过度自信、信息与中国证券市场资产价格行为研究
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摘要
过度自信作为有限理性投资者最主要的心理特征之一,通过作用于投资者对于信息结构的处理方式及其交易行为对证券市场中的资产价格行为起着决定作用。因此,在金融市场微观结构理论框架下,基于过度自信及信息流动机制对证券市场资产价格行为的系统研究便格外重要。本文在过度自信视角下基于金融市场微观结构理论和经典信息模型系统的研究过度自信对交易的驱动作用及其对证券市场资产价格行为的影响,从理论和实证角度分析了过度自信对证券市场中资产价格行为的决定作用。全文主要从以下5个方面进行探讨:
1.基于非对称信息和过度自信的交易驱动机理研究。首先从信息经济学的角度,区别于以往的研究,利用Nyholm模型度量超高频知情交易概率,重点研究了交易活跃程度和非对称信息之间的超高频特性,更加透彻地分析交易持续期间、交易量、知情交易变化的原因,对每一笔交易过程的深入研究为各变量之间的相互影响关系提供有力支持;其次,基于经典信息模型和理性预期框架,本部分在引入公共信息考虑信息结构环境的前提下,建立状态依赖过度自信模型,考察当市场中不存在噪音交易者时信息结构是如何作用于过度自信的投资者,并通过影响其对信息的处理方式从而对交易策略和市场的均衡资产价格产生影响的,从信息流动机制和市场微观结构角度分析历史收益和交易量之间的内在关系,为交易驱动研究提供全新的视角和解释。
2.投资者过度自信与我国证券市场量价关系研究。本文通过构建适用于我国证券市场的计量模型,考察了整个证券市场、行业和个股的过度自信效应。首先从整个市场的角度,通过市场行情数据研究了投资者行为以及过度自信效应,并实证检验了市场收益和市场交易量之间的领先滞后关系;其次进一步分析了市场收益和个股交易量之间的跨期动态关系,并将不同行业股票作为整体来分别对其过度自信效应和处置效应进行研究,这样不仅可以使我们综合考察我国整个股市周期中过度自信效应的表现特征,更是可以让我们从行业和个股的层面深入探究过度自信效应的截面差异性,揭示了各个行业过度自信效应异同的经验原因。
3.投资者过度自信与证券市场波动性关系研究。本文不同于以往学者对于我国证券市场过度自信效应的检验思路和方法,主要使用市场和个股的行情数据,首先对我国上证和深证两个A股市场进行整体综合考察,从整体市场角度分析过度自信在交易量之谜这个金融异象上的解释力;其次在行业和个股层面上深入探究过度自信和波动性关系的截面差异,随后更是进一步按照公司规模和交易活跃程度分组讨论过度自信你和波动性之间的相互作用,不仅使我们从整体市场的角度对过度自信与波动性之间的作用机制有所把握,而且深入细致的探究了不同行业、个股特征下过度自信与波动性之间关系的异同,并进行了合理的理论和经验阐释。
4.投资者过度自信与市场质量。本文不仅基于市场指数高频数据系统构建了包含市场深度和市场有效性在内的动态指标体系,而且在此基础上深入探讨过度自信与市场质量之间的联系,揭示出了过度自信与波动性、流动性、市场深度和有效性等表征市场质量指标之间的动态关系,首次对我国证券市场过度自信与市场质量之间的动态关系进行整体综合考察,在市场和个股的角度探究过度自信与市场质量之间的内在作用。不仅拓宽了国内学者基于市场微观结构对行为金融理论研究的视角,而且为有关机构制定政策提供合理的科学依据。
5.投资者过度自信和股票动量策略的交叉套利研究。本文首先基于信息模型研究框架,通过拓展引入特定信息结构环境和投资者过度自信参数构建了可以直接度量市场中过度自信交易概率的序贯交易理论模型,并运用合理方法对模型进行参数估计,突破性的解决了过度自信难以度量的问题;其次,利用估计所得时变的过度自信指标,在此基础上进一步构建投资组合和交叉策略,对我国市场中过度自信与动量效应的关系展开研究,首次从实证检验的角度从投资者有限理性的角度对我国动量效应的产生原因进行解释。
Overconfidence is one of the defining psychological traits of irrational investors. It affects their information processing and trading behavior, and thus influence assets’prices in the security market. Therefore, it is important to study assets’price behavior based on human overconfidence and mechanism of information flow within the framework of the theory of financial market microstructure. This paper is based on the theory of financial market microstructure and the classic information model. It is a systematic analysis of how overconfidence drives transactions and how it affects asset price behavior both theoretically and empirically. This analysis consists of five main parts:
1. The research is about the driving force of transactions based on asymmetric information and over-confidence. Firstly, it’s different from traditional economic researches in that it measures ultra-high-frequency probability of informed trading with the Nyholm model, studies ultra-high-frequency characteristic between transaction activity and asymmetric information in particular, and analyses more thoroughly the reasons for changes of transactions’duration, volume, and informed trading. Those in-depth researches on each transaction clearly show the relations between all variables. Secondly, this paper takes the environment of information structure into consideration, referring to public information. It sets up a state -dependent overconfidence model based on classic information model and the framework of rational expectation. It studies how information structure influences overconfident investors’information processing, hence their trading strategy and the equilibrium prices of assets in the market when there’s not noise traders. It studies the intrinsic relations between historical yield and volume of transactions from the perspective of information flow and microstructure, which is a new way to explain the driving force of transactions.
2. This paper continues to study overconfidence and price volume relations in China’s security market. It sets up a quantitative model to measure the effect of overconfidence upon different industries, stocks and the security market as a whole. Firstly, it looks at the whole market, observes investor behavior and overconfidence effect based on data collected from the market. It empirically tests the time relations between yield and transaction volume in the market. Secondly, it further analyzed the dynamic relations between yield and transaction volume of individual stocks. It treats stocks in different industries as a whole and studies the effect upon it of overconfidence and disposition respectively. This enables us not only to observe the traits of overconfidence effect in a whole cycle of security market in China, but also to study the cross-sectional differences of overconfidence effect in individual industries and stocks, thus to find empirical reasons for such differences.
3. Relations between investor overconfidence and volatility in the security market. Measures taken to study overconfidence effect in this paper is different from those traditionally used. It collects data of individual stocks and the market as a whole and 1) observes exchanges of Shanghai and Shenzhen– the two A share markets in China– to study the extent to which overconfidence can be applied to explain the mysterious financial phenomenon of unknown transaction volume. 2) It studies the cross-sectional differences of the relations between over-confidence and volatility based on different industries and stocks, then continue to discuss the interactions between over-confidence and volatility by groups divided according to company size and transaction dynamism. In this way, we can not only understand the interaction between over-confidence and volatility, but also do in-depth research of the differences and similarities in different industries and stocks of the relations between the two, thus explain the mechanism and our experience.。
4. Investor overconfidence and market quality. This paper sets up a dynamic index system which includes variables such as market depth and efficiency based on the high frequency market index data. It also discusses deeply the relations between overconfidence and market quality, reveals the dynamic relations between different quality indices such as overconfidence, volatility, liquidity, market depth and efficiency. This is the first comprehensive study of the dynamic relations between over-confidence and market quality in China’s security market. It studies in the intrinsic interactions of the two from the perspective of both the market and individual stocks. It broadens domestic scholars’perspective in term of theoretical research in Behavioral Finance based on microstructure. It also builds reliable scientific grounds for governments’policy making.
5. Investor overconfidence and cross-arbitrage using momentum strategy in stock trading. 1) The paper is based on the framework of information model. It builds up a theoretical model of sequential trading that can directly measure the probability of overconfidential transactions in the market, using parameters of overconfidence and specific information structure environment. It estimates parameters in a rational way and thus enables the measurement of overconfidence. 2) It builds up investment portfolio and cross-over strategy upon the estimated overconfidence index, studies the relations between overconfidence and the momentum effect in China’s market, and for the first time explains the reasons for momentum effect in China through the perspectives of both empirical tests and irrational investors.
1.基于非对称信息和过度自信的交易驱动机理研究。首先从信息经济学的角度,区别于以往的研究,利用Nyholm模型度量超高频知情交易概率,重点研究了交易活跃程度和非对称信息之间的超高频特性,更加透彻地分析交易持续期间、交易量、知情交易变化的原因,对每一笔交易过程的深入研究为各变量之间的相互影响关系提供有力支持;其次,基于经典信息模型和理性预期框架,本部分在引入公共信息考虑信息结构环境的前提下,建立状态依赖过度自信模型,考察当市场中不存在噪音交易者时信息结构是如何作用于过度自信的投资者,并通过影响其对信息的处理方式从而对交易策略和市场的均衡资产价格产生影响的,从信息流动机制和市场微观结构角度分析历史收益和交易量之间的内在关系,为交易驱动研究提供全新的视角和解释。
2.投资者过度自信与我国证券市场量价关系研究。本文通过构建适用于我国证券市场的计量模型,考察了整个证券市场、行业和个股的过度自信效应。首先从整个市场的角度,通过市场行情数据研究了投资者行为以及过度自信效应,并实证检验了市场收益和市场交易量之间的领先滞后关系;其次进一步分析了市场收益和个股交易量之间的跨期动态关系,并将不同行业股票作为整体来分别对其过度自信效应和处置效应进行研究,这样不仅可以使我们综合考察我国整个股市周期中过度自信效应的表现特征,更是可以让我们从行业和个股的层面深入探究过度自信效应的截面差异性,揭示了各个行业过度自信效应异同的经验原因。
3.投资者过度自信与证券市场波动性关系研究。本文不同于以往学者对于我国证券市场过度自信效应的检验思路和方法,主要使用市场和个股的行情数据,首先对我国上证和深证两个A股市场进行整体综合考察,从整体市场角度分析过度自信在交易量之谜这个金融异象上的解释力;其次在行业和个股层面上深入探究过度自信和波动性关系的截面差异,随后更是进一步按照公司规模和交易活跃程度分组讨论过度自信你和波动性之间的相互作用,不仅使我们从整体市场的角度对过度自信与波动性之间的作用机制有所把握,而且深入细致的探究了不同行业、个股特征下过度自信与波动性之间关系的异同,并进行了合理的理论和经验阐释。
4.投资者过度自信与市场质量。本文不仅基于市场指数高频数据系统构建了包含市场深度和市场有效性在内的动态指标体系,而且在此基础上深入探讨过度自信与市场质量之间的联系,揭示出了过度自信与波动性、流动性、市场深度和有效性等表征市场质量指标之间的动态关系,首次对我国证券市场过度自信与市场质量之间的动态关系进行整体综合考察,在市场和个股的角度探究过度自信与市场质量之间的内在作用。不仅拓宽了国内学者基于市场微观结构对行为金融理论研究的视角,而且为有关机构制定政策提供合理的科学依据。
5.投资者过度自信和股票动量策略的交叉套利研究。本文首先基于信息模型研究框架,通过拓展引入特定信息结构环境和投资者过度自信参数构建了可以直接度量市场中过度自信交易概率的序贯交易理论模型,并运用合理方法对模型进行参数估计,突破性的解决了过度自信难以度量的问题;其次,利用估计所得时变的过度自信指标,在此基础上进一步构建投资组合和交叉策略,对我国市场中过度自信与动量效应的关系展开研究,首次从实证检验的角度从投资者有限理性的角度对我国动量效应的产生原因进行解释。
Overconfidence is one of the defining psychological traits of irrational investors. It affects their information processing and trading behavior, and thus influence assets’prices in the security market. Therefore, it is important to study assets’price behavior based on human overconfidence and mechanism of information flow within the framework of the theory of financial market microstructure. This paper is based on the theory of financial market microstructure and the classic information model. It is a systematic analysis of how overconfidence drives transactions and how it affects asset price behavior both theoretically and empirically. This analysis consists of five main parts:
1. The research is about the driving force of transactions based on asymmetric information and over-confidence. Firstly, it’s different from traditional economic researches in that it measures ultra-high-frequency probability of informed trading with the Nyholm model, studies ultra-high-frequency characteristic between transaction activity and asymmetric information in particular, and analyses more thoroughly the reasons for changes of transactions’duration, volume, and informed trading. Those in-depth researches on each transaction clearly show the relations between all variables. Secondly, this paper takes the environment of information structure into consideration, referring to public information. It sets up a state -dependent overconfidence model based on classic information model and the framework of rational expectation. It studies how information structure influences overconfident investors’information processing, hence their trading strategy and the equilibrium prices of assets in the market when there’s not noise traders. It studies the intrinsic relations between historical yield and volume of transactions from the perspective of information flow and microstructure, which is a new way to explain the driving force of transactions.
2. This paper continues to study overconfidence and price volume relations in China’s security market. It sets up a quantitative model to measure the effect of overconfidence upon different industries, stocks and the security market as a whole. Firstly, it looks at the whole market, observes investor behavior and overconfidence effect based on data collected from the market. It empirically tests the time relations between yield and transaction volume in the market. Secondly, it further analyzed the dynamic relations between yield and transaction volume of individual stocks. It treats stocks in different industries as a whole and studies the effect upon it of overconfidence and disposition respectively. This enables us not only to observe the traits of overconfidence effect in a whole cycle of security market in China, but also to study the cross-sectional differences of overconfidence effect in individual industries and stocks, thus to find empirical reasons for such differences.
3. Relations between investor overconfidence and volatility in the security market. Measures taken to study overconfidence effect in this paper is different from those traditionally used. It collects data of individual stocks and the market as a whole and 1) observes exchanges of Shanghai and Shenzhen– the two A share markets in China– to study the extent to which overconfidence can be applied to explain the mysterious financial phenomenon of unknown transaction volume. 2) It studies the cross-sectional differences of the relations between over-confidence and volatility based on different industries and stocks, then continue to discuss the interactions between over-confidence and volatility by groups divided according to company size and transaction dynamism. In this way, we can not only understand the interaction between over-confidence and volatility, but also do in-depth research of the differences and similarities in different industries and stocks of the relations between the two, thus explain the mechanism and our experience.。
4. Investor overconfidence and market quality. This paper sets up a dynamic index system which includes variables such as market depth and efficiency based on the high frequency market index data. It also discusses deeply the relations between overconfidence and market quality, reveals the dynamic relations between different quality indices such as overconfidence, volatility, liquidity, market depth and efficiency. This is the first comprehensive study of the dynamic relations between over-confidence and market quality in China’s security market. It studies in the intrinsic interactions of the two from the perspective of both the market and individual stocks. It broadens domestic scholars’perspective in term of theoretical research in Behavioral Finance based on microstructure. It also builds reliable scientific grounds for governments’policy making.
5. Investor overconfidence and cross-arbitrage using momentum strategy in stock trading. 1) The paper is based on the framework of information model. It builds up a theoretical model of sequential trading that can directly measure the probability of overconfidential transactions in the market, using parameters of overconfidence and specific information structure environment. It estimates parameters in a rational way and thus enables the measurement of overconfidence. 2) It builds up investment portfolio and cross-over strategy upon the estimated overconfidence index, studies the relations between overconfidence and the momentum effect in China’s market, and for the first time explains the reasons for momentum effect in China through the perspectives of both empirical tests and irrational investors.
引文
[1]Simon H A. Rational choice and the structure of the environment[J]. Psychological review. 1956, 63(2): 129-138.
[2]Newell A, Simon H A. Human problem solving[M]. Prentice-Hall Englewood Cliffs, NJ, 1972.
[3]Kahneman D, Tversky A. Prospect theory: An analysis of decision under risk[J]. Econometrica: Journal of the Econometric Society. 1979, 47(2): 263-291.
[4]De Bondt W, Thaler R. Does the stock market overreact[J]. Journal of Finance. 1985, 40(3): 793-805.
[5]Shefrin H, Statman M. The disposition to sell winners too early and ride losers too long: Theory and evidence[J]. Journal of Finance. 1985, 40(3): 777-790.
[6]Shleifer A. Inefficient markets: An introduction to behavioral finance[M]. Oxford University Press, USA, 2000.
[7]Chuang W I, Lee B S. An empirical evaluation of the overconfidence hypothesis[J]. Journal of Banking and Finance. 2006, 30(9): 2489-2515.
[8]Markowitz H. Portfolio selection[J]. Journal of finance. 1952, 7(1): 77-91.
[9]Sharpe W F. Capital asset prices: A theory of market equilibrium under conditions of risk[J]. Journal of finance. 1964, 19(3): 425-442.
[10]Linter J. The Valuation of Risky Assets and the Selection of Risky Investments in Stock Portfolios and Budget Constraints[J]. Review of Economics and Statistics, February. 1965.
[11]Black F, Jensen M C, Scholes M. The capital asset pricing model: Some empirical tests[J]. Studies in the theory of capital markets. 1972, 81: 79-121.
[12]Cox J C, Ross S A. The valuation of options for alternative stochastic processes[J]. Journal of financial Economics. 1976, 3(1-2): 145-166.
[13]Ross S A. A simple approach to the valuation of risky streams[J]. Journal of Business. 1978, 51(3): 453-475.
[14]Fama E F. Efficient capital markets: A review of theory and empirical work[J]. Journal of finance. 1970: 383-417.
[15]Fischhoff B, Kahneman D, Slovic P, et al. Judgment under uncertainty: Heuristics and biases[J]. Science. 1974, 185: 1124-1131.
[16]Shefrin H. Beyond greed and fear: Understanding behavioral finance and the psychology of investing[M]. Oxford University Press, USA, 2002.
[17]Oskamp S. Overconfidence in case-study judgments[J]. Journal of consulting psychology. 1965, 29(3): 261-265.
[18]Fischhoff B, Slovic P, Lichtenstein S. Knowing with certainty: The appropriateness of extreme confidence[J]. Journal of Experimental Psychology. 1977, 3(4): 552-564.
[19]Koriat A, Lichtenstein S, Fischhoff B. Reasons for confidence.[J]. Journal of Experimental Psychology: Human Learning and Memory. 1980, 6(2): 107-118.
[20]Fischhoff B, Slovic P, Lichtenstein S. Lay foibles and expert fables in judgments about risk[J]. American Statistician. 1982, 36(3): 240-255.
[21]Russo J E, Schoemaker P. Managing overconfidence[J]. Sloan Management Review. 1992, 33(2): 7-17.
[22]Daniel K, Hirshleifer D, Subrahmanyam A. Investor psychology and security market under-and overreactions[J]. Journal of finance. 1998, 53(6): 1839-1885.
[23]Gervais S, Odean T. Learning To Become Overconfident[J]. Review of Financial Studies. 2001, 14: 1.
[24]Weinstein N D. Unrealistic optimism about future life events[J]. Journal of personality and social psychology. 1980, 39(5): 806-820.
[25]Keren G. On the calibration of probability judgments: Some critical comments and alternative perspectives[J]. Journal of Behavioral Decision Making. 1997, 10(3): 269-278.
[26]Russo J E, Schoemaker P. Managing overconfidence[J]. Sloan Management Review. 1992, 33(2): 7-17.
[27]Kahneman D, Slovic P, Tversky A. Judgment under uncertainty: Heuristics and biases[M]. Cambridge University Press, 1982.
[28]Tversky A, Kahneman D. Availability: A heuristic for judging frequency and probability[J]. Cognitive psychology. 1973, 5(2): 207-232.
[29]Griffin D, Tversky A. The weighing of evidence and the determinants of confidence[J]. Cognitive Psychology. 1992, 24(3): 411-435.
[30]Lundeberg M A, Fox P W, Punccohar J. Highly confident but wrong: Gender differences and similarities in confidence judgments.[J]. Journal of EducationalPsychology. 1994, 86(1): 114-121.
[31]Webster R L, Ellis T S. Men's and women's self-confidence in performing financial analysis[J]. Psychological reports. 1996, 79(3): 1251-1254.
[32]Barber B M, Odean T. Boys Will be Boys: Gender, Overconfidence, and Common Stock Investment[J]. Quarterly Journal of Economics. 2001, 116(1): 261-292.
[33]Gigerenzer G. How to make cognitive illusions disappear: Beyond "heuristics and biases"[J]. European review of social psychology. 1991, 2(1): 83-115.
[34]Odean T. Volume, volatility, price, and profit when all traders are above average[J]. Journal of finance. 1998, 53(6): 1887-1934.
[35]Kyle A S. Continuous auctions and insider trading[J]. Econometrica: Journal of the Econometric Society. 1985, 53(6): 1315-1335.
[36]Grossman S J, Stiglitz J E. On the impossibility of informationally efficient markets[J]. The American Economic Review. 1980, 70(3): 393-408.
[37]Barberis N, Shleifer A, Vishny R. A model of investor sentiment[J]. Journal of Financial Economics. 1998, 49(3): 307-343.
[38]Hong H, Stein J C. A unified theory of underreaction, momentum trading, and overreaction in asset markets[J]. Journal of finance. 1999, 54(6): 2143-2184.
[39]Odean T. Do investors trade too much[J]. American Economic Review. 1999, 89(5): 1279-1298.
[40]Barber B M, Odean T. Boys Will be Boys: Gender, Overconfidence, and Common Stock Investment[J]. Quarterly Journal of Economics. 2001, 116(1): 261-292.
[41]Barber B M, Odean T. Online investors: do the slow die first[J]. Review of Financial Studies. 2002, 15(2): 455.
[42]Glaser M, Weber M. Overconfidence and trading volume[J]. The Geneva Risk and Insurance Review. 2007, 32(1): 1-36.
[43]Statman M, Thorley S, Vorkink K. Investor overconfidence and trading volume[J]. Review of Financial Studies. 2006, 19(4): 1531.
[44]Lin M C. Returns and Investor Behavior in Taiwan: Does Overconfidence Explain this Relationship[J]. Review of Pacific Basin Financial Markets and Policies. 2005, 8(03): 405-446.
[45]Barber B M, Odean T. Trading is hazardous to your wealth: The common stock investment performance of individual investors[J]. Journal of Finance. 2000, 55(2):773-806.
[46]Deaves R, Luders E, Luo G Y. An experimental test of the impact of overconfidence and gender on trading activity[J]. Review of Finance. 2009, 13(3): 555.
[47]Régner I, Hilton D, Cabantous L, et al. Overconfidence, miscalibration and positive illusions[R]. Working paper, University of Toulouse, 2004.
[48]吴卫星.汪勇祥和梁衡义,过度自信,有限参与和资产价格泡沫[J].经济研究. 2006(004).
[49]程兵,梁衡义,肖宇谷.动量和反转投资策略在我国股市中的实证分析[J].财经问题研究. 2004(008): 29-35.
[50]杨春鹏,吴冲锋.行为金融:过度自信与混合期望收益模型[J].当代经济科学. 2004, 26(001): 25-28.
[51]李心丹,王冀宁.中国个体证券投资者交易行为的实证研究[J].经济研究. 2002(011): 54-63.
[52]谭松涛,王亚平.股民过度交易了么?——基于中国某证券营业厅数据的研究[J].经济研究. 2006, 41(010): 83-95.
[53]Kirchler E, Maciejovsky B. Simultaneous over-and underconfidence: Evidence from experimental asset markets[J]. Journal of Risk and Uncertainty. 2002, 25(1): 65-85.
[54]Biais B, Hilton D, Mazurier K, et al. Judgemental overconfidence, self-monitoring, and trading performance in an experimental financial market[J]. Review of Economic Studies. 2005: 287-312.
[55]Kirchler E, Maciejovsky B. Simultaneous over-and underconfidence: Evidence from experimental asset markets[J]. Journal of Risk and Uncertainty. 2002, 25(1): 65-85.
[56]高鸿桢,林嘉永.信息不对称资本市场的实验研究[J].经济研究. 2005, 2.
[57]Bagehot W. The Only Game in Town[J]. Financial Analysts Journal. 1971: 12-14.
[58]Admati A R, Pfleiderer P. A theory of intraday patterns: Volume and price variability[J]. Review of Financial Studies. 1988: 3-40.
[59]Diamond D W, Verrecchia R E. Constraints on short-selling and asset price adjustment to private information[J]. Journal of Financial Economics. 1987, 18(2): 277-311.
[60]Easley D, O'Hara M. Time and the process of security price adjustment[J]. Journal of Finance. 1992, 47(2): 577-605.
[61]Manganelli S. Duration, volume and volatility impact of trades[J]. Journal of Financial markets. 2005, 8(4): 377-399.
[62]房振明,王春峰,曹媛媛.上海证券市场流动性模式的研究[J].管理工程学报. 2005, 19(002): 33-39.
[63]黄杰鲲.电子指令驱动市场上的交易持续期与知情交易的相互关系研究[J].南方经济. 2006(001):5-21.
[64]周开国,何兴强,柴俊.股票交易活跃性,流动性与基于信息的交易——对H股的微观结构分析[J].财经问题研究. 2006(008): 50-59.
[65]Easley D, Kiefer N M, O'Hara M, et al. Liquidity, information, and infrequently traded stocks[J]. Journal of Finance. 1996, 51(4): 1405-1436.
[66]Nyholm K. Inferring the private information content of trades: a regime-switching approach[J]. Journal of Applied Econometrics.2003, 18(4): 457-470.
[67]Engle R F, Russell J R. Autoregressive conditional duration: A new model for irregularly spaced transaction data[J]. Econometrica. 1998, 66(5): 1127-1162.
[68]Engle R F. The econometrics of ultra-high-frequency data[J]. Econometrica. 2003, 68(1): 1-22.
[69]Andersen T G, Bollerslev T. Intraday periodicity and volatility persistence in financial markets[J]. Journal of empirical finance. 1997, 4(2-3): 115-158.
[70]Benos A V. Aggressiveness and survival of overconfident traders[J]. Journal of Financial Markets. 1998, 1(3-4): 353-383.
[71]Kyle A S, Wang F A. Speculation duopoly with agreement to disagree: can overconfidence survive the market test?[J]. Journal of Finance. 1997, 52(5): 2073-2090.
[72]Hirshleifer D. Investor psychology and asset pricing[J]. Journal of Finance. 2001, 56(4): 1533-1597.
[73]Griffin J M, Nardari F, Stulz R M. Do investors trade more when stocks have performed well? Evidence from 46 countries[J]. Review of Financial Studies. 2007, 20(3): 905.
[74]刘端,陈收.投资者过度信心与处置效应对交易的驱动作用研究[J].系统工程. 2007, 25(009): 1-9.
[75]Grossman S. On the efficiency of competitive stock markets where trades have diverse information[J]. Journal of Finance. 1976: 573-585.
[76]Karpoff J M. The relation between price changes and trading volume: A survey[J]. Journal of Financial and quantitative Analysis. 1987, 22(1): 109-126.
[77]Stoll H R, Whaley R E. Program trading and expiration-day effects[J]. Financial Analysts Journal. 1987, 43(2): 16-28.
[78]Bessembinder H, Seguin P J. Price volatility, trading volume, and market depth: Evidence from futures markets[J]. Journal of Financial and Quantitative Analysis. 1993, 28(1): 21-39.
[79]Chordia T, Roll R, Subrahmanyam A. Market liquidity and trading activity[J]. Journal of Finance. 2001, 56(2): 501-530.
[80]Lo A W, Wang J. Trading volume: Definitions, data analysis, and implications of portfolio theory[J]. Review of Financial Studies. 2000, 13(2): 257.
[81]Lee C, Swaminathan B. Price momentum and trading volume[J]. Journal of Finance. 2000, 55(5): 2017-2069.
[82]Gervais S, Kaniel R, Mingelgrin D H. The high-volume return premium[J]. Journal of Finance. 2001: 877-919.
[83]Milton H, Raviv A. Differences of Opinion Make a Horse Race[J]. Review of Financial Studies. 1993, 6(3).
[84]Shalen C T. Volume, volatility, and the dispersion of beliefs[J]. Review of Financial Studies. 1993, 6(2): 405-434.
[85]Bessembinder H, Chan K, Seguin P J. An empirical examination of information, differences of opinion, and trading activity[J]. Journal of Financial Economics. 1996, 40(1): 105-134.
[86]Ross S A. Information and volatility: The no-arbitrage martingale approach to timing and resolution irrelevancy[J]. Journal of Finance. 1989: 1-17.
[87]Shefrin H, Statman M. The disposition to sell winners too early and ride losers too long: Theory and evidence[J]. Journal of Finance. 1985, 40(3): 777-790.
[88]Runkle D E. Vector autoregressions and reality[J]. Journal of Business and Economic Statistics. 2002, 20(1): 128-133.
[89]Cooper M. Filter rules based on price and volume in individual security overreaction[J]. Review of Financial Studies. 1999, 12(4): 901.
[90]Griffin D, Tversky A. The weighing of evidence and the determinants of confidence[J]. Cognitive Psychology. 1992, 24(3): 411-435.
[91]Shiller R J. The use of volatility measures in assessing market efficiency[J]. Journal of Finance. 1981, 36(2): 291-304.
[92]Campbell J Y, Cochrane J H. By force of habit: A consumption-based explanation of aggregate stock market behavior[J]. Journal of political Economy. 1999, 107(2):205-251.
[93]Scheinkman J A, Xiong W. Overconfidence and speculative bubbles[J]. Journal of Political Economy. 2003, 111(6).
[94]Lamoureux C G, Lastrapes W D. Persistence in variance, structural change, and the GARCH model[J]. Journal of Business & Economic Statistics. 1990, 8(2): 225-234.
[95]Lee B S, Rui O M. The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence[J]. Journal of Banking and Finance. 2002, 26(1): 51-78.
[96]Bohl M T, Henke H. Trading volume and stock market volatility: The Polish case[J]. International Review of Financial Analysis. 2003, 12(5): 513-525.
[97]王承炜,吴冲锋.中国股市价格—交易量的线性及非线性因果关系研究[J].管理科学学报. 2002, 5(004): 7-12.
[98]孔东民,毕秋侠.股票收益率波动的异方差:基于交易量及异质信息分解的检验[J].南开管理评论. 2006, 9(003): 92-97.
[99]Wang C, Sun Q, Chee S L. The Behavior and Performance of Individual Investors in China. National University of Singapore working paper.
[100]Nelson D B. Conditional heteroskedasticity in asset returns: A new approach[J]. Econometrica: Journal of the Econometric Society. 1991, 59(2): 347-370.
[101]Glosten L R, Jagannathan R, Runkle D E. On the relation between the expected value and the volatility of the nominal excess return on stocks[J]. Journal of finance. 1993, 48(5): 1779-1801.
[102]李胜利.中国股票市场杠杆效应研究[J].证券市场导报. 2002, 10: 10-14.
[103]Daniel K, Hirshleifer D. A. Subrahmanyam, 2001, Overconfidence, Arbitrage, and Equilibrium Asset Pricing[J]. Journal of Finance. , 56(3): 921-965.
[104]García D, Sangiorgi F, Uro Evi B. Overconfidence and market efficiency with heterogeneous agents[J]. Economic Theory. 2007, 30(2): 313-336.
[105]Ko K J, Huang Z. Arrogance can be a virtue: Overconfidence, information acquisition, and market efficiency[J]. Journal of Financial Economics. 2007, 84(2): 529-560.
[106]Madhavan A. Market microstructure: A survey[J]. Journal of Financial Markets. 2000, 3(3): 205-258.
[107]Philip D E, Steil B. Institutional Investors[Z]. Cambridge, Massachusetts, 2001.
[108]Merton R C. On estimating the expected return on the market: An exploratoryinvestigation[J]. Journal of Financial Economics. 1980, 8(4): 323-361.
[109]Andersen T G, Bollerslev T, Diebold F X. A framework for exploring the macroeconomic determinants of systematic risk[J]. American Economic Review. 2005, 95(2): 398-404.
[110]Stoll H R. Friction[J]. Journal of Finance. 2000, 55(4): 1479-1514.
[111]Bandi F M, Russell J R. Separating microstructure noise from volatility[J]. Journal of Financial Economics. 2006, 79(3): 655-692.
[112]Bandi F M, Russell J R, Zhu Y. Using high-frequency data in dynamic portfolio choice[J]. Econometric Reviews. 2008, 27(1): 163-198.
[113]Jegadeesh N, Titman S. Returns to buying winners and selling losers: Implications for stock market efficiency[J]. Journal of finance. 1993, 48(1): 65-91.
[114]Jegadeesh N, Titman S. Profitability of momentum strategies: An evaluation of alternative explanations[J]. Journal of Finance. 2001, 56(2): 699-720.
[115]Chan L, Jegadeesh N, Lakonishok J. Momentum strategies[J]. Journal of Finance. 1996, 51(5): 1681-1713.
[116]Conrad J, Kaul G. An anatomy of trading strategies[J]. Review of Financial Studies. 1998, 11(3): 489.
[117]Rouwenhorst K G. International momentum strategies[J]. Journal of Finance. 1998, 53(1): 267-284.
[118]Ahmet B, Nusret C. Do markets overreact? International evidence[J]. Journal of Banking and Finance. 1999, 23: 1121-1144.
[119]Chui A, Titman S, Wei K. Momentum, legal systems and ownership structure: An analysis of Asian stock markets[J]. Hong Kong University of Science and Technology. 2000.
[120]Griffin J M, Ji X, Martin J S. Momentum investing and business cycle risk: Evidence from pole to pole[J]. Journal of Finance. 2003, 58(6): 2515-2547.
[121]吴世农,沈艺峰.中国证券市场过度反应了吗[J]. 1999.
[122]王永宏,赵学军.中国股市惯性策略和反转策略的实证分析[J].证券市场导报. 2001(006): 28-33.
[123]周琳杰.中国股票市场动量策略赢利性研究[J].世界经济. 2002(008): 60-64.
[124]吴世农,吴超鹏.我国股票市场“价格惯性策略”和“盈余惯性策略”的实证研究[J].经济科学. 2003(004): 41-50.
[125]林秀梅,方毅.中国股市动量投资策略和逆向投资策略的实证研究[J].数量经济技术经济研究. 2004(010): 141-152.
[126]邵晓阳,苏敬勤,于圣睿.沪市A股反转效应与惯性效应实证研究[J].当代经济管理. 2005, 27(002): 96-101.
[127]贺学会,陈诤.基于牛市和熊市不同周期的股票市场动量效应研究[J].财经理论与实践. 2006, 27(005): 40-44.
[128]张强,杨淑娥,杨红.中国股市投资者情绪与股票收益的实证研究[J].系统工程. 2007, 25(007): 13-17.
[129]Lesmond D A, Schill M J, Zhou C. The illusory nature of momentum profits[J]. Journal of Financial Economics. 2004, 71(2): 349-380.
[130]George T J, Hwang C Y. The 52-week high and momentum investing[J]. Journal of Finance. 2004, 59(5): 2145-2176.
[131]Daniel K, Titman S. Evidence on the characteristics of cross sectional variation in stock returns[J]. Journal of Finance. 1997, 52(1): 1-33.
[132]Hong H, Lim T, Stein J C. Bad news travels slowly: Size, analyst coverage, and the profitability of momentum strategies[J]. Journal of Finance. 2000, 55(1): 265-295.
[133]Fama E F, Kenneth R. French, 1996, Multifactor explanations of asset pricing anomalies[J]. Journal of Finance. , 51(1): 55-84.
[134]Jegadeesh N, Titman S. Cross-sectional and time-series determinants of momentum returns[J]. Review of Financial Studies. 2002, 15(1): 143.
[135]Conrad J, Kaul G. An anatomy of trading strategies[J]. Review of Financial Studies. 1998, 11(3): 489.
[136]Chordia T, Shivakumar L. Momentum, business cycle, and time-varying expected returns[J]. Journal of Finance. 2002, 57(2): 985-1019.
[137]Chordia T, Shivakumar L. Earnings and price momentum[J]. Journal of Financial Economics. 2006, 80(3): 627-656.
[138]Barberis N, Shleifer A, Vishny R. A model of investor sentiment[J]. Journal of Financial Economics. 1998, 49(3): 307-343.
[139]Hong H S. JC. An unified Theory of underreaction, momentum trading and overreaction in asset markets[J]. Journal of Finance. 1999, 54: 2143-2184.
[140]Barberis N, Huang M, Santos T. Prospect Theory and Asset Prices[J]. Quarterly Journal of Economics. 2001, 116(1): 1-53.
[141]Grinblatt M, Han B. The disposition effect and momentum[Z]. National Bureau of Economic Research Cambridge, Mass., USA, 2002.
[142]Glosten L R, Milgrom P. Bid, ask and transaction prices in a market-maker market with heterogeneously informed traders[J]. Journal of Financial Economics.1985, 14: 71-100.
[143]Easley D, O'Hara M. Price, trade size, and information in securities markets[J]. Journal of Financial economics. 1987, 19(1): 69-90.
[144]Easley D, Kiefer N M, O'Hara M. One day in the life of a very common stock[J]. Review of Financial Studies. 1997: 805-835.
[145]Easley D, Kiefer N M, O'Hara M, et al. Liquidity, information, and infrequently traded stocks[J]. Journal of Finance. 1996, 51(4): 1405-1436.
[146]Easley D, Kiefer N M, O'Hara M. The information content of the trading process[J]. Journal of Empirical Finance. 1997, 4(2-3): 159-186.
[2]Newell A, Simon H A. Human problem solving[M]. Prentice-Hall Englewood Cliffs, NJ, 1972.
[3]Kahneman D, Tversky A. Prospect theory: An analysis of decision under risk[J]. Econometrica: Journal of the Econometric Society. 1979, 47(2): 263-291.
[4]De Bondt W, Thaler R. Does the stock market overreact[J]. Journal of Finance. 1985, 40(3): 793-805.
[5]Shefrin H, Statman M. The disposition to sell winners too early and ride losers too long: Theory and evidence[J]. Journal of Finance. 1985, 40(3): 777-790.
[6]Shleifer A. Inefficient markets: An introduction to behavioral finance[M]. Oxford University Press, USA, 2000.
[7]Chuang W I, Lee B S. An empirical evaluation of the overconfidence hypothesis[J]. Journal of Banking and Finance. 2006, 30(9): 2489-2515.
[8]Markowitz H. Portfolio selection[J]. Journal of finance. 1952, 7(1): 77-91.
[9]Sharpe W F. Capital asset prices: A theory of market equilibrium under conditions of risk[J]. Journal of finance. 1964, 19(3): 425-442.
[10]Linter J. The Valuation of Risky Assets and the Selection of Risky Investments in Stock Portfolios and Budget Constraints[J]. Review of Economics and Statistics, February. 1965.
[11]Black F, Jensen M C, Scholes M. The capital asset pricing model: Some empirical tests[J]. Studies in the theory of capital markets. 1972, 81: 79-121.
[12]Cox J C, Ross S A. The valuation of options for alternative stochastic processes[J]. Journal of financial Economics. 1976, 3(1-2): 145-166.
[13]Ross S A. A simple approach to the valuation of risky streams[J]. Journal of Business. 1978, 51(3): 453-475.
[14]Fama E F. Efficient capital markets: A review of theory and empirical work[J]. Journal of finance. 1970: 383-417.
[15]Fischhoff B, Kahneman D, Slovic P, et al. Judgment under uncertainty: Heuristics and biases[J]. Science. 1974, 185: 1124-1131.
[16]Shefrin H. Beyond greed and fear: Understanding behavioral finance and the psychology of investing[M]. Oxford University Press, USA, 2002.
[17]Oskamp S. Overconfidence in case-study judgments[J]. Journal of consulting psychology. 1965, 29(3): 261-265.
[18]Fischhoff B, Slovic P, Lichtenstein S. Knowing with certainty: The appropriateness of extreme confidence[J]. Journal of Experimental Psychology. 1977, 3(4): 552-564.
[19]Koriat A, Lichtenstein S, Fischhoff B. Reasons for confidence.[J]. Journal of Experimental Psychology: Human Learning and Memory. 1980, 6(2): 107-118.
[20]Fischhoff B, Slovic P, Lichtenstein S. Lay foibles and expert fables in judgments about risk[J]. American Statistician. 1982, 36(3): 240-255.
[21]Russo J E, Schoemaker P. Managing overconfidence[J]. Sloan Management Review. 1992, 33(2): 7-17.
[22]Daniel K, Hirshleifer D, Subrahmanyam A. Investor psychology and security market under-and overreactions[J]. Journal of finance. 1998, 53(6): 1839-1885.
[23]Gervais S, Odean T. Learning To Become Overconfident[J]. Review of Financial Studies. 2001, 14: 1.
[24]Weinstein N D. Unrealistic optimism about future life events[J]. Journal of personality and social psychology. 1980, 39(5): 806-820.
[25]Keren G. On the calibration of probability judgments: Some critical comments and alternative perspectives[J]. Journal of Behavioral Decision Making. 1997, 10(3): 269-278.
[26]Russo J E, Schoemaker P. Managing overconfidence[J]. Sloan Management Review. 1992, 33(2): 7-17.
[27]Kahneman D, Slovic P, Tversky A. Judgment under uncertainty: Heuristics and biases[M]. Cambridge University Press, 1982.
[28]Tversky A, Kahneman D. Availability: A heuristic for judging frequency and probability[J]. Cognitive psychology. 1973, 5(2): 207-232.
[29]Griffin D, Tversky A. The weighing of evidence and the determinants of confidence[J]. Cognitive Psychology. 1992, 24(3): 411-435.
[30]Lundeberg M A, Fox P W, Punccohar J. Highly confident but wrong: Gender differences and similarities in confidence judgments.[J]. Journal of EducationalPsychology. 1994, 86(1): 114-121.
[31]Webster R L, Ellis T S. Men's and women's self-confidence in performing financial analysis[J]. Psychological reports. 1996, 79(3): 1251-1254.
[32]Barber B M, Odean T. Boys Will be Boys: Gender, Overconfidence, and Common Stock Investment[J]. Quarterly Journal of Economics. 2001, 116(1): 261-292.
[33]Gigerenzer G. How to make cognitive illusions disappear: Beyond "heuristics and biases"[J]. European review of social psychology. 1991, 2(1): 83-115.
[34]Odean T. Volume, volatility, price, and profit when all traders are above average[J]. Journal of finance. 1998, 53(6): 1887-1934.
[35]Kyle A S. Continuous auctions and insider trading[J]. Econometrica: Journal of the Econometric Society. 1985, 53(6): 1315-1335.
[36]Grossman S J, Stiglitz J E. On the impossibility of informationally efficient markets[J]. The American Economic Review. 1980, 70(3): 393-408.
[37]Barberis N, Shleifer A, Vishny R. A model of investor sentiment[J]. Journal of Financial Economics. 1998, 49(3): 307-343.
[38]Hong H, Stein J C. A unified theory of underreaction, momentum trading, and overreaction in asset markets[J]. Journal of finance. 1999, 54(6): 2143-2184.
[39]Odean T. Do investors trade too much[J]. American Economic Review. 1999, 89(5): 1279-1298.
[40]Barber B M, Odean T. Boys Will be Boys: Gender, Overconfidence, and Common Stock Investment[J]. Quarterly Journal of Economics. 2001, 116(1): 261-292.
[41]Barber B M, Odean T. Online investors: do the slow die first[J]. Review of Financial Studies. 2002, 15(2): 455.
[42]Glaser M, Weber M. Overconfidence and trading volume[J]. The Geneva Risk and Insurance Review. 2007, 32(1): 1-36.
[43]Statman M, Thorley S, Vorkink K. Investor overconfidence and trading volume[J]. Review of Financial Studies. 2006, 19(4): 1531.
[44]Lin M C. Returns and Investor Behavior in Taiwan: Does Overconfidence Explain this Relationship[J]. Review of Pacific Basin Financial Markets and Policies. 2005, 8(03): 405-446.
[45]Barber B M, Odean T. Trading is hazardous to your wealth: The common stock investment performance of individual investors[J]. Journal of Finance. 2000, 55(2):773-806.
[46]Deaves R, Luders E, Luo G Y. An experimental test of the impact of overconfidence and gender on trading activity[J]. Review of Finance. 2009, 13(3): 555.
[47]Régner I, Hilton D, Cabantous L, et al. Overconfidence, miscalibration and positive illusions[R]. Working paper, University of Toulouse, 2004.
[48]吴卫星.汪勇祥和梁衡义,过度自信,有限参与和资产价格泡沫[J].经济研究. 2006(004).
[49]程兵,梁衡义,肖宇谷.动量和反转投资策略在我国股市中的实证分析[J].财经问题研究. 2004(008): 29-35.
[50]杨春鹏,吴冲锋.行为金融:过度自信与混合期望收益模型[J].当代经济科学. 2004, 26(001): 25-28.
[51]李心丹,王冀宁.中国个体证券投资者交易行为的实证研究[J].经济研究. 2002(011): 54-63.
[52]谭松涛,王亚平.股民过度交易了么?——基于中国某证券营业厅数据的研究[J].经济研究. 2006, 41(010): 83-95.
[53]Kirchler E, Maciejovsky B. Simultaneous over-and underconfidence: Evidence from experimental asset markets[J]. Journal of Risk and Uncertainty. 2002, 25(1): 65-85.
[54]Biais B, Hilton D, Mazurier K, et al. Judgemental overconfidence, self-monitoring, and trading performance in an experimental financial market[J]. Review of Economic Studies. 2005: 287-312.
[55]Kirchler E, Maciejovsky B. Simultaneous over-and underconfidence: Evidence from experimental asset markets[J]. Journal of Risk and Uncertainty. 2002, 25(1): 65-85.
[56]高鸿桢,林嘉永.信息不对称资本市场的实验研究[J].经济研究. 2005, 2.
[57]Bagehot W. The Only Game in Town[J]. Financial Analysts Journal. 1971: 12-14.
[58]Admati A R, Pfleiderer P. A theory of intraday patterns: Volume and price variability[J]. Review of Financial Studies. 1988: 3-40.
[59]Diamond D W, Verrecchia R E. Constraints on short-selling and asset price adjustment to private information[J]. Journal of Financial Economics. 1987, 18(2): 277-311.
[60]Easley D, O'Hara M. Time and the process of security price adjustment[J]. Journal of Finance. 1992, 47(2): 577-605.
[61]Manganelli S. Duration, volume and volatility impact of trades[J]. Journal of Financial markets. 2005, 8(4): 377-399.
[62]房振明,王春峰,曹媛媛.上海证券市场流动性模式的研究[J].管理工程学报. 2005, 19(002): 33-39.
[63]黄杰鲲.电子指令驱动市场上的交易持续期与知情交易的相互关系研究[J].南方经济. 2006(001):5-21.
[64]周开国,何兴强,柴俊.股票交易活跃性,流动性与基于信息的交易——对H股的微观结构分析[J].财经问题研究. 2006(008): 50-59.
[65]Easley D, Kiefer N M, O'Hara M, et al. Liquidity, information, and infrequently traded stocks[J]. Journal of Finance. 1996, 51(4): 1405-1436.
[66]Nyholm K. Inferring the private information content of trades: a regime-switching approach[J]. Journal of Applied Econometrics.2003, 18(4): 457-470.
[67]Engle R F, Russell J R. Autoregressive conditional duration: A new model for irregularly spaced transaction data[J]. Econometrica. 1998, 66(5): 1127-1162.
[68]Engle R F. The econometrics of ultra-high-frequency data[J]. Econometrica. 2003, 68(1): 1-22.
[69]Andersen T G, Bollerslev T. Intraday periodicity and volatility persistence in financial markets[J]. Journal of empirical finance. 1997, 4(2-3): 115-158.
[70]Benos A V. Aggressiveness and survival of overconfident traders[J]. Journal of Financial Markets. 1998, 1(3-4): 353-383.
[71]Kyle A S, Wang F A. Speculation duopoly with agreement to disagree: can overconfidence survive the market test?[J]. Journal of Finance. 1997, 52(5): 2073-2090.
[72]Hirshleifer D. Investor psychology and asset pricing[J]. Journal of Finance. 2001, 56(4): 1533-1597.
[73]Griffin J M, Nardari F, Stulz R M. Do investors trade more when stocks have performed well? Evidence from 46 countries[J]. Review of Financial Studies. 2007, 20(3): 905.
[74]刘端,陈收.投资者过度信心与处置效应对交易的驱动作用研究[J].系统工程. 2007, 25(009): 1-9.
[75]Grossman S. On the efficiency of competitive stock markets where trades have diverse information[J]. Journal of Finance. 1976: 573-585.
[76]Karpoff J M. The relation between price changes and trading volume: A survey[J]. Journal of Financial and quantitative Analysis. 1987, 22(1): 109-126.
[77]Stoll H R, Whaley R E. Program trading and expiration-day effects[J]. Financial Analysts Journal. 1987, 43(2): 16-28.
[78]Bessembinder H, Seguin P J. Price volatility, trading volume, and market depth: Evidence from futures markets[J]. Journal of Financial and Quantitative Analysis. 1993, 28(1): 21-39.
[79]Chordia T, Roll R, Subrahmanyam A. Market liquidity and trading activity[J]. Journal of Finance. 2001, 56(2): 501-530.
[80]Lo A W, Wang J. Trading volume: Definitions, data analysis, and implications of portfolio theory[J]. Review of Financial Studies. 2000, 13(2): 257.
[81]Lee C, Swaminathan B. Price momentum and trading volume[J]. Journal of Finance. 2000, 55(5): 2017-2069.
[82]Gervais S, Kaniel R, Mingelgrin D H. The high-volume return premium[J]. Journal of Finance. 2001: 877-919.
[83]Milton H, Raviv A. Differences of Opinion Make a Horse Race[J]. Review of Financial Studies. 1993, 6(3).
[84]Shalen C T. Volume, volatility, and the dispersion of beliefs[J]. Review of Financial Studies. 1993, 6(2): 405-434.
[85]Bessembinder H, Chan K, Seguin P J. An empirical examination of information, differences of opinion, and trading activity[J]. Journal of Financial Economics. 1996, 40(1): 105-134.
[86]Ross S A. Information and volatility: The no-arbitrage martingale approach to timing and resolution irrelevancy[J]. Journal of Finance. 1989: 1-17.
[87]Shefrin H, Statman M. The disposition to sell winners too early and ride losers too long: Theory and evidence[J]. Journal of Finance. 1985, 40(3): 777-790.
[88]Runkle D E. Vector autoregressions and reality[J]. Journal of Business and Economic Statistics. 2002, 20(1): 128-133.
[89]Cooper M. Filter rules based on price and volume in individual security overreaction[J]. Review of Financial Studies. 1999, 12(4): 901.
[90]Griffin D, Tversky A. The weighing of evidence and the determinants of confidence[J]. Cognitive Psychology. 1992, 24(3): 411-435.
[91]Shiller R J. The use of volatility measures in assessing market efficiency[J]. Journal of Finance. 1981, 36(2): 291-304.
[92]Campbell J Y, Cochrane J H. By force of habit: A consumption-based explanation of aggregate stock market behavior[J]. Journal of political Economy. 1999, 107(2):205-251.
[93]Scheinkman J A, Xiong W. Overconfidence and speculative bubbles[J]. Journal of Political Economy. 2003, 111(6).
[94]Lamoureux C G, Lastrapes W D. Persistence in variance, structural change, and the GARCH model[J]. Journal of Business & Economic Statistics. 1990, 8(2): 225-234.
[95]Lee B S, Rui O M. The dynamic relationship between stock returns and trading volume: Domestic and cross-country evidence[J]. Journal of Banking and Finance. 2002, 26(1): 51-78.
[96]Bohl M T, Henke H. Trading volume and stock market volatility: The Polish case[J]. International Review of Financial Analysis. 2003, 12(5): 513-525.
[97]王承炜,吴冲锋.中国股市价格—交易量的线性及非线性因果关系研究[J].管理科学学报. 2002, 5(004): 7-12.
[98]孔东民,毕秋侠.股票收益率波动的异方差:基于交易量及异质信息分解的检验[J].南开管理评论. 2006, 9(003): 92-97.
[99]Wang C, Sun Q, Chee S L. The Behavior and Performance of Individual Investors in China. National University of Singapore working paper.
[100]Nelson D B. Conditional heteroskedasticity in asset returns: A new approach[J]. Econometrica: Journal of the Econometric Society. 1991, 59(2): 347-370.
[101]Glosten L R, Jagannathan R, Runkle D E. On the relation between the expected value and the volatility of the nominal excess return on stocks[J]. Journal of finance. 1993, 48(5): 1779-1801.
[102]李胜利.中国股票市场杠杆效应研究[J].证券市场导报. 2002, 10: 10-14.
[103]Daniel K, Hirshleifer D. A. Subrahmanyam, 2001, Overconfidence, Arbitrage, and Equilibrium Asset Pricing[J]. Journal of Finance. , 56(3): 921-965.
[104]García D, Sangiorgi F, Uro Evi B. Overconfidence and market efficiency with heterogeneous agents[J]. Economic Theory. 2007, 30(2): 313-336.
[105]Ko K J, Huang Z. Arrogance can be a virtue: Overconfidence, information acquisition, and market efficiency[J]. Journal of Financial Economics. 2007, 84(2): 529-560.
[106]Madhavan A. Market microstructure: A survey[J]. Journal of Financial Markets. 2000, 3(3): 205-258.
[107]Philip D E, Steil B. Institutional Investors[Z]. Cambridge, Massachusetts, 2001.
[108]Merton R C. On estimating the expected return on the market: An exploratoryinvestigation[J]. Journal of Financial Economics. 1980, 8(4): 323-361.
[109]Andersen T G, Bollerslev T, Diebold F X. A framework for exploring the macroeconomic determinants of systematic risk[J]. American Economic Review. 2005, 95(2): 398-404.
[110]Stoll H R. Friction[J]. Journal of Finance. 2000, 55(4): 1479-1514.
[111]Bandi F M, Russell J R. Separating microstructure noise from volatility[J]. Journal of Financial Economics. 2006, 79(3): 655-692.
[112]Bandi F M, Russell J R, Zhu Y. Using high-frequency data in dynamic portfolio choice[J]. Econometric Reviews. 2008, 27(1): 163-198.
[113]Jegadeesh N, Titman S. Returns to buying winners and selling losers: Implications for stock market efficiency[J]. Journal of finance. 1993, 48(1): 65-91.
[114]Jegadeesh N, Titman S. Profitability of momentum strategies: An evaluation of alternative explanations[J]. Journal of Finance. 2001, 56(2): 699-720.
[115]Chan L, Jegadeesh N, Lakonishok J. Momentum strategies[J]. Journal of Finance. 1996, 51(5): 1681-1713.
[116]Conrad J, Kaul G. An anatomy of trading strategies[J]. Review of Financial Studies. 1998, 11(3): 489.
[117]Rouwenhorst K G. International momentum strategies[J]. Journal of Finance. 1998, 53(1): 267-284.
[118]Ahmet B, Nusret C. Do markets overreact? International evidence[J]. Journal of Banking and Finance. 1999, 23: 1121-1144.
[119]Chui A, Titman S, Wei K. Momentum, legal systems and ownership structure: An analysis of Asian stock markets[J]. Hong Kong University of Science and Technology. 2000.
[120]Griffin J M, Ji X, Martin J S. Momentum investing and business cycle risk: Evidence from pole to pole[J]. Journal of Finance. 2003, 58(6): 2515-2547.
[121]吴世农,沈艺峰.中国证券市场过度反应了吗[J]. 1999.
[122]王永宏,赵学军.中国股市惯性策略和反转策略的实证分析[J].证券市场导报. 2001(006): 28-33.
[123]周琳杰.中国股票市场动量策略赢利性研究[J].世界经济. 2002(008): 60-64.
[124]吴世农,吴超鹏.我国股票市场“价格惯性策略”和“盈余惯性策略”的实证研究[J].经济科学. 2003(004): 41-50.
[125]林秀梅,方毅.中国股市动量投资策略和逆向投资策略的实证研究[J].数量经济技术经济研究. 2004(010): 141-152.
[126]邵晓阳,苏敬勤,于圣睿.沪市A股反转效应与惯性效应实证研究[J].当代经济管理. 2005, 27(002): 96-101.
[127]贺学会,陈诤.基于牛市和熊市不同周期的股票市场动量效应研究[J].财经理论与实践. 2006, 27(005): 40-44.
[128]张强,杨淑娥,杨红.中国股市投资者情绪与股票收益的实证研究[J].系统工程. 2007, 25(007): 13-17.
[129]Lesmond D A, Schill M J, Zhou C. The illusory nature of momentum profits[J]. Journal of Financial Economics. 2004, 71(2): 349-380.
[130]George T J, Hwang C Y. The 52-week high and momentum investing[J]. Journal of Finance. 2004, 59(5): 2145-2176.
[131]Daniel K, Titman S. Evidence on the characteristics of cross sectional variation in stock returns[J]. Journal of Finance. 1997, 52(1): 1-33.
[132]Hong H, Lim T, Stein J C. Bad news travels slowly: Size, analyst coverage, and the profitability of momentum strategies[J]. Journal of Finance. 2000, 55(1): 265-295.
[133]Fama E F, Kenneth R. French, 1996, Multifactor explanations of asset pricing anomalies[J]. Journal of Finance. , 51(1): 55-84.
[134]Jegadeesh N, Titman S. Cross-sectional and time-series determinants of momentum returns[J]. Review of Financial Studies. 2002, 15(1): 143.
[135]Conrad J, Kaul G. An anatomy of trading strategies[J]. Review of Financial Studies. 1998, 11(3): 489.
[136]Chordia T, Shivakumar L. Momentum, business cycle, and time-varying expected returns[J]. Journal of Finance. 2002, 57(2): 985-1019.
[137]Chordia T, Shivakumar L. Earnings and price momentum[J]. Journal of Financial Economics. 2006, 80(3): 627-656.
[138]Barberis N, Shleifer A, Vishny R. A model of investor sentiment[J]. Journal of Financial Economics. 1998, 49(3): 307-343.
[139]Hong H S. JC. An unified Theory of underreaction, momentum trading and overreaction in asset markets[J]. Journal of Finance. 1999, 54: 2143-2184.
[140]Barberis N, Huang M, Santos T. Prospect Theory and Asset Prices[J]. Quarterly Journal of Economics. 2001, 116(1): 1-53.
[141]Grinblatt M, Han B. The disposition effect and momentum[Z]. National Bureau of Economic Research Cambridge, Mass., USA, 2002.
[142]Glosten L R, Milgrom P. Bid, ask and transaction prices in a market-maker market with heterogeneously informed traders[J]. Journal of Financial Economics.1985, 14: 71-100.
[143]Easley D, O'Hara M. Price, trade size, and information in securities markets[J]. Journal of Financial economics. 1987, 19(1): 69-90.
[144]Easley D, Kiefer N M, O'Hara M. One day in the life of a very common stock[J]. Review of Financial Studies. 1997: 805-835.
[145]Easley D, Kiefer N M, O'Hara M, et al. Liquidity, information, and infrequently traded stocks[J]. Journal of Finance. 1996, 51(4): 1405-1436.
[146]Easley D, Kiefer N M, O'Hara M. The information content of the trading process[J]. Journal of Empirical Finance. 1997, 4(2-3): 159-186.
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