教师主页移动版

基本信息 研究方向为金融工程和金融风险管理。长期以来一直在复杂系统建模、计算金融与风险管理等领域开展了深入研究，参与研究多项国家级和省部级课题，发表学术论文20多篇，专著1部，专利1项。

教育背景

研究领域 计算金融、金融风险管理、区块链金融

工作履历

讲授课程 《投资学》、《统计学》、《商业银行经营管理》、《金融经济学》、《计量经济学》……

研究领域

研究成果 1、著作邹琳，杨密，马超群，计算金融实验建模方法及其应用研究.第一版.长沙:湖南大学出版社,2014.简介： 本书系统地总结了计算实验金融理论，梳理了人工金融市场的发展脉络。对人工金融市场的建模方法进行了归纳，综述了计算实验方法的应用。从个人行为与羊群行为建模的角度，对股票市场进行理论导向型个人行为建模，计算导向型个人行为建模和个人行为与羊群行为建模，结合中国股票市场的特征，构建了三个人工股票市场，利用计算实验的方法，揭示了中国股票市场的复杂性特征产生的原因以及投资者的行为对股票市场的影响。本书的主要读者对象为从事金融学科领域研究的高校教师、研究生、金融监管机构和各金融机构的决策者及研究人员。 2、论文[1] Lin Zou*, Lijuan Xie, Yuanjing Yang. A double-layer network and the contagion mechanism of China’s financial systemic risk. Journal of Artificial Societies and Social Simulation, 2019, 22(4), DOI: 10.18564/jasss.4122 (SSCI，ESI，一区））  [2]Qiujun Lan, Lin Zou*, Yin Zhou, Linjie He. A supply chain network equilibrium model with a smoothing newton solution scheme. Enterprise Information Systems, 2019, 13(2), DOI: 10.1080/17517575.2018.1539773 (SCI，ESI，三区) [3]Lin Zou, Shiyu Jia, Qiujun Lan, Zhongding Zhou.Research on Blockchain-Based Commercial Paper Financing in Supply Chain . Advances in Intelligent Systems and Interactive Applications, Proceedings of the 4th International Conference on Intelligent, Interactive Systems and Applications (IISA2019), 2019, pp.357-364[4]Lin Zou,Jianan Li,Junjun Zhang. Information and Investors’ Wealth: A Studying in Agent-Based Stock Market[A].ICMSS 2017[C].2017:300-306[5] Lin Zou, Yuanjing Yang, Junjun Zhang. The analysis of implicit mechanism of information on liquidity in an artificial stock market. Int. J. Intelligent Systems Technologies and Applications, 2015, Vol. 14, Nos. 3/4, 302-329 (EI)摘要：In the stock markets, investors rely significantly on the information to make decisions. To study the effects of information dissemination on stock market liquidity, we build an artificial stock market with a two-layered network. This two-layered network is composed of an interpersonal relationship network and a medium network. In the artificial stock market, we study the path of information affecting the liquidity of stock market through changing information sources and information issuing frequency. The experiment results show that with the lower of information issuing frequency, the difference of holdings decided by information between investors will increase and the change of each investor’s holdings in two adjacent periods will increase. The market’s liquidity will increase. Furthermore, with the increase of the proportion of information issuing by public media, the difference of holdings decided by information between investors will gradually increase. The market’s liquidity will increase.[6] 邹琳，杨亚男，马超群. 股票市场混沌演化机制:基于计算实验方法的模拟解释[J]. 系统工程，2013，（7）：8-14.摘要：通过构造一个具有中国特色的人工股票市场，研究混沌的生成机制和混沌动力学过程。在建立基于双向拍卖交易机制的人工股票市场的基础上，进行控制性实验。通过反复实验，挖掘导致股票市场混沌产生的序参量。实验结果表明：政策因子、噪声交易者 、交易者学习进化速度、交易者预测规则集中预测规则的数目和股票市场的流通量是股票市场的序参量，它们的变化会导致市场涌现的动力学特征的改变，并且某些序参量的改变与股票市场混沌动力学特征的出现并不是线性的关系。最后，根据对序参量的分析结果 ，提出了相应的混沌控制方法。Abstract: By constructing an artificial stock market with Chinese characteristics, chaotic generated mechanism and chaotic dynamics process are studied. Based on an order-driven artificial Chinese stock market, this paper conduct controlled experiments.Through repeated experiments, order parameters are digged out which lead to stock market chaos. The result show that policy factor 、noise traders、interval of evolution、the number of traders' forecasting rules and the number of trading cycle are order parameters of stock market, and their change would lead to the change of dynamics characteristics emerged by market. Also it isn't linear relationship between the change of some order parameters and the appearance of stock market chaotic dynamics characteristics. Finally, based on the analysis result of order parameters, this paper put forward corresponding strategies to control chaos.[7] 邹琳，马超群,杨晓光，周忠宝. 不同交易制度下股利支付率对股价影响：基于Agent系统的仿真研究[J]. 系统工程，2011，29（10）：7-13.摘要：一般认为股利政策是股价的重要信号之一，但是不同交易制度下股利对股价影响的研究却相当缺乏。本文从计算金融学的角度，通过计算实验的方法，构建了人工金融市场，分别在做市商的交易机制和双向拍卖交易机制下，研究股利支付的变化对股价的影响。结论表明，在做市商交易机制下，股利不能传递信息，而在双向拍卖交易机制下，投资者可以通过股利来获得股票的信息。这个结论对交易者的投资决策具有指导作用。Abstract: One of important studying content of the signal transmission theory is whether non-anticipative change of dividend will bring non-anticipative change of stock price. Though computational and experimental method, we build an artificial stock market with trading mechanism of the market maker and double auction respectively, and study the relation between dividend and stock price based on computation finance theory. The conclusion indicates that dividend transmits different signs under different trading mechanism that will be very useful for investors. [8] 邹琳，马超群，张虹. 金融混沌Duffing-Holms模型及其控制方法研究——基于OGY方法和非线性同步控制方法[J]. 湖南大学学报（自科版），2011，12：88-92. (EI收录)摘要： 分析并发掘了金融混沌的 Duffing -Holms 模型的序参量, 提出了 Duffing -Holms 模型存在周期解的条件, 这表明可以通过 OGY 方法和非线性同步方法对金融混沌进行控制. 在进行 OGY 控制时, 设定了 Duffing -H olms 模型的一个周期解, 并通过数值模拟将混沌控制到该轨道上, 结果指出要对中国金融市场进行有效的混沌控制, 必须做好充分准备, 对金融市场进行微调. 非线性同步方法的数值模拟结果显示, 可以通过确定一个市场为驱动系统, 另一个为受控响应系统, 控制沪深两市的混沌.Abstract: The order parameter of Duffing -Holms model is analyzed and found out. Existence conditions of Duffing -Holms model's periodic solutions are put forward, which indicates that we can control financial chaos in OGY method and nonlinear synchronous method. One periodic solution is set out before numerical simulation of OGY is done. The conclusion has demonstrated that, to control effectively chaos in Chinese financial market, the government must prepare fully and adjust slowly. Finally, the conclusion of numerical simulation of nonlinear synchronous controlling has demonstrated that the government can control stock markets of Shanghai and Shenzhen by indentifying one market as the driven system and the other as the controlled response system.[9] 马超群，杨密，邹琳. 基于Agent异质行为演化的人工金融市场及其非线性特征研究[J]. 财经理论与实践，2011，32（2）：2-7.摘要：通过构建基于Agent的人工金融市场，试图从交易者个人异质行为演化的角度研究金融市场非线性特征的形成。市场中，Agent依赖个人行为特征，如：情绪、记忆长度等，来同时考虑基本面信息与价格趋势，针对当前市场状态，基于经验认知权衡二者后形成价格预期与交易行为。权重的自适应性更新揭示了个人行为的演化，其通过遗传算法与生成函数进化预测规则来实现。模拟实验表明，在做市商的价格生成机制下，当市场由自信的基本面分析者，技术分析者和自适应性理性交易者组成时，人工金融市场呈现出与真实市场相似的非线性特征---尖峰、厚尾，波动聚集性，长期记忆性以及混沌特征。这为探究导致市场产生非线性特征的行为因素提供了一个计算实验平台。Abstract: This paper explores the formation of financial market’s nonlinear characteristics from the standpoint of the evolution of investor individual’s heterogeneous behavior through an agent-based artificial financial market. In our market, agent will consider fundamental information and price tendency simultaneously relied on personal behavioral characters, such as mood, memory length and so on, make the trade-off between them based on empirical knowledge, then form price expectation and trading behavior to current market state. The adaptive updating of the weight represents the evolution of agent’s behavior, which is realized by the evolution of forecast rules with Genetic Algorithm (GA) and Generation Function (GF). Simulation testing shows that when the market fraction is composed of confident fundamentalist, chartists and adaptively rational agents, artificial financial market appears the same nonlinear characteristics--leptokurtosis, fat tail, clustered volatility, long-term memory and chaos, as real markets do, under a market maker scenario. This provides a computational experiment platform to study these behavioral factors, which cause the market to emerge nonlinear characteristics. [10] 邹琳，马超群，刘钰，崔璨. 基于财富与信息角度的人工股票市场建模及非线性特征形成机理[J]. 系统工程，2010，28（10）：29-35.摘要: 在 Chinrella人工股票市场的交易框架下, 建立了在异质信念模块中增加财富与信息模型的人工股票市场。并通过多次实验, 研究了财富与信息对股票市场非线性特征的影响。结果表明, 收益率的尖峰、厚尾, 波动聚集性, 长期记忆性这三种非线性特征的形成各不相同。 财富分布均匀更多导致收益率的尖峰、厚尾, 长期记忆性产生, 而财富分布不均匀导致收益率波动聚集性的产生; 技术分析者信息处理方面, 不均匀处理更多导致尖峰、厚尾产生, 均匀处理更多导致波动聚集性产生, 利用更多过去信息将更多导致长期记忆性产生。 最后, 从股票市场非线性特征的形成机理角度提出了完善股票市场的建议。Abstract : Under trading framework of Chinrella’s artificial stock market , we build a new artificial stock market to add wealth and information models in heterogeneous belief module . Through many experiments , we study influence of wealth and the information on the nonlinear characteristic of stock market. T he results show that the formations of three nonlinear characteristics such as leptokurtosis, volatility clustering, long memory of returns are different . The even distribution of wealth will more likely to lead to leptokurtosis and long memory of returns , while the uneven distribution o f wealth w ill more likely lead to volatility clustering of returns . W hen technical analysts process information unequally, leptokurtosis will be more likely to occur, whereas volatility clustering w ill be more likely to occur . The use of more past information tends to lead to long memory of returns. Finally , we give some suggestion on how to improve stock markets from the view of formation mechanism of the stock market’s nonlinearity. [11] M. Yang, C. Q. Ma, and L. Zou. Asset pricing under evolution of agent’s behavioral heterogeneity in an artificial financial market [C]. The 2nd International Conference on Information Engineering and Computer Science, 2010,(3):1562-1566.（EI收录）.Abstract : We use the study method of Computational Finance to explore the formation and evolution of asset prices from the standpoint of the evolution of investor individual's heterogeneous behavior through building an agent-based artificial financial market. In our model,agent will consider fundamental information and price tendency simultaneously at each period to form expectation that based on personal characters, such as mood,memory length,adjustment and extrapolation speed.The weight that he relies on both fundamental and technical analysis varies over time,which is the best prediction to current market state from empirical rule-set that has been updated through learning from the market situation with Genetic Algorithm (GA) and individual's trading experience with Generation Function (GF).The adaptive updating of the weight represents the evolution of agent's behavior.The model captures the two prime behaviors of agent and the trade-off between them,which realized by agent's adaptively personal learning. Simulation testing shows that even considering agent's variation of behavior in the market,the market fraction also has to be composed of the proportions of confident fundamentalists,chartists and adaptively rational agents as empirical evidence suggests, which will cause the so-called "stylized facts" in financial time series,under a market maker scenario.The impact of the market fraction varies on asset pricing also has been examined.[12]李红权，邹琳.基于Agent的投资者情绪对于股市演化行为仿真研究[J]. 计算机工程与应用，2009, 45(12): 30-32.摘要： 基于双向拍卖机制作为价格生成机制， 应用遗传算法来进化预测规则， 建立了中国股市的人工金融市场模型， 并在此基础上研究了投资者情绪对于市场演化行为的影响。 研究结果表明人工市场能够产生真实市场演化过程中的混沌动力学行为， 并且市场演化行为随着投资者情绪的变化而变动。这一研究对挖掘中国股票市场的演化规律具有重要意义。Abstract：Based on the double auction mechanism for pricing and the Genetic Algorithm to optimize forecasting rules， this paper proposed a new artificial financial model to simulate China’ s stock market， and moreover， made a study on the effect of investor sentiment on market evolution.The results show that the artificial stock market can generate chaotic dynamics in market evolution which is similar to the study in real markets， and market evolving behaviors change along with investor sentiment.This study would provide new sight for research on financial market evolution rules.[13] 邹琳，马超群，李红权. 中国股市仿真系统建模及其非线性特征研究[J].系统管理学报，2008，17（4）：385-389.摘要： 作为新兴的股票市场 , 中国股票市场还不成熟和完善 , 用传统方法很难建模。在交易者模型中引入了噪声交易者模型 , 并加入政策因子 , 应用遗传算法来进化预测规则 , 建立了 Agent 的价格预期模型。同时根据中国股利收益率偏低的特点 , 建立了中国的股利动力学模型。在此基础上建立了中国股票市场仿真系统。对该系统进行模拟及分析 , 发现仿真系统与真实市场同样主要的非线性动力学特征  — — 分形和混沌动力学特征。这一研究对挖掘中国股票市场的演化规律和混沌动力学产生的关键因素具有重要意义。 Abstract :As an emerging booming stock market , Chinese stock market has not mature nor perfect. It is difficult to model it by using traditional methods. In this paper , we divide traders into rational traders and noise traders and introduce a model of noise traders. Joining policy factor and evolving forecasting rules with GA , we modeling the formation of Agent’s price expectations based on character of Chinese stock market. At same time , we build the dividend dynamic model with the character that the dividend distribution ratios are very low for Chinese stocks. Based on these models ’ we simulate Chinese stock market. Then we compare the characteristic of real stock market and of the artificial stock market and find real stock market and artificial stock market are of same primary nonlinear characteristic 2 fractal and chaos. It is significant to study evolving rules of Chinese stock market and order parameters that lead stock market come into being chaos.[14] Lin Zou, Chaoqun Ma. Agent-based artificial Chinese stock market and nonlinear characteristic analysis[J]. In：Proc of Management Track within WiCOM：Information Systems and Management, 2008.(EI收录)Abstract : In Consideration of the characteristics of the Chinese stock market, we modeled the formation of Agent’s price expectations, with the policy introduced as a factor into the model. We categorized traders as rational traders and noise traders, and constructed a model of noise traders. We also consider the characteristics of the Chinese stock market when we built dividend model. With these models, we simulated the Chinese stock market. Then we compared the characteristics of the real stock market and of an artificial stock market and found the real stock market and the artificial stock market are of the same primary nonlinear characteristics—fractal and chaos. This research is of great significance in capturing the critical factors which characteristics the evolving rules and the chaos dynamics of the Chinese stock market.[15] 马超群，邹琳，李红权. 股票市场的非线性结构与混沌效应检验：基于BDS方法与CR方法[J].湖南大学学报（自然科学版），2008，35（5）：85－88.（EI收录）摘要：在传统研究方法的基础上, 运用Rosenstein 提出的小数据量算法计算最大李雅普诺夫指数, 进而引入BDS与返回临近检验 (CR), 从不同角度对中国股票市场的混沌动力学结构进行分析. 为了避免破坏混沌吸引子的分形结构 , 采用对数线性趋势消除法 (LLD) 进行数据处理. 研究结果表明 , 中国股市具有低维混沌吸引子、对初值敏感依赖性、准周期性等显著的非线性混沌特征. 并就市场混沌的经济含义与应用价值进行了探讨。 Abstract :Based on the analysis of the traditional methods , the small data algorithm originated by Rosenstein was introduced to calculate the maximum Lyapunov exponent , and two types of tests 2 BDS and close return(CR) were used to further analyze the dynamical characteristic of chaotic of Chinese stock markets. For avoiding destroying the fractal structure , we utilized a special method of log -linear detrended (LLD) to process the sample data. The conclusions indicate that the notable chaos dynamics characteristic appear to exhibit in Chinese stock markets , such as a low dimensionality chaos attractor , sensitive dependence on initial values, quasi-periodicity. And the economical implication and application value of chaos was also investigated. [16]李红权，邹琳.股票市场混沌吸引子的特征量——基于G-P算法与小数据量算法[J]. 计算机工程与应用，2007, 6(43): 229-232.摘要： 针对金融时间序列的特点, 论文分析已有混沌特征量算法的基础上, 采用特殊的对数线性趋势消除法( 简记为LLD ) 处理数据、 引入 Rosenstein 提出的小数据量算法等计算最大李雅普诺夫指数以及其它混沌系统的特征量, 对我国证券市场的混沌动力学结构作出了稳健的分析。结果表明中国股市具有显著的非线性混沌特征, 这一结论将为金融理论的研究提供新的方向。 Abstract : This paper firstly discusses traditional arithmetic on the detection of chaos and the characteristics of financial time series.And then using log- linear detrending method , small data set arithmetic proposed by Rosenstein to calculate largest Lyapunov exponents and other detecting techniques , this study examines chaotic structure in China stock market.The results show that the stock market has significantly chaotic dynamics.Our conclusion can provide new approaches for research on financial market theory.[17]Lin Zou, Zhan Zhou. Periodic solutions for nonautonomous discrete-time neural networks. Applied Mathematics Letters, 2006, 19: 174-185 .(SCI源刊)Abstract: In this paper, we theoretically prove the existence of periodic solutions for a nonautonomous discrete-time neural networks by using the topological degree theory. Sufficient conditions are also obtained for the existence of an asymptotically stable periodic solution. As a special case, we obtain the existence of a fixed point to the corresponding autonomous discrete-time neural networks which corrects the error in [W.R. Zhao, W. Lin, R.S.Liu, J. Ruan, Asymptotical stability in discrete-time neural networks, IEEE Trans. Circuits Syst. I 49 (2002)1516–1520]. Numerical simulations are given at the end of the paper.[18] Ma Chaoqun, Li Hongquan, Zou lin, Wu Zhijian. Long-Term Memory in Emerging Markets: Evidence from the Chinese Stock Market. International Journal of Information Technology & Decision Making. 2006, 5(3) : 495-501 .(SCI收录，SSCI收录)Abstract: The notion of long memory, or long-term dependence, has received considerable attention in empirical finance. This paper makes two main contributions. First, the paper aims to provide evidence of nonlinear (long memory) dynamics in the equity market of china. Analysis of market patterns in china market (a typical emerging market) instead of U.S. market (a developed market) will be meaningful because little previous research on the behaviors of emerging markets has been carried out. Secondly, we aim at the comprehensive search of long memory feature in China stock market returns as well as volatility. While many empirical works were done on the detection of long memory in return series, very few investigations focused on the market volatility, though the long-term dependence in volatility may lead to some types of volatility persistence as observed in financial markets and affect volatility forecasts and derivative pricing formulas. So, using modified rescaled range analysis and ARFIMA model testing, this study examined long-term dependence in Chinese stock market returns and volatility. The results show that although the returns themselves contain little serial correlation, the variability of returns has significantly long-term dependence. It would be beneficial to encompass long memory structure to assess the behavior of stock prices and research on financial market theory.[19]李红权,马超群,邹琳.中国证券市场的混沌动力学特征研究[J]. 中国管理科学，2005，13（专辑）：194-200.摘要：证券市场价格行为服从随机游走过程还是混沌动力学过程,一直是近来金融实证研究争论的一个热点.在分析已有研究的基础上,采用特殊的对数线性趋势消除法(简记为LLD)处理数据、使用Rosenstein提出的小数据量算法计算最大李雅普诺夫指数以及其它混沌系统的科学判据,对我国证券市场的混沌动力学结构做出了严谨的分析,结果表明中国股市具有显著的非线性混沌特征,并且阐明了证券市场混沌效应的经济含义与应用价值.这一结论将为研究股票价格行为特征与金融经济学理论提供新的方向.Abstract: Whether the behavior of stock market price follows a random process or is characterized by chaotic dynamics, it has received considerable attention in empirical finance. Firstly, this paper discussed many empirical works done on the detection of chaos in financial time series. And then using log-linear detrending method, small data set arithmetic proposed by Rosentein to calculate largest Lyapunov exponents and other detecting techniques, this study examined chaotic structure in China stock market. The result show that the stock market has significantly chaotic dynamics. In the end, we discussed its economic meaning and practical values. Our conclusion provides new approaches for assessing the behavior of stock price and research on financial market theory.[20]佘升翔，马超群，赵庆华，邹琳. 股票组合的变现策略模型[J]. 统计与决策,2005, (8): 4-6. 摘要：构造股票组合的变现策略模型具有重要的现实意义。本文通过一系列参数定义，在单股票变现模型的基础上纳入股票相关性，建立了股票组合变现的优化模型，并通过一个算例对之进行了验证和演示。[21] 邹琳，周展. 非自治离散神经网络周期解的渐近稳定性[J].湖南大学学报（自然科学版），2003，30（6）：92－93.摘要：在神经网络的应用中,稳定性是一个关键.有些模型存在平衡点,而有些模型存在周期解.神经网络的应用,有些要求这些平衡点或周期解渐近稳定;有些提出了更高的要求,要求平衡点或周期解指数稳定.因此,该文主要研究神经网络周期解的存在性，利用拓扑度原理给出了非自治离散神经网络模型周期解的存在性,给出了非自治离散神经网络模型周期解渐近稳定的充分条件. 3、研究项目[1]金融市场multi-agent异质信息的风险形成机理及预警研究，国家自然科学基金青年基金项目（71301047），主持人，2014.1-2016.12。[2]行为和演化范式下完全人工金融市场建模及应用研究，高等学校博士学科点专项科研基金（20100161120005），主持人，2011.1-2013.12。[3]湖南省基础设施建设投融资体制创新研究,湖南省社科基金，主持人，2010-2011.4、奖励基于计算金融学的中国股票市场混沌动力学特征及风险管理研究,湖南省优秀博士学位论文，2011.25、专利：金融风险管理辅助挖掘分析系统，马超群、兰秋军、陈为民、邹琳、文凤华、张小勇、李红权，2007.5。

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