Hendershott et al. (2011, Does Algorithmic Trading Improve Liquidity? Journal of Finance 66, 1–33) show that algorithmic traders improve liquidity in equity markets. An equally important and unanswered question is whether they improve liquidity when information asymmetry is high. We use days surrounding earnings announcement as a period of high information asymmetry. First, we follow Hendershott et al. (2011, Does Algorithmic Trading Improve Liquidity? Journal of Finance 66, 1–33) to use introduction of NYSE autoquote as a natural experiment. We find that increased algorithmic trading (AT) as a result of NYSE autoquote does not improve liquidity around earnings announcements. Next, we use trade-to-order volume % and cancel rate as a proxy for algorithmic trading and find that abnormal spreads surrounding the days of earnings announcement are significantly higher for stocks with higher AT. Our findings indicate that algorithmic traders reduces their role of liquidity provision in markets when information asymmetry is high. These findings shed further light on the role of liquidity provision by algorithmic traders in the financial markets.

中文翻译：

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当信息不对称程度很高时，算法交易者会提高流动性吗？

亨德肖特等人。(2011, Dos Algorithmic Trading Improvement Liquidity? Journal of Finance 66, 1-33) 表明算法交易员提高了股票市场的流动性。一个同样重要且未解决的问题是，当信息不对称程度很高时，它们是否会提高流动性。我们将围绕收益公告的日子作为信息高度不对称的时期。首先，我们关注 Hendershott 等人。(2011, Dos Algorithmic Trading Improvement Liquidity? Journal of Finance 66, 1–33) 将 NYSE 自动报价引入作为自然实验。我们发现，由于 NYSE 自动报价而增加的算法交易 (AT) 并没有提高收益公告周围的流动性。下一个，我们使用交易对订单量百分比和取消率作为算法交易的代理，发现在收益公告日周围的异常点差对于 AT 较高的股票明显更高。我们的研究结果表明，当信息不对称程度很高时，算法交易者会降低他们在市场中提供流动性的作用。这些发现进一步阐明了算法交易者在金融市场中提供流动性的作用。