We examine the relation between trading volume and associated CBOE’s implied volatility in commodity ETF, stock market index, and stock market index ETF by employing a new approach, behavioral concepts. Availability, conservatism, and extrapolation biases work well in explaining the trading volume-implied volatility relations in all types of assets. Coefficients of contemporaneous and lagged trading volumes are statistically significant, showing that investors rely on recently observed or experienced due to their fresh memory and recent experience. This is supported by availability and conservatism biases. In addition, given statistically significant coefficients of lead trading volume, traders also overweigh recent situations when making decision and are slow to change their former beliefs in the arrival of new information, supported by conservatism and extrapolation biases. The relation is more pronounced in the most extreme quintiles, demonstrating asymmetric trading volume-implied volatility relation. Of all, the relation of euro currency is weakest. We conclude that difference in findings depends on types of assets, which have different patterns of volatility skew.

中文翻译：

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金融市场中的成交量与隐含波动率关系：行为解释

我们采用一种新的方法——行为概念来研究商品 ETF、股票市场指数和股票市场指数 ETF 的交易量与相关 CBOE 隐含波动率之间的关系。可用性、保守性和外推偏差可以很好地解释所有类型资产的交易量与隐含波动率的关系。同期和滞后交易量的系数具有统计显着性，表明投资者由于新鲜记忆和近期经验而依赖最近观察或经历的交易量。这得到了可用性和保守主义偏见的支持。此外，鉴于铅交易量的统计显着系数，交易者在做出决策时也会过度考虑近期情况，并且在保守主义和外推偏差的支持下，缓慢地改变他们以前对新信息到来的信念。这种关系在最极端的五分之一中更为明显，证明了交易量与隐含波动率关系的不对称。其中，欧元货币的关联性最弱。我们得出的结论是，研究结果的差异取决于资产类型，而资产类型具有不同的波动性偏差模式。