kaniel

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Siraprapa Watakit

5502310013

Individual Investor Trading and ReturnPatterns around Earnings Announcements

KANIEL, LIU, SAAR, and TITMAN [2012]

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Agenda2

Overview

Contribution

Data

Conclusion

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Overview of The Paper3

The study mainly focus on the question: Whether or not,

individuals can gain abnormal returns due to their private

information or skill?

Previously study usually point out that the trading by individuals

are merely a noise or suggest that there is no evidence supportsthat individuals are informed traders

For single individual investor, the claim may be true but in

aggregation , there many be some signal that is relatively

important To investigate this question, the authors study the abnormal returns

of aggregate individual investors around the earning

announcement time(also: dividend, merging announcement )

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Contribution4

New methodology and new evidence to support that individual

investors are an informed traders

Pre-event trading by individuals predicts returns on and after

earnings announcement dates

The abnormal returns in this study are attributed to liquidity

provision and individuals information/skill

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I.Sample and Data5

Large dataset of 1.55 Trillions on individual trades on NYSE

TORQ during 2000-2003

The account type are included, no need for

individual/institutionals mapping

The definition ofcumulative abnormal net individual trading

CAR = Cumulative abnormal returns Market Adjusted(EQ.W)

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II.Sample and Data6

Table 2: correcting the clustering event problem, sort by market.cap

and then calculate IndNT

Mostly buying

before eventMostly Selling on

and after event

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II. Individual Trading and Return Predictability:

Information versus Liquidity7

First, calculate IndNT[-10,-1]and sort stocks into quintile;

quintile 1 contains the stocks that individuals sold the most

quintile 5 contains the stocks that individuals bought the most

Then, calculate CARs Table 3

stocks that were sold

intensively have negative

return

stocks that were bought

intensively have positive return

pre-event trading is significantly

related to abnormal returns

(on and after)

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To rule out means reversion, sort by CARs then by IndNT,

Table 4 Panel A

Table 4 B: sort by news(Earning Surprise) then by IndNT


Information versus Liquidity

not significant,no means

reversion

significant, news

does matter

Table 5

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Could these CARs be the results ofliquidity provision and NOT

information?

people just trade because they want to rebalance their portfolios,

not because they know something others dont

To find out, run regression models

Get the estimators from (3) and calculate expected CAR

Compute the difference


Information versus Liquidity

Abnormal return component that

CANNOT be attributed to

LIQUIDITY and hence be

attributed to INFORMATION

other models have RISK,

RiskAmount

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Information versus Liquiditysignificant,

individuals have

info

removed floor

market maker

other version of models have similar results

(include dividend announcement)

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Conclusion11

Using new methodology and also new and large dataset, evidence

are found and supports that

Individuals have skill/information

pre-event trading predict on and after abnormal returns

The abnormal return decomposition shows that the returns and

partly from liquidity provision and information/skill(50:50)

kaniel

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