越来越胖:崩盘风险和零售交易

Qianyun Yang
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引用次数: 0

摘要

我通过新颖的机器学习方法估计个股的事前崩溃概率。我特别介绍了不平衡学习技术,以促进罕见事件的预测。我指出,崩盘概率高的股票往往回报率较低。进一步的结果表明,以罗宾汉交易员为代表的至少一部分散户投资者倾向于追逐高崩盘风险的股票,这可能会推高其价格,并导致随后的回报降低。利用罗宾汉在2017年底引入的免佣金期权交易作为准自然实验,以及来自Reddit的文本信息,我证明了散户参与显著增加股票崩盘风险的因果证据。这种效应对小公司更为明显。
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Fat and Fatter: Crash Risk and Retail Trading
I estimate ex-ante crash probabilities for individual stocks via novel machine learning methodologies. In particular, I introduce imbalanced learning techniques to facilitate rare events prediction. I show that stocks with high crash probabilities tend to have lower returns. Further results indicate that at least a subset of retail investors, as proxied by Robinhood traders, tend to chase high crash risk stocks, which may bid up their prices and result in lower returns subsequently. Using Robinhood's introduction of commission-free option trading at the end of 2017 as a quasi-natural experiment, together with textual information from Reddit, I document causal evidence that retail participation significantly increases stock crash risk. This effect is stronger for small firms.
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