKeyLaboratoryofOilandGasReservoirGeologyandExploitation,ChengduUniversityofTechnology,China)Abstract:Analgorithmisintrod…     

海南岛地体及其毗邻陆缘晚中生代—新生代古地磁研究和构造演化

本文叙述了对海南岛及其毗邻大陆边缘白垩纪到第四纪地层岩石进行古地磁研究的全部工作过程。通过分析岩石中剩余磁矢量的磁偏角及磁倾角的变化,提出海南岛白垩纪以来经历的构造演化模式如下:早期伴随顺时针旋转而向南迁移,后期伴随逆时针转动并向北运移。联系该地区及邻区的地质、地球物理资料,对海南岛上述的构造地体运动提出以下认识:北部湾内早期有一拉张作用,主要是该作用使湾内地壳显著伸长减薄,形成北部湾盆地。从而导致了海南岛的早期构造运动,而海南岛后期的构造运动则主要是受南海海底扩张的影响。海南地体运动规律的阐明对于了解北部湾油气盆地的形成演化有重要的理论和实际意义。     

Exciton Seebeck in Molecular Systems

Various applications relevant to the exciton dynamics,such as the organic solar cell,the large-area organic light-emitting diodes and the thermoelectricity,are operating under temperature gradient.The potential abnormal behavior of the exicton dynamics driven by the temperature difference may affect the efficiency and performance of the corresponding devices.In the above situations,the exciton dynamics under temperature difference is mixed with     

Achieving Unusual States of Matter Under High Pressure

The elongation method,originally proposed by Imamura was further developed for many years in our group.As a method towards O(N)with high efficiency and high accuracy for any dimensional systems.This treatment designed for one-dimensional(ID)polymers is now available for three-dimensional(3D)systems,but geometry optimization is now possible only for 1D-systems.As an approach toward post-Hartree-Fock,it was also extended to     

《Chinese Science Bulletin》SUBJECT INDEX TO VOLUME 59(2014)

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An on-line scaling method for improving scalability of a database cluster

The explosive growth of the Internet and database applications has driven database to be more scalable and available, and able to support on-line scaling without interrupting service. To support more client's queries without downtime and degrading the response time, more nodes have to be scaled up while the database is running. This paper presents the overview of scalable and available database that satisfies the above characteristics. And we propose a novel on-line scaling method. Our method improves the existing on-line scaling method for fast response time and higher throughputs. Our proposed method reduces unnecessary network use, i.e. , we decrease the number of data copy by reusing the backup data. Also, our on-line scaling operation can be processed parallel by selecting adequate nodes as new node. Our performance study shows that our method results in significant reduction in data copy time.     

An improved R-tree based on childnode''s probability

R-Tree is a good structure for spatial searching. But in this indexing structure,either the sequence of nodes in the same level or sequence of traveling these nodes when queries are made is random. Since the possibility that the object appears in different MBR which have the same parents node is different, if we make the subnode who has the most possibility be traveled first, the time cost will be decreased in most of the cases. In some case, the possibility of a point belong to a rectangle will shows direct proportion with the size of the rectangle. But this conclusion is based on an assumption that the objects are symmetrically distributing in the area and this assumption is not always coming into existence. Now we found a more direct parameter to scale the possibility and made a little change on the structure of R-tree, to increase the possibility of founding the satisfying answer in the front sub trees. We names this structure probability based arranged R-tree (PBAR-tree).     

Integrating GIS Web services based on mediating architecture

The geographic information service is enabled by the advancements in general Web service technology and the focused efforts of the OGC in defining XML-based Web GIS service. Based on these models, this paper addresses the issue of services chaining,the process of combining or pipelining results from several interoperable GIS Web Services to create a customized solution. This paper presents a mediated chaining architecture in which a specific service takes responsibility for performing the process that describes a service chain. We designed the Spatial Information Process Language (SIPL) for dynamic modeling and describing the service chain, also a prototype of the Spatial Information Process Execution Engine (SIPEE) is implemented for executing processes written in SIPL. Discussion of measures to improve the functionality and performance of such system will be included.     

Tracking data management using topology of moving object database system for moving object constrained trajectory in LBS application

Advances in wireless technologies and positioning technologies and spread of wireless devices, an interest in LBS (Location Based Service) is arising. To provide location based service, tracking data should have been stored in moving object database management system (called MODBMS) with proper policies and managed efficiently. So the methods which acquire the location information at regular time intervals then, store and manage have been studied. In this paper, we suggest tracking data management techniques using topology that is corresponding to the moving path of moving object. In our techniques, we update the MODBMS when moving object arrived at a street intersection or a curved road which is represented as the node in topology and predict the location at past and future with attribute of topology and linear function. In this technique, location data that are corresponding to the node in topology are stored, thus reduce the number of update and amount of data. Also in case predicting the location,because topology are used as well as existing location information, accuracy for prediction is increased than applying linear function or spline function.