Competitive advantages among investors exist when stock prices do not reflect all
available information or investors have different information. When analysts interpret and
disseminate public information, they may influence informed and uninformed investors and
produce changes in the price discovery process. The probability of informed trading after
analyst recommendations provides insight into this influence.
How Is This Research Useful to Practitioners?
The probability of informed trading (PIN) variable is simply a proxy for the proportion of
trades executed by informed investors. The authors define informed investors as investors
trading with superior knowledge of the probability distribution of share prices, through
either access to private information or skillful processing of public information.
Uninformed investors do not have the same information but are aware of this disadvantage and
attempt to profit by following trades of informed investors.
The authors show that when analysts in the Spanish equity market issue a change of
recommendation, informed trading increases but uninformed trading experiences a larger
increase, causing PIN to decrease. This decrease in PIN happens whether the analyst issues
an upgrade or a downgrade. The arrival of uninformed buyers is not significantly different
from the arrival of uninformed sellers, suggesting herding behavior. When there is no
change, or there is a reiteration, of analyst recommendation, informed trading decreases
slightly, but uninformed trading experiences a larger decrease, causing PIN to increase.
This effect is most significant for small-market-cap stocks, which are determined to have a
higher initial PIN. Large-market-cap companies and stocks with high share turnover ae
determined to have a lower PIN and less variation in PIN across all situations.
After a change of analyst recommendation, the presence of informed investors fails to
improve efficiency because there is no significant effect on the price discovery process.
This finding is evidenced by a delay measure of how long it takes an individual stock to
incorporate marketwide information and may be attributable to the analyst
recommendation’s attracting uninformed investors who are naive about what the
equilibrium price should be.
Knowledge of factors affecting the PIN variable is valuable for market makers and market
participants who manage the risk that the counterparty is trading with superior information.
Market regulators may also be interested in knowing when trading with information asymmetry
is taking place.
How Did the Authors Conduct This Research?
Sociedad de Bolsas S.A. provides data on the Spanish equity market for 1997–2010,
including transaction date, time, broker codes, price, and trading volume. The authors
obtain analyst recommendation data from FactSet. They choose the Spanish market because of
prior research in which an environment of lower-quality information and significant herding
behavior in this market was identified. Stock information—including market
capitalization, average trading volume, and book value—is obtained from the Datastream
database by Thomson Financial. These data produce a sample containing 49 average
observations for each of the 161 months.
The PIN variable estimates the arrival of informed investors as a percentage of the arrival
of all investors, whereby the probability of informed trading is modeled as a function of
excessive buying or selling order flow attributable to information events. Informed
investors place trades motivated by speculation—buying on good news and selling on bad
news—and these order flows are assumed to follow a Poisson process. Uninformed
investors are essentially liquidity traders, buying and selling for reasons unrelated to the
model according to a Poisson-independent distribution. Whether a transaction is initiated by
a buyer or a seller is unavailable in the dataset and is estimated using a tick test,
whereby an uptick indicates a buyer and a downtick indicates a seller.
To address heteroskedasticity, the authors use pooled regressions under a
variance–covariance matrix over the entire firm-month sample. These regressions
include the logarithm of variables—including market cap, share turnover, annualized
standard deviation of daily yields, and book-to-market ratio—previously shown to have
a significant relationship with PIN. Regressing daily returns on contemporaneous and lagged
market returns, the authors create a delay measure similar to an F-test,
representing individual stock return variation explained by lagged market returns.
Classifying market participants as informed or uninformed on the basis of a presumption
about their knowledge of the probability distribution of share prices presents a challenge
when market participants have various time horizons. Automated high-frequency-trading
systems and day traders may have sophisticated knowledge about the probability distribution
of share prices in the short term and may adjust their holding periods accordingly to profit
from very short-term price fluctuations. Although these market participants may not clearly
fit the authors’ informed or uninformed classification, they may account for
significant order flow—particularly during the later years of the study period,
starting around 2005.
The authors mention that company news announcements or other information disclosures that
occurred during the study period may have influenced PIN measures, although they focus
specifically on analyst recommendations. The PIN variable is susceptible to the estimation
bias of nonobservable parameters, the misclassification of trades as buyer initiated or
seller initiated, and problems with applying the measure to very high-volume stocks and
high-frequency trading. Despite its limitations, PIN remains a useful analytical tool and an
area for continued research.