基于多agent的虚拟股市仿真研究

复杂适应系统的基本思想认为系统的复杂性起源于其中个体的自适应性。该文借助Multi-agent的建模技术,对真实股市和投资者的行为进行合理的约简,设计出具有自适应能力的股民(agent),通过自适应股民的相互行为,从而构建一个虚拟的股票市场。最后对仿真的结果进行分析并展望了未来的研究方向。     

基于 EMD 和 RVM 的股指期货价格预测

提出了一种基于EMD（经验模态分解）与RVM（相关向量机）的股指期货价格预测方法。首先将目标价格序列通过EMD技术进行分解,然后对分解后的分量进行重组得到三个新序列,通过分析这三个新序列的特点,构造不同的RVM模型对每个新序列分别进行预测,最后将三个新序列的预测结果通过RVM组合得到最终预测值。实验结果表明,该方法能取得良好的预测效果。     

优先股的特征和我国的制度设计

优先股是相对普通股而言的金融创新产品,融合了股权与债权两者的优点,投资人既能获取低风险收益,在利益遭遇侵害时又不失产权人应有的权利诉求。因此,在我国资本市场供给失衡的背景下推行优先股制度具有重要的现实意义。     

Stock analysts vs. the crowd: Mutual prediction and the drivers of crowd wisdom

We examine the drivers of crowd wisdom in the financial domain by relating analyst report and social media sentiment via Granger causality (GC) testing based on the wisdom of crowds (WoC) theory. The significance of a large number of the tested time series indicates that analyst reports and social media content are suitable for mutual prediction. We elaborate on the conditions under which crowd cognitive diversity matters, and we derive related measures. The results suggest that the WoC theory can partially explain the GC between the two media types and that both professional analysts and the crowd can outperform one another under favorable circumstances.     

Predicting stock market returns from malicious attacks: A comparative analysis of vector autoregression and time-delayed neural networks

With the growing importance of Internet-based businesses, malicious code attacks on information technology infrastructures have been on the rise. Prior studies have indicated that these malicious attacks are associated with detrimental economic effects on the attacked firms. On the other hand, we conjecture that more intense malicious attacks boost the stock price of information security firms. Furthermore, we use artificial neural networks and vector autoregression analyses as complementary methods to study the relationship between the stock market returns of information security firms and the intensity of malicious attacks, computed as the product of the number of malicious attacks and their severity levels. A major contribution of this work is the resulting time-delayed artificial neural network model that allows stock return predictions and is particularly useful as an investment decision support system for hedge funds and other investors, whose portfolios are at risk of losing market value during malicious attacks.     

虚拟技术在证券商网络中的应用

本文叙述了虚拟技术在通讯、局域网络等方面的具体运用。分析了虚拟技术在证券商网络系统中所产生的作用以及发展前景。     

生产装置中备件智能化库存管理

分析了大型生产企业中影响备件库存的众多因素,提出了一个简单实用的备件库存数学计算公式,并以此为基础开发了备件智能化库存管理软件。     

基于参数模型的利率期限结构估计的实证

为了获得我国利率期限结构估计的可靠模型,对已有的经典模型进行实证检验.选用1997年6月至2004年10月上证所国债市场的月度数据,对利率期限结构估计参数模型中的Nelson-Siegel模型(NS模型)和Svensson模型(SV模型)进行了似然比检验、样本内和样本外的分组拟合优度检验.检验结果表明,NS模型比SV模型更适合于上证所的利率期限结构估计;上证所利率期限结构在1～10a期限期间尤其是5～7a期限期间能够获得可靠的估计;在0～1a和10～20a期限期间估计的可靠性不高.     

我国经理人股票期权的会计计量

文章从计量的属性入手,结合作为衍生金融工具的股票期权的计量来论述经理人股票期权的计量问题.通过介绍国外(主要是美国)对经理人股票期权采用的主要两种计量方法-内在价值法和公允价值法,再结合我国目前经理人股票期权会计处理现状,得出目前我国应采用内在价值法计量股票期权.     

Agent-based computational modeling of the stock price-volume relation

From the perspective of the agent-based model of stock markets, this paper examines the possible explanations for the presence of the causal relation between stock returns and trading volume. Using the agent-based approach, we find that the explanation for the presence of the stock price-volume relation may be more fundamental. Conventional devices such as information asymmetry, reaction asymmetry, noise traders or tax motives are not explicitly required. In fact, our simulation results show that the stock price-volume relation may be regarded as a generic property of a financial market, when it is correctly represented as an evolving decentralized system of autonomous interacting agents. One striking feature of agent-based models is the rich profile of agents' behavior. This paper makes use of the advantage and investigates the micro-macro relations within the market. In particular, we trace the evolution of agents' beliefs and examine their consistency with the observed aggregate market behavior. We argue that a full understanding of the price-volume relation cannot be accomplished unless the feedback relation between individual behavior at the bottom and aggregate phenomena at the top is well understood.