Trade Informativeness in Modern Markets
利用基于交易的日历时间组合分析，研究了机构、自营和零售三类投资者交易的信息含量，发现机构交易信息含量为正，零售为负，且流动性供给交易的信息含量高于需求交易。
Using transactions-based calendar time (TBCT) portfolio analysis, we investigate informativeness of trades of investor categories, namely institutions, proprietary traders, and retail clients. We find that trade informativeness is positive for institutional and negative for retail-client investors. The informativeness of liquidity-demanding trades are less than the informativeness of liquidity-supplying trades for all trading groups, over both long and short horizons. We also find that institutions are benefitted by algorithmic executions compared to manual executions and this benefit is elevated on days of high volume and volatility. Proprietary algorithmic traders (high-frequency traders) generate positive alpha for their trades only from their liquidity-supplying trades.