Institutional investors, especially in emerging markets such as India, have been the focus of much research and media interest. Both foreign and domestic institutional investors’ transactions are widely used as indicators of future movements in stock prices.
Institutions generally manage money on behalf of other investors: Does their mandate, their size, or their management structure make them less susceptible to irrational trading? Are they more informed than other groups of investors, such as retail investors? Can they predict stock price movements? Do they systematically arbitrage away irrational responses of individual investors to informational events? From a public policy point of view, are institutions a stabilizing or destabilizing influence on stock prices?
In a recent study (with John Campbell of Harvard University and Allie Schwartz of Cornerstone Research), we set out to analyse these questions using data from the US equity market, where institutional investors hold a very large fraction of stocks—estimates range from 35% to 40% of market capitalization across all stocks during the 1990s.
These questions have been the focus of much academic research in the past. Several studies have come to the conclusion that institutions are simple price-momentum traders. That is, they follow sequences of high stock returns by purchasing and sequences of low stock returns by selling, without distinguishing whether these price moves are cash flow driven, or disconnected with cash flow. These studies conclude that institutional trading exacerbates the problem of noise in prices. Other studies have found that institutions are not simply following price-momentum strategies; rather, they sell shares to individuals when stock prices increase in the absence of any news about underlying cash flows.
Illustration: Jayachandran / Mint
However, a serious limitation of all these studies is their use of quarterly, or even annual, information to draw conclusions. Movements in institutional ownership happen continuously.
However, in the US (as in many other countries), institutions are only required to report their ownership to the regulatory authority on a quarterly basis. This makes it hard to say whether institutions are reacting to stock price movements, or causing price movements, and makes it impossible to measure institutional responses to high-frequency cash flow news such as earnings announcements.
To address this issue, we developed a new method for inferring high-frequency institutional trading behaviour, which combines two sources of information that in the past have been used separately in analyses of investor behaviour. One of the sources is trade-by-trade data pertaining to all listed stocks on the NYSE and AMEX, beginning 1993. This is essentially the ‘tape’, recording transactions prices and quantities of every trade conducted on these exchanges. This is matched with records of the SEC (Securities and Exchange Commission) mandated 13-F filings of large institutional investors, which provide quarterly snapshots of institutional holdings.
In doing so, we can provide a rule for inferring overall changes in institutional ownership from the general patterns of trading on a particular day. This rule can be used to track institutional trading on a daily or intra-daily basis.
Using this method, we have discovered several interesting facts. First, institutions tend to trade in a manner that suggests that they absorb (rather than provide) liquidity provided by the specialist, and possibly also provided by limited orders from individuals. Furthermore, institutions are particularly likely to demand liquidity when they sell stocks. All these patterns are more pronounced in large stocks than in small stocks.
Second, our results suggest that institutions buy stocks using trades that are above $30,000 (about Rs12 lakh) in size, while buy volume between $2,000 and $30,000 is associated with decreasing institutional ownership.
Interestingly, extremely small buys below $2,000 also predict increasing institutional ownership, suggesting that institutions use these trades to conceal their activity or to round small positions up or down. All these patterns are reversed for sell volume, and are remarkably consistent across small, medium and large firms.
Finally, we investigate whether institutions trade in such a manner as to take advantage of high-frequency cash flow news announcements such as earnings announcements. We find that institutional trading is able to forecast earnings ‘surprises’, that is, actual earnings less a measure of the consensus analyst forecast. Furthermore, institutional trading can forecast the post-earnings announcement drift, the well-documented movement of stock prices in the direction of the earnings surprise for several months following the day of the earnings announcement. These results suggest that institutional investors, at least in the US, do seem to be in possession of superior information about the path of future cash flows.
These results imply that institutions systematically arbitrage away irrational responses of individual investors to informational events like earnings announcements. The interest in the direction of institutional investor trading, therefore, does seem justifiable—it contains information about the direction of future cash flows.
Tarun Ramadorai is a faculty member in finance at the Saïd Business School, University of Oxford.
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