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。

本文通过我国股市的高频数据和相关性分析来研究市场群体的学习和心理行为。我们根据心理学中的操作性条件反射，首次提出一个交易性条件反射的概念，用成交量-价概率波方程中的成交量概率来计量市场群体交易性条件反射的强度。我们发现：总体来说，平均收益率与交易性条件反射强度变化之间具有显著的正相关性，市场群体对收益率的心理预期显著地表现了卖出的处置效应和买入的羊群行为，并且该“羊群”对价格趋势的心理预期明显地大于其反转的；第二，我们还发现在细分后的某一时期，它们之间具有显著的负相关性。我们用条件反射来解释他们的交易行为“异象”。

本文通过我国股市的高频数据和相关性分析来研究市场群体的学习和心理行为。我们根据心理学中的操作性条件反射，首次提出一个交易性条件反射的概念，用成交量-价概率波方程中的成交量概率来计量市场群体交易性条件反射的强度。我们发现：总体来说，平均收益率与交易性条件反射强度变化之间具有显著的正相关性，市场群体对收益率的心理预期显著地表现了卖出的处置效应和买入的羊群行为，并且该“羊群”对价格趋势的心理预期明显地大于其反转的；第二，我们还发现在细分后的某一时期，它们之间具有显著的负相关性。我们用条件反射来解释他们的交易行为。

To brief a transaction volume-price probability wave equation, a new advance in econophysics; To introduce a notion of trading conditioning for the first time in terms of operant conditioning in psychology; To measure the intensity of market crowd’s trading conditioning by transaction volume probability; To test correlation between the rate of mean return and the change in the intensity of trading conditioning subject to the return, using high frequency data in China stock market; To study market crowd’s learning and psychological behavior by correlation analysis, and explain their behavioral“anomalies”by trading conditioning.

基于解析的成交量价概率波分布函数，用成交量概率描述价格波动的不确定性和强度，我们根据市场群体的心理行为，构造了一个关于价格波动和收益信息的交易性条件反射的理论模型。应用此模型对中国股市高频数据检验，我们主要有以下发现：1）总体来说平均收益率与交易性条件反射强度变化率之间存在着显著的正相关；2）在泡沫破裂前、后两个时期，它们之间的正相关缺乏显著性；3）比较特殊的是上证指数在牛市上升的一段时期内，它们之间存在着显著的负相关。我们的模型和实证能够同时检验股市中的处置效应和羊群行为，并且解释过度交易等市场异象。