Are Trade Size‐Based Inferences About Traders Reliable? Evidence from Institutional Earnings‐Related Trading

• Author: MUSA SUBASI,WILLIAM CREADY,ABDULLAH KUMAS
• Date: 01 September 2014
• DOI: http://doi.org/10.1111/1475-679X.12056
• Published date: 01 September 2014

DOI: 10.1111/1475-679X.12056

Journal of Accounting Research

Vol. 52 No. 4 September 2014

Printed in U.S.A.

Are Trade Size-Based Inferences

About Traders Reliable? Evidence

from Institutional Earnings-Related

Trading

WILLIAM CREADY,

∗ABDULLAH KUMAS,

†AND MUSA SUBASI

‡

Received 4 January 2012; accepted 8 May 2014

ABSTRACT

The use of observed transaction sizes to differentiate between “small” and

“large” investor trading patterns is widespread. A significant concern in such

studies is spurious effects attributable to misclassification of transactions,

particularly those originating from large investors. Such effects can arise

unintentionally, strategically, or endogenously. We examine comprehensive

records of a sample of institutional investors (i.e., “large” traders), includ-

ing their order sizes and overall position changes, to assess the degree to

which such misclassifications give rise to spurious inferences about “small”

and “large” investor trading activities. Our analysis shows that these institu-

tions are heavily involved in small transaction activity. It also shows that they

increase their order sizes substantially in announcement periods relative to

nonannouncement periods, presumably as an endogenous response to earn-

ings news. In the immediate earnings announcement period, transaction size-

based inferences about directional trading are quite misleading—producing

∗Naveen Jindal School of Management, University of Texas at Dallas; †Robins School of

Business, University of Richmond; ‡Robert Trulaske Sr. College of Business, University of

Missouri–Columbia.

Accepted by Douglas Skinner. We gratefully acknowledge valuable comments from Ashiq

Ali, Daniel Cohen, and seminar participants at the University of Texas at Dallas, the NYU

summer research conference, Florida International University, Seoul National University,

and Sungkyunkwan University. An Online Appendix to this paper can be downloaded at

http://research.chicagobooth.edu/arc/journal/onlineappendices.aspx.

877

Copyright C, University of Chicago on behalf of the Accounting Research Center,2014

878 W.CREADY,A.KUMAS,AND M.SUBASI

spurious “small trader” effects and, more surprisingly, erroneous inferences

about “large trader” activity.

1. Introduction

A considerable body of research, building on early work by Cready [1988]

and Lee [1992] explores how investor information processing activity as

expressed through trading differs by investor size. Commonly, these anal-

yses infer trader characteristics indirectly, using transaction size to identify

a trader as small (individual) or large (institutional).1As is also often rec-

ognized by such studies, these categorizations are imperfect. For example,

large investor orders are often broken up in execution, resulting in multi-

ple small transactions that are likely to be misattributed to small investors.

If such distortions are systematic (e.g., they are related to the price adjust-

ment process that is taking place), then linking size-stratified trading find-

ings with investor scale is problematic. Small transaction activities of large

investors or, conversely, large transaction activities of small investors, repre-

sent alternative explanations for supposed differences between small and

large investors.

We investigate the reliability of transaction size-based inferences about

trader behaviors using a detailed database on institutional transactions

from Ancerno Ltd. These investors are all pension or mutual funds and

Puckett and Yan [2011] conclude that Ancerno trading accounts for

around 10% of institutional trading activity. We examine how Ancerno trad-

ing shows up across conventional small and large trade size classifications

and the degree to which transaction size-based inferences accurately reflect

underlying position changes. The analysis focuses on earnings announce-

ment trading because the announcement trading response is quite large

(per the existing literature) and has been subjected to extensive transac-

tion size-based analysis. Hence, we should be able to readily detect system-

atic trading effects within the subset of investors examined. We can also

interpret and relate what we find from the perspective of a sizable existent

body of knowledge on transaction size-stratified trading around announce-

ment dates.

We find that in announcement periods Ancerno investors seemingly

trade in an unsophisticated manner. They buy when analyst or random

walk earnings forecast errors are negative (bad news) and sell when these

1A review of the literature subsequent to Cready [1988] and Lee [1992] identified over

30 published papers employing transaction size-based techniques with 10 of them appearing

in year 2010 or later. Most of these explicitly link these techniques to the idea of isolating

individual or “small investor” from institutional or “large investor” trading activity, although a

very few of them (e.g., O’Neil and Swisher [2003]) appeal to a more generic notion that trade

size reflects how “informed” a trade is. That is, “large” transactions reflect informed trading

while “small” transactions reflect uninformed trading apart from any link to the size of the

investor making the trade.

ARE TRADE SIZE-BASED INFERENCES RELIABLE?879

errors are positive (good news). These patterns conflict with existing trans-

action size evidence that “large traders” trade in the direction of the analyst

forecast error and ignore the random walk error (Battalio and Menden-

hall [2005; henceforth BM], Ayers, Li, and Yeung [2011; henceforth ALY]).

However, even though Ancerno investor trading constitutes a sizable por-

tion of overall market trading activity, we find no evidence that their drift-

facilitating announcement period trading impacts the magnitude of the

subsequent post-earnings-announcement drift (PEAD).

Our analysis further identifies three substantive issues pertinent to draw-

ing inferences about information-driven trading activities of small and large

traders based on transaction sizes. First, large investors are heavily involved

in small transaction and order activity.2In our data, it is not uncommon for

over 50% of these investors’ transactions to take place within traditional

“small” investor transaction size categories. Hence, traditional “small in-

vestor” trade size cut-offs contain considerable levels of large investor trad-

ing. And, since this activity is intentional on the part of these investors (i.e.,

they choose to enter “small” orders), it follows that underlying factors that

lead large investors to engage or not engage in small trade size activity is a

potentially confounding factor when attributing small trade size findings to

small traders.

Second, order sizes of Ancerno investors increase around 40% in an-

nouncement periods. Hence order and, by extension, transaction size are

substantive endogenous aspects of investor response to information. This

trade size effect undercuts the reliability of commonly encountered asser-

tions based on transaction size categories. For example, in our data, trading

activity increases by much higher percentages in large trade size categories

relative to small trade size categories, consistent with the idea that investor

responsiveness to earnings news increases with size/scale (Cready [1988],

Lee [1992]). However, the opposite is true when we examine response by

institution size: smaller institution trading response is stronger than large

institution response. It is the upward shift in order sizes that gives rise to the

appearance of a higher (lower) trade response by large (small) investors in

our analyses. This finding has implications for small trade size-based in-

ferences about small investor trading found in the existing literature. For

example, is the Asthana, Balsam, and Sankaraguruswamy [2004] finding

that EDGAR increased small, but not large, trader response to 10K filings

due to small investors ramping up their trading, or is it due to large in-

vestors becoming less inclined to shift to larger event period order sizes in

the new EDGAR disclosure environment? Is the lower small trader response

to relative report complexity in Miller [2010] due to inhibited information

2An order represents a specific point-in-time request by an investor to buy or sell shares of a

security. Execution of such orders results in transactions. In the execution process, a single or-

der can be broken up into multiple transactions or several orders can be aggregated together

into a single transaction. This distinction is important because trade size-based research largely

relies on easy-to-observe transactions rather than hard-to-observe orders.