现有研究发现，中国证券市场存在盈利季节性的股市异象：处于盈利淡季的股票在盈余公告期间会比处于旺季的股票获得更大的累计超额收益。如果管理层在盈余公告前发布业绩预告，能否有效地抑制投资者的非理性预期、降低盈余公告期间盈利季节性的股市异象？本文以2010至2020年A股上市公司为样本，分析发现：首先，A股市场在业绩预告期间也存在盈利季节性的股市异象。处于盈利淡季的公司在业绩预告期间比处于盈利旺季的公司平均可多获得2.1%的累计超额收益；其次，盈余公告和业绩预告期间，处于盈利淡季的公司比处于盈利旺季的公司有更大的股价波动率和股票交易量。第三，在盈余公告前发布业绩预告，能显著抑制盈余公告期间盈利季节性对收益率、股价波动率和股票交易量的预测能力。第四，自愿性业绩预告、与盈余公告的间隔时间越短的业绩预告抑制作用更明显。在更换盈利、盈利季节性、累计超额收益测度指标等一系列稳健性检验后，结论依然存在。表明管理层业绩预告能有效地降低投资者的非理性预期，提高股票定价效率。研究结果对市场建设和投资者决策均有一定的借鉴意义。

本文研究股票市场中的交易量权重价格动态均衡，用最大交易量权重价格表示价格参照点或均衡点。我们假设日内股价由于动量效应不断地偏离该价格均衡点，又由于反转效应重新返回，并且交易量权重在价格区间的分布服从一组解析的交易量权重价格动态均衡模型。通过量化动量交易、反转交易和相互作用交易，我们构建了价量概率波二阶微分方程，得到了交易量权重价格动态均衡的数学模型，并且用相互一致性偏好来解释该动态均衡的形成机制。利用我国 A 股市场每笔交易的高频数据进行实证检验，表明了该模型的有效性。交易量权重价格动态均衡模型的数学表达式包含了期望效用理论、前景理论和反射理论的主要内容，具有很好的应用前景，例如可以建立相互作用条件下的动态均衡风险模型及其风险管理。

基于电商平台的消费信贷的出现，给金融监管者带来了新的挑战。本文利用模型分析了电商平台消费信贷的经济福利影响，并得到四个结论：第一，如果银行无法提供充足的消费信贷，那么电商平台就有激励提供信贷，以支持规模经济并扩大交易量。第二，电商平台提供的消费信贷越多，它们的市场势力就越大，就会带来更多的效率损失。第三，电商平台消费信贷扩充了货币政策的信贷传输渠道。第四，由于消费者存在现时偏见，电商平台相比银行更有可能过度授信。这些结论值得监管机构关注。

随着互联网金融在我国的发展，网络借贷产品在家庭资产配置中逐渐受到青睐。本文以 2010 年 1 月 1 日至 2014 年 12 月 31 日中国日均交易量最大的 P2P 平台——红岭创投（www.my089.com）所有有效成功借款为研究样本， 发现股票市场投资者情绪对于网络借贷溢酬的整体线性影响为正向的溢出效应， 但适度情绪下的溢出效应与极端情绪下的传染效 应共同作用的结果在高次项加入回归时发现存在降低-提高-降低的 S 型效应， 说明在极端情绪下，负向的传染效会成为主导。 进一步利用借款项目逾期情况与借款基本信息进行 Probit 回归， 发现高潜在违约率的项目股市的投资者情绪对借款溢酬的影响仍符合 S 型， 但低潜在违约率的项目传染效应会弱化， 这说明投资者能够在极端情绪下识别低风险项目， 并能发 现它的避险功能。

It has been long that literature in financial academics focuses mainly on price and return but much less on trading volume. In the past twenty years, it has already linked both price and trading volume to economic fundamentals, and explored the behavioral implications of trading volume such as investor’s attitude toward risks, overconfidence, disagreement, and attention etc. However, what is surprising is how little we really know about trading volume. Here we show that trading volume probability represents the frequency of market crowd’s trading action in terms of behavior analysis, and test two adaptive hypotheses relevant to the volume uncertainty associated with price in China stock market. The empirical work reveals that market crowd trade a stock in efficient adaptation except for simple heuristics, gradually tend to achieve agreement on an outcome or an asset price widely on a trading day, and generate such a stationary equilibrium price very often in interaction and competition among themselves no matter whether it is highly overestimated or underestimated. This suggests that asset prices include not only a fundamental value but also private information, speculative, sentiment, attention, gamble, and entertainment values etc. Moreover, market crowd adapt to gain and loss by trading volume increase or decrease significantly in interaction with environment in any two consecutive trading days. Our results demonstrate how interaction between information and news, the trading action, and return outcomes in the three-term feedback loop produces excessive trading volume which includes various internal and external causes. Finally, we reconcile market dynamics and crowd’s trading behaviors in a unified framework by Shi’s price-volume differential equation in stock market where, we assume, investors derive a liquidity utility expressed in terms of trading wealth which is equal to the sum of a probability weighting utility and a reversal utility in reference to an outcome. JEL Classifications: G12, G02, D83 （长期以来，金融学术领域里的文献只注重价格和收益率，却较少研究交易量。在最近的二十年里，金融学术文献已经开始研究价格和交易量两者与经济基本量之间的相互关系，并且探讨交易量的行为内涵，例如投资者对风险的态度、过度自信、不同观点以及关注程度等等。然而，我们还是对交易量的认识知之甚少。本文根据行为分析，用交易量概率来表示市场群体的交易频率，并且通过我国股市来实证检验涉及交易量与价格之间不确定关系的两种适应性假说。实证结果表明：市场群体在每日交易的时间窗口内除了采用简单的经验法则之外，同时还采用有效的适应性方式来从事股票交易，并且逐步倾向于形成一个结果和认同的资产价格；无论该资产价格是否明显地被高估或低估，市场群体在相互作用和竞争的过程中往往能够形成这样一个稳态的均衡价格。这表明了资产价格不仅包含了基本价值同时还包含了非公开信息、投机、情绪、关注、赌博和娱乐等价值。此外，在任意两个连续交易日之间，市场群体在与市场环境的相互作用过程中，通过交易量的增加或减少来有效地适应盈亏。我们的研究结果说明了在由信息、交易与收益结果三项构成的反馈环中，它们之间的相互作用是如何导致了过度交易的，这其中包含了导致过度交易的各种内外因素。最后，我们假设股票市场中的投资者是通过交易财富来产生流动性效用，它等于概率加权效用与相对于结果为参照系的反转效用之和，从而推导出Shi氏价-量微分方程，将市场动力学行为与群体交易行为协调在一个统一的框架体系。）

It has been long that literature in financial academics focuses mainly on price and return but much less on trading volume. In the past twenty years, it has already linked both price and trading volume to economic fundamentals, and explored the behavioral implications of trading volume such as investor’s attitude toward risks, overconfidence, disagreement, and attention etc. However, what is surprising is how little we really know about trading volume. Here we show that trading volume probability represents the frequency of market crowd’s trading action in terms of behavior analysis, and test two crowd’s trading behavioral hypotheses relevant to the volume uncertainty associated with price in China stock market. The empirical work reveals that market crowd trade in simple heuristics and efficient adaptation, gradually tend to achieve agreement on an outcome or an asset price widely on a trading day, and generate such a stationary equilibrium price very often in interaction among themselves no matter whether it is highly overestimated or underestimated, suggesting that asset prices include not only a fundamental value but also private information, speculative, sentiment, gamble, and entertainment values etc. In addition, market crowd adapt to gain and loss by trading volume increase or decrease significantly in interaction with environment in any two consecutive trading days. Our results demonstrate how interaction between information and news, the trading action, and return outcomes in the three-term feedback loop produces excessive trading volume which includes various internal and external causes. Finally, we reconcile market dynamics and crowd’s trading behaviors in a unified framework by Shi’s price-volume differential equation in stock market where, we assume, investors derive a liquidity utility expressed in terms of trading wealth which is equal to the sum of a probability weighting utility and a reversal utility in reference to an outcome. JEL Classifications: G12, G02, D83 (长期以来，金融学术领域里的文献只注重价格和收益率，却较少研究交易量。在最近的二十年里，金融学术文献已经开始研究价格和交易量两者与经济基本量之间的相互关系，并且探讨交易量的行为内涵，例如投资者对风险的态度、过度自信、不同观点以及关注程度等等。然而，我们还是对交易量的认识知之甚少。本文根据行为分析，用交易量概率来表示市场群体的交易频率，并且通过我国股市来实证检验交易量与价格之间不确定关系中关于群体交易行为的两个基本假说。实证结果表明：市场群体在每日交易的时间窗口内采用简单的经验法则和有效的适应方式来从事交易，并且总是逐步地倾向于形成一个结果和认同的资产价格；无论该资产价格是否明显地被高估或低估，市场群体在相互作用的过程中往往能够形成这样一个稳态的均衡价格，这表明了资产价格不仅包含基本价值同时还包含非公开信息、投机、情绪、赌博和娱乐等价值。此外，在任意两个连续交易日之间，市场群体在与市场环境的相互作用过程中，通过交易量的增加或减少来有效地适应盈亏。我们的研究结果说明了在由信息、交易与收益结果三项构成的反馈环中，它们之间的相互作用是如何导致了过度交易的，这其中包含了导致过度交易的各种内外因素。最后，我们假设股票市场中的投资者是通过交易财富来产生流动性效用，它等于概率加权效用与相对于结果为参照系的反转效用之和，从而推导出Shi氏价-量微分方程，将市场动力学行为与群体交易行为协调在一个统一的框架体系。)

本文检验了美国期货市场WTI原油、S&P500指数和10年期国债品种的日内、日间价格波动与日内交易量、隔日交易量之间的关系，发现预期的日内和隔日交易量都有平抑期货市场价格波动的作用，非预期的隔日交易量与期货价格波动之间有正相关关系，非预期的日内交易量对价格波动的影响不显著。从信息对称性的角度分析，预期的交易量中含有更多信息，能抑制期货价格的偏离；非预期的交易量主要由信息反馈者提供，他们往往对期货价格的变动做出过度反应，从而加剧价格波动。

It has been long that literature in finance focuses mainly on price and return but much less on trading volume, even completely ignoring it. There is no information on supply-demand quantity and trading volume in neoclassical finance models. Contrary to one of the clearest predictions of rational models of investment in a neoclassical paradigm, however, trading volume is very high on the world’s stock market. Here we extend Shi’s price-volume differential equation, propose a notion of trading conditioning, and measure the intensity of market crowd trading conditioning by accumulative trading volume probability in the wave equation in terms of classical and operant conditioning in behavior analysis. Then, we develop three kinds of market crowd trading behavior models according to the equation, and test them using high frequency data in China stock market. It is hardly surprising that we find: 1) market crowd behave coherence in interaction widely and reach agreement on a stationary equilibrium price between momentum and reversal traders; 2) market crowd adapt to stationary equilibrium price by volume probability increase or decrease in interaction between market crowd and environment (or information and events) in an open feedback loop, and keep coherence by conversion between the two types of traders when it jumps and results in an expected return from time to time, the outcome of prior trading action; 3) while significant herd and disposition “anomalies” disappear simultaneously by learning experience in a certain circumstance, other behavioral “anomalies”, for examples, greed and panic, pronounce significantly in decision making. Specifically, a contingency of return reinforcement and punishment, which includes a variety of internal and external causes, produces excessive trading volume. The behavioral annotation on the volume probability suggests key links and the new methods of mathematical finance for quantitative behavioral finance.长期以来，金融的学术文献主要关注价格和回报率，很少考虑甚至完全忽视了交易量。新经典金融模型就没有供需量和交易量的信息。然而，与新经典框架理性投资模型的预计结果不同，交易量在世界的股票市场上是非常大的。我们基于Shi的价-量微分方程，根据行为分析中的经典性和操作性条件反射，提出了交易性条件反射的概念，并且用该方程中的累计交易量概率来计量市场群体交易性条件反射的强度。由该方程，我们得到三种市场群体的交易行为模型，并且用我国股市的高频数据进行实证分析。不难发现：1）市场群体在相互作用的过程中普遍地表现出相互一致的行为特征，趋势和反转交易者之间存在着一个大家都能够接受的稳态均衡价格；2）交易行为有时会导致稳态均衡价格出现跳跃、带来预期收益率，这时，市场群体在开放的反馈环中，通过与环境（或信息和事件）之间的相互作用，由成交量概率的增加或减少来适应该均衡价格的变化，趋势和反转交易者也会通过相互转换保持市场群体行为的相互一致性； 3）尽管在某特定环境下市场群体通过学习实践，羊群和处置行为同时消失了，但是其他行为“异象”，例如贪婪与恐慌，在决策中却表现的十分显著。特别地，收益率强化和惩罚过程，其中包含各种内外因素，导致过度交易量。累计交易量概率的行为诠释为计量行为金融学提供了关键性的纽带作用和数学金融的新方法。

本文采用经典Weibull-SCD(1,1)模型，应用超高频股指期货行情数据，研究了我国股指期货市场交易久期的日内模式和聚类特征,研究结论如下：四个合约均具有显著的日内效应，当月合约全天呈现显著的W型特征，下月、下季和隔季合约全天基本呈现倒V形特征。当月合约比下月合约的交易聚类性显著，下季合约比隔季合约的交易聚类性显著。微观结构变量对交易久期的影响与理论预测相一致，即在我国股指期货市场交易久期的聚类性，不是由于流动性交易造成的，而是新信息发生作用的结果，也就是说当前的持仓量、买卖价差和成交量都会对未来的交易久期，即聚类性产生显著的影响。持仓量和交易量的提高促进了未来交易久期的降低，而买卖价差的扩大会使未来的交易久期提高。

本文以2005 年至2010 年中国上市公司为样本，通过考察市场对上市公司盈余公告的 反应程度（异常交易量、异常波动率两个维度）来探讨新会计准则的实施对于信息披露质量 的影响。我们的实证研究发现：随着新会计准则的实施，盈余公告之后的异常交易量和波动 率都显著增加。并且在控制了其它影响因素以后，该结论仍