Abstract
Many questions about institutional trading can only be answered if one tracks high-frequency changes in institutional ownership. In the United States, however, institutions are only required to report their ownership quarterly in 13-F filings. We infer daily institutional trading behavior from the “tape”, the Transactions and Quotes database of the New York Stock Exchange, using a sophisticated method that best predicts quarterly 13-F data from trades of different sizes. We find that daily institutional trades are highly persistent and respond positively to recent daily returns but negatively to longer-term past daily returns. Institutional trades, particularly sells, appear to generate short-term losses—possibly reflecting institutional demand for liquidity—but longer-term profits. One source of these profits is that institutions anticipate both earnings surprises and post-earnings announcement drift. These results are different from those obtained using a standard size cutoff rule for institutional trades.
Highlights
Mean Trade and Quotes (TAQ) total buys TAQ total sells TAQ unclassifiable TAQ total volume TAQ net imbalance Spectrum change
All summary statistics are presented as annualized percentages
We show the explanatory power for the quarterly change in Spectrum institutional ownership of the Lee and Radhakrishna (2000, LR)
Summary
John Y., Tarun Ramadorai, and Allie Schwartz. Forthcoming. We present means, medians, and standard deviations for the Trade and Quotes (TAQ) and Spectrum variables in our specifications. All summary statistics are presented as annualized percentages (standard deviations are annualized under the assumption that quarterly observations are iid). The sample period extends from 1993:Q1 to 2000:Q4 We show the explanatory power for the quarterly change in Spectrum institutional ownership of the Lee and Radhakrishna (2000, LR)
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