基于Agent的股票价格行为仿真

对于股票市场价格行为的解释一直是现代金融理论的核心问题之一。上世纪80年代以来，基于Agcnt的计算金融学提出：社会经济系统的各种复杂性来源于经济系统中个体(Agent)的适应性行为。该文的基本思路即是借助行为金融学和人工智能研究的成果，采用Agent系统理论和计算机仿真相结合，构建符合现实的仿真股市，并通过适应性个体之间的行为和个体与外界经济环境的交互，对股票市场的价格行为提供一种新颖的理解思路。     

计算金融学与政策模拟的前沿研究动态

面向对象的计算金融学建模方法是一个非常有前景的金融市场分析方法,也是该研究领域的国际前沿与热点问题。基于计算金融学的政策模拟与政策设计研究则是该领域在最近几年的新进展,旨在通过金融市场的仿真实验平台,模拟市场交易者和监管部门的行为,考察各种监管措施和政策可能产生的市场反应。从研究方法、理论进展、研究逻辑、面临的机遇与挑战等几个方面对这一领域的最新研究成果进行了系统地分析与评述。     

高等农业院校金融学专业教学改革构想

随着经济的发展和中国加入WTO后金融市场的逐步对外开放 ,社会对金融人才的要求不断提高 ,而高等农业院校金融学专业的教学改革却明显滞后。深入地分析研究了高等农业院校金融学专业发展中存在的问题和面临的挑战 ,在此基础上提出了高等农业院校金融学专业进行教学改革的构想 ,以便促进其进一步的发展     

面向Agent的分布式多媒体系统分析

分布式多媒体系统是一个复杂的动态系统,传统的面向对象分析方法存在不适应的地方。基于Agent的计算以其良好的自适应性、结构的动态优化和智能化的信息处理而广泛应用于分布式计算环境。该文讨论了基于Agent的分布式多媒体系统的分析与设计。首先分析了分布式多媒体系统的复杂性,指出这种复杂性表现为系统结构的层次性、交互性、行为的不可预测性;在此基础上,阐述了面向对象分析方法在解决复杂系统分析和设计时存在的不足,进而讨论了基于Agent的分析方法,并通过一个实例对方法加以说明。基于Agent的分析方法能够较好地解决多媒体异构环境存储、分布式多媒体对象处理和语义合成表现等问题。     

基于计算实验的公共交通需求预测方法

一般来说,用于交通需求预测的数学模型往往缺少对出行个体微观水平上的异质性和可变交通情景的考虑.针对这些问题,本文提出了一种基于计算实验的公共交通需求预测方法.该方法主要由交通调查、基于Agent的人工交通系统（Artificial transportation system,ATS）和计算实验3部分组成.在出行个体Agent建模中引入BDI（Belief-desire-intention）模型,来推演各出行个体在出行过程中对各交通选择的决策制定过程.在人工交通系统的基础上,可以设计并执行大量的计算实验来进行交通需求预测.本文通过基于校车系统的一系列交通调查和计算实验验证了该方法的可行性和优越性,并针对各种不同交通情景进行了交通分布预测和交通方式划分预测.     

Agent技术在Web数据仓库结构中的应用研究

针对基于Web的数据仓库体系结构存在的问题,在该体系结构中引入软件Agent技术,运用移动Agent技术来解决传统方法难以解决的一些主要问题,提出了一种基于Agent的Web数据仓库系统体系结构。文中发挥数据仓库技术和Web技术结合的优势,重点研究了Agent技术在Web服务器端的应用,在把有用的Web数据集成并入到数据仓库中这一目前的研究热点问题中,提出了基于Agent技术将HTML页面转化为XML数据源的解决方案。此外,文章分别研究了应用服务器端和数据仓库系统中的Agent技术的应用,并提出了将Agent技术引入后实现基于Web的数据仓库体系的关键技术。     

基于元Agent技术的作战个体行为建模

针对虚拟作战个体行为具有智能性和自主性的特点,从行为功能考虑,将影响人员外在行为的内部因素分解为元Agent,提出一种基于元Agent聚集的作战人员行为模型。依据各个主体特点采用智能模型实现其结构,描述感知因素的量化值和可信度,引入收益指标评估意图的远景规划,通过动作执行概率的赋值达到重复作战行为的优先选择。与传统方法相比,该模型充分考虑到个体行为内在因素间的交互耦合和复杂反馈,提高了作战个体战场行为的智能性、自主性和差异性,为作战人员行为建模等问题提供一种新的研究思路。     

FKAOS方法中的Agent实体优化分析研究

利用KAOS目标分析方法,可以获取一些粗糙的Agent实体对象.但其中一些实体对象并不符合Agent的基本特性要求.通过提出"为什么"需要这些Agent的问题,FKAOS方法进一步对粗糙的Agent进行分析,并优化Agent的设计.优化Agent的目标是建立一个充分体现自主实体特性的、规模适中的、任务相对独立的多Agent协同社会体系.提出了3种有效优化Agent的方法:基于责任本体的优化方法、基于需求资源的优化方法和基于交互关系的优化方法.     

基于进化规划的多Agent系统任务调度

Agent任务调度是多Agent系统研究的重要内容之一.调度方法直接影响调度方案的优劣与否和系统的执行效率.进化规划是近年来兴起的一种进化计算方法,具有对实数直接操作及全局寻优能力.将之用于Agent任务调度,建立了Agent任务调度模型,设计了进化规划调度算法.采取多个体竞争策略有效地解决了进化规划的早熟问题.实例验证了这种方法的可行性及性能,进一步的研究是在资源及优先度限制的条件下,如何用进化规划算法解决Agent任务调度问题.     

基于组织的面向Agent 程序设计及其语言Oragent

当前,面向Agent程序设计在支持动态开放多Agent系统开发方面存在一系列的不足,如缺乏高层抽象、底层实现模型与高层设计模型相脱节、在支持系统动态性方面缺乏有效的运行机制和语言设施等.针对这些问题,提出一种基于组织的面向Agent程序设计方法.该方法将组织、Group、角色和Agent等高层抽象作为一阶实体,缩小了多Agent系统的设计模型与实现模型之间的概念鸿沟;借助于组织学中的机制——角色扮演机制、基于角色的交互——支持系统动态性的规约和实现,如Agent行为的动态组合、动态的交互等,基于该程序设计思想,设计了基于组织的面向Agent程序设计语言——Oragent,定义了其抽象语法和形式语义,并通过案例分析说明了如何基于该程序设计思想和Oragent语言来构造和实现动态而灵活的多Agent系统.     

计算技术的重要应用领域——计算金融

1.前言 20世纪70年代后期Black-Scholes的期权定价模型出现后,复杂的数学模型处理、数值分析和大规模计算在金融中的应用越来越多。计算机开始进入金融领域,当时由于受计算机性能,如内存容量和中央处理器运算速度的限制,无法解决金融领域中的大规模和复杂性特征,特别是不断有新金融工具引入的金融创新和日益增加的市场易变性,仅用计算机实现一些简单的统计或其他数值分析。进入21世纪,随着我国加入     

Intelligent agent-assisted adaptive order simulation system in the artificial stock market

Agent-based computational economics (ACE) has received increased attention and importance over recent years. Some researchers have attempted to develop an agent-based model of the stock market to investigate the behavior of investors and provide decision support for innovation of trading mechanisms. However, challenges remain regarding the design and implementation of such a model, due to the complexity of investors, financial information, policies, and so on. This paper will describe a novel architecture to model the stock market by utilizing stock agent, finance agent and investor agent. Each type of investor agent has a different investment strategy and learning method. A prototype system for supporting stock market simulation and evolution is also presented to demonstrate the practicality and feasibility of the proposed intelligent agent-based artificial stock market system architecture.     

Agent-Based Approach to Option Pricing Anomalies

Psychological studies on decision making under uncertainty, which have been inspired by Kahneman and Tversky's study, have attracted considerable interest in financial research as key factors to solve anomalies that cannot be explained by the traditional models. Recently, we proposed an agent-based prospect theoretical model and demonstrated that the loss-aversion feature of investors is capable of explaining a large number of financial stylized facts. This paper aims to extend the previous work to the field of option pricing. Two important anomalies in the field-the implied volatility smile and the skewness premium-will be analyzed. This paper can be considered as an attempt to integrate the behavioral financial theory and the option pricing theory by using the agent-based approach.     

An agent-based simulation model for analyzing the governance of the Brazilian Financial System

Regulation can play an important role in effectively managing systemic risk while providing accountability to all affected governments. IMF points out weak governance structures as one of the main causes for financial/economical crisis. However, research in this area is still limited. One of the reasons is the inherent complexity of the public sector governance notion. In this research, the regulatory governance of the financial sector is conceived as a complex system, in which governance is perceived as a phenomenon resulting from the interactions among all the actors that influence or are influenced by regulatory activities within the financial sector. An agent-based simulation was developed to analyze and evaluate the emergent behaviors from the governance in the Brazilian finance sector under different macroeconomics variables and different attitudes, perceptions and desires of economic and political actors. The agent-based model is combined with an econometric model, which is intended to characterize the macroeconomic environment. The regulatory environment is modeled by computational agents using BDI (beliefs–desires–intentions) architecture. The agents have beliefs about their environment and desires they want to satisfy, thus leading them to create intentions to act. The agents’ behavior was modeled using fuzzy rules built by means of content analysis of newspapers and in-depth interviews with experts from the financial area. Computational experiments demonstrate the potential of the agent-based model simulation in the study of complex environments involving regulatory governance.     

An Agent-Based Approach to Option Pricing Anomalies

Psychological studies on decision-making under uncertainty, which have been inspired by Kahneman and Tversky's study, have attracted considerable interest in financial research as key factors to solve anomalies that cannot be explained by the traditional models. Recently, we proposed an agent-based prospect theoretical model and demonstrated that the loss-aversion feature of investors is capable of explaining a large number of financial stylized facts. This paper aims to extend the previous work to the field of option pricing. Two important anomalies in the field—the implied volatility smile and the skewness premium—will be analyzed. This study can be considered as an attempt to integrate the behavioral financial theory and the option pricing theory by using the agent-based approach.      

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.     

Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model

The behavioral origins of the stylized facts of financial returns have been addressed in a growing body of agent-based models of financial markets. While the traditional efficient market viewpoint explains all statistical properties of returns by similar features of the news arrival process, the more recent behavioral finance models explain them as imprints of universal patterns of interaction in these markets. In this paper we contribute to this literature by introducing a very simple agent-based model in which the ubiquitous stylized facts (fat tails, volatility clustering) are emergent properties of the interaction among traders. The simplicity of the model allows us to estimate the underlying parameters, since it is possible to derive a closed form solution for the distribution of returns. We show that the tail shape characterizing the fatness of the unconditional distribution of returns can be directly derived from some structural variables that govern the traders’ interactions, namely the herding propensity and the autonomous switching tendency.JEL classifications: G12; C61Earlier versions of this paper have been presented at the 11th Symposium of the Society of Nonlinear Dynamics and Econometrics, Florence, March 2003, the 8th Spring Meeting of Young Economists, Leuven, April 2003, the 8th Workshop on Economics with Heterogeneous Interacting Agents, Kiel, May 2003, the 27th congress of Associazione per la Matematica Applicata alle Scienze Economiche e Sociali, Cagliari, September 2003; research seminars at the Department of Econometrics, University of Geneva, March 2003, and at the Department of Physics, University of Cagliari, May 2003, and have gained considerably from comments by many participants in these events.     

互联网金融服务创新对小微企业融资模式影响研究

互联网金融产品对传统金融市场的渗透,给银行业的传统金融服务模式带来巨大的冲击,从政府的政策导向可见互联网金融的冲击力之大。在互联网金融服务与传统金融服务的对碰中,研究小微企业融资模式受到怎样的影响,探索解决小微企业融资难问题的方法,推动小微企业的健康发展有着积极的现实意义。文章首先归纳了互联网金融发展的现状和趋势,互联网金融的内涵及影响,进而从互联网金融模式创新角度分析了互联网金融对小微企业融资模式的影响。     

IBIZA: E-market Infrastructure for Custom-built Information Products

The merger of electronic commerce, intelligent agent and distributed computing technologies over TCP/IP-based platforms enables the creation of electronic markets in new types of products featuring both human and software agents as actors. One such example is a market in custom-built information products. These are information products that have been constructed to meet specific requirements provided by the consumer. Examples include custom research reports, analysis, and computational objects. How should these markets be designed? What are the market mechanisms that should be used to coordinate the interactions between the actors? What should be the decision strategies employed by the software agents that participate in the market? IBIZA is a computational workbench that enables designers to create and simulate electronic markets in information products. It provides a repository of software agents, bidding strategies, brokering strategies and market mechanisms. Using the repository, designers can instantiate particular designs of electronic markets and conduct experiments to study the impact of design decisions on desired objectives. In this paper, we focus on the key technical and economic issues encountered in the design of IBIZA. We illustrate using examples from our work on designing a software agent-based electronic market for automated model development.     

基于Agent的复杂系统分布仿真建模方法的研究

基于Agent的分布仿真是研究大型复杂系统的一种有效的、重要的方法。为了减小复杂系统仿真的复杂度,增加仿真模型的重用和可维护性,需要研究基于Agent分布仿真的建模方法。首先对复杂系统及其特性进行了分析,对基于Agent的仿真进行了全面的论述,然后对基于Agent的复杂系统仿真中的复杂系统建模分析、Agent建模分析以及Agent的分布进行了分析,给出了基于Agent的复杂系统分布仿真的建模步骤,最后给出了在此建模思想指导下的金融证券市场的建模过程。