Facing the puzzling risk-return trade-off, this paper proposes a new model for risk premia to capture nonlinear and time-varying features under the influence of trading volume. Using high-frequency data for the US stock market in Wharton Research Data Services' Trade and Quote database, our empirical findings suggest a significant nonlinear and time-varying contemporary relationship between return and realized volatility, ranging from positive to negative with an up-down-up pattern, summarized as follows. First, the contemporary relationship is positive on inactive trading days when the trading volume is smaller than usual, in which case traders may face no new information or event uncertainty. Second, the relationship is significantly negative when the trading volume is large on active trading days, in which case traders may be overconfident and behave in a risk-seeking fashion. Third, the risk premium tends toward zero during extremely abnormal trading days. Finally, low and high levels of trading volume have asymmetrical influences on risk premia, with a larger absolute value of risk premia for high levels of trading volume. Furthermore, the nonlinear changing autocorrelation of returns is insignificant from zero on normal trading days and most likely different from zero on abnormal trading days. These results provide explanations for the conflicts between financial theoretic and empirical studies.

面对令人费解的风险与收益权衡，本文提出了一种新的风险溢价模型，以捕捉交易量影响下的非线性和时变特征。使用沃顿商学院数据服务的贸易和报价数据库中的美国股票高频数据，我们的经验发现表明，收益率与实际波动率之间存在显着的非线性且时变的当代关系，从正到负随上而下模式，总结如下。首先，当交易量小于往常时，在闲置的交易日中，当代关系是积极的，在这种情况下，交易者可能不会面临新的信息或事件的不确定性。其次，当活跃交易日的交易量很大时，该关系显着为负，在这种情况下，交易者可能会过分自信并以冒险的方式行事。第三，在极端异常的交易日中，风险溢价趋向于零。最后，交易量的高低对风险溢价具有不对称的影响，对于高交易量而言，风险溢价的绝对值更大。此外，收益的非线性变化自相关在正常交易日从零开始是微不足道的，并且在异常交易日从零开始很可能不同于零。这些结果为金融理论与实​​证研究之间的冲突提供了解释。高交易量的风险溢价的绝对值更大。此外，收益的非线性变化自相关在正常交易日从零开始是微不足道的，并且在异常交易日从零开始很可能不同于零。这些结果为金融理论与实​​证研究之间的冲突提供了解释。高交易量的风险溢价的绝对值更大。此外，收益的非线性变化自相关在正常交易日从零开始是微不足道的，并且在异常交易日从零开始很可能不同于零。这些结果为金融理论与实​​证研究之间的冲突提供了解释。