Do Prices Reveal The Presence Of Informed Trading?

Pierre Collin-Dufresne

Ecole Polytechnique Fédérale de Lausanne – Swiss Finance Institute; National Bureau of Economic Research (NBER)

Vyacheslav Fos

Boston College – Department of Finance

January 27, 2015

Journal of Finance, Forthcoming


Using a comprehensive sample of trades from Schedule 13D filings by activist investors, we study how measures of adverse selection respond to informed trading. We find that on days when activists accumulate shares, measures of adverse selection and of stock illiquidity are lower, even though prices are positively impacted. Two channels help explain this phenomenon: (a) activists select times of higher liquidity when they trade, and (b) activists use limit orders. We conclude that when informed traders can select when and how to trade, standard measures of adverse selection may fail to capture the presence of informed trading.

Do Prices Reveal The Presence Of Informed Trading? – Introduction

An extensive body of theory suggests that stock illiquidity, as measured by the bid-ask spread and by the price impact of trades, should be increasing in the information asymmetry between market participants (Glosten and Milgrom (1985), Kyle (1985), Easley and O’Hare (1987)). Based on this literature, there have been many attempts to measure trading costs empirically, and to decompose such costs into different components such as adverse selection, order processing, and inventory costs (Glosten (1987), Glosten and Harris (1988), Stoll (1989), Hasbrouck (1991a)). Empirical measures of adverse selection typically rely on an estimate of the persistent price impact of trades to capture the amount of private information in trades. An extensive empirical literature employing these adverse selection measures thus assumes that they capture information asymmetry (Barclay and Hendershott (2004), Vega (2006), Duarte et al. (2008), Bharath, Pasquariello, and Wu (2009), Kelly and Ljungqvist (2012)).

But, do these empirical measures of adverse selection actually capture information asymmetry? To test this question one would ideally separate informed from uninformed trades ex-ante and measure their relative impact on price changes. However, since we generally do not know the traders’ information sets, this is hard to do in practice.

In this paper we use a novel data set of trades by investors that we can identify as having substantial private information to study how illiquidity measures are actually related to informed trading. More specifically, we exploit a disclosure requirement Rule 13d-1(a) of the 1934 Securities Exchange Act to identify trades that rely on valuable private information. Rule 13d-1(a) requires investors to file with the SEC within 10 days of acquiring more than 5% of any class of securities of a publicly traded company if they have an interest in influencing the management of the company. In addition to having to report their actual position at the time of filing, Item 5(c) of Schedule 13D requires the filer to report the date, price, and quantity of all trades in the target company executed during the 60 days that precede the filing date.

We collect a comprehensive sample of trades from the Schedule 13D filings. We view this sample as an interesting laboratory to study the liquidity and price impact of informed trades. An average Schedule 13D filing in our sample is characterized by a positive and significant market reaction upon announcement. For example, the cumulative return in excess of the market is about 6% in the (t-10,t+1) window around the filing date and about 3% in the (t-1,t+1) window around the filing date. To summarize, the evidence implies that Schedule 13D filers’ information is valuable. We can therefore classify the pre-announcement trades by Schedule 13D filers as informed trades. Note that, by its very nature, the information held by Schedule 13D filers is likely to qualify as \private information” and to be long-lived.

Our main empirical result is that standard measures of adverse selection and stock illiquidity do not reveal the presence of informed trading. Specifically, we find that several measures of adverse selection are lower on days when Schedule 13D filers trade, which suggests that adverse selection is lower and the stock is more liquid when there is significant informed trading in the stock. For example, on an average day when Schedule 13D filers trade, the measured price impact (lambda) is almost 30% lower relative to the sample average. Importantly, we show that days when Schedule 13D filers trade are characterized by positive and significant market-adjusted returns, which suggests that informed trades do impact prices. Adverse selection measures, however, fail to detect that price impact.

Informed Trading

Informed Trading

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