Information Risk and Long-Run Performance of Initial Public Offerings

145 Pages·2009·0.894 MB·English

by  Frank Ecker (auth.)

Frank Ecker
Information Risk and Long-Run Performance
of Initial Public Offerings
GABLER EDITION WISSENSCHAFT
Frank Ecker
Information Risk
and Long-Run Performance
of Initial Public Offerings
With forewords by Prof. Dr. Hellmuth Milde
and Prof. Dr. Per Olsson
GABLER EDITION WISSENSCHAFT
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Dissertation am Fachbereich IV der Universität Trier, 2005
1st Edition 2008
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Foreword
ExactlyfortyyearsafterEugeneFama’s(1965)article“TheBehaviorofStockMarket
Prices”(JournalofBusiness),theplay”EfficientCapitalMarkets”isstillgoingstrong.
Withhisthesis,FrankEckerisaddinganewacttotheplay: Hisworkisacombination
of several new developments on the analytical and empirical capital market research
front.
Capital market efficiency is based on two aspects. First, the ability of investors
to identify a situation in which asset prices are out of the capital market equilibrium.
Second,onthepossibilityofthemarkettomakearbitrageprofitsbydrivingtheprices
back to the equilibrium value. Both aspects are conditional on the set of ”relevant”
information. As a result, the basic question is: What is relevant information and how
isitprocessedbyinvestors?
Thisworkisbuildingontheconceptofinformationquality,informationuncertainty
or information risk. Fama’s efficient market hypothesis is just a special case based on
the assumption that new information is absolutely correct and completely credible to
all investors. In contrast, this work makes use of the more general assumption that
new information can be characterized by very different degrees of credibility, or qual-
ity. The setting of initial public offerings is chosen as one of the few capital market
transactionsarguablycharacterizedbyhighinformationasymmetrybetweenthefirm’s
insiders (management) and outsiders (investors). As these investors know that they
areataninformationaldisadvantage,theywillonlyimputeanexpectedandpotentially
incorrect information risk premium into the stock price. After the IPO, as new infor-
mationisrevealedovertime,asignallingprocessbythefirmstarts,graduallyallowing
investors to update their belief on the firm’s true information risk and therefore the
firm’sexpectedrateofreturninaBayesiansense.
Whilemanyexplanationsforthepossiblelong-rununderperformanceofIPOshave
been proposed in the literature, Frank Ecker hypothesizes that cross-sectional differ-
ences in the information risk surprise (positive and negative) drive the cross-sectional
differencesinstockmarketperformance,anexplanationthatisactuallyconsistentwith
efficient capital markets under information uncertainty. This work provides new evi-
denceonthemagnitudeandthepersistenceofthisupdatingprocess.
Hellmuth Milde
Foreword
In his work, Frank Ecker connects two strands of literature in the information eco-
nomics / financial economics / accounting research areas: the stock market pricing of
informationuncertaintyandthelong-runperformanceofinitialpublicofferings(IPOs).
The pricing of information risk and information uncertainty is at the forefront of
today’s asset pricing research. The traditional view of market efficiency holds that
stock prices always incorporate all available information. Consequently, the quality of
information cannot matter: Whether information quality is good or bad, everybody
has access to the market price, which serves as an aggregator of all value relevant in-
formation. However, in a world where new information about a firm arrives and is
expectedtocontinuearrivinginthefuture,thequestionastohow,andhowfast,that
information gets into price becomes pertinent. Specifically, if the public information
is not of perfect quality, we can no longer be assured that someone else will not have
accesstobetterinformationatthenextinformationrelease,i.e. asinvestors,wecanbe
rationallyafraidofendinguponthewrongsideofinformationasymmetries. Certainly
ariskonewouldwantcompensationfor. Inher2003PresidentialAddresstotheAmer-
icanFinanceAssociation,MaureenO’Haralaidouttheargumentsinanintuitiveway:
“Traderswithsuperiorinformationwillmovepricestowardfullinformationlevels,but
continuouslyattainingfullinformationlevelsisnotcredible-newinformationarrives,
oldinformationbecomesstale,andeveninformedtradersmayfacerisksthattheirin-
formation is obsolete. Market prices can be martingales with respect to information,
but if traders have diverse information sets, then these expectations need not be the
sameacrosstraders. Thus,asinmicrostructuremodels,theadjustmentofpricestofull
information values can differ widely across markets that are deemed efficient.” Easley
and O’Hara (2004) continue to show how such information effects may not be diver-
sified away in equilibrium. They argue that information risk effects are systematic in
the pricing of stocks, i.e. part of required return, in spite of the fact that firm-specific
informationbydefinitionisidiosyncratic.
The arguments referenced above are not uncontroversial. Other researchers argue
that it is the overall precision of information rather than information asymmetries
that affects required returns. The empirical facts, on the other hand, are fairly well
established. Studyafterstudyshowthatdifferentmeasuresofinformationriskand/or
informationqualityhaveeconomicallyandstatisticallysignificantpredictivepowerover
stockpricesandstockreturns(e.g.,Easleyetal. 2002,Francisetal. 2004,2005). Firms
with high information uncertainty have higher required returns and lower prices, also
after controlling for all other factors that we know affect returns and prices (such as
beta,size,book-to-marketratios,etc.).
viii Foreword
FrankEckerbuildsontheevidenceregardinginformationuncertaintyandidentifies
a situation where information uncertainty effects are likely to be at their most severe:
whenfirmsfirststartpublictrading,i.e.,attheirinitialpublicofferings(IPOs). Frank
Ecker starts with the presumption that investors are rational in a Bayesian sense. If
theyunderestimateinformationuncertaintybeforetheIPO,theirinitialrequiredreturn
istoolow,andpriceistoohigh. Asinvestorsgraduallygetmoreandmoreinformation
signalsandcanevaluatethefirm-specificinformationrisk,theywilladjusttherequired
return upwards, causing a drawn-out price adjustment: negative abnormal returns.
TheoppositewillholdtrueifinvestorsinitiallyoverestimateanIPOfirm’sinformation
uncertainty. Thus,FrankEcker’smainargumentcanbedescribedasapriceadjustment
processtowardsfullinformationpricinginasituationwhereinformationisinitiallyvery
sparse. Theideaisquitenovel–itessentiallytakestheresultsfromtheliteratureabout
required returns and applies it to a situation where there are abnormal returns, thus
showing that there is a rational explanation for what has hitherto been described as
irrationalintheliterature: thelong-termabnormalreturnsfollowingfirms’IPOs.
FrankEcker’sworkisthefirsttexttoputforthandtestatheoryforthelong-term
performance of IPO firms that builds on rational expectations, yet can accommodate
long-term abnormal returns. Importantly, it is also the first test that fully explores
cross-sectional variation in abnormal returns following firms’ IPOs. Thus, we are left
with a cohesive story that builds on rational investor behavior, supported by robust
empiricalevidence.
Per Olsson
Preface
I would like to express my gratitude to many people who contributed to this work:
Professor Hartmut Wa¨chter presided over my defense. My colleagues at the Swedish
InstituteforFinancialResearchinStockholmcommentedonanearlyoutlineofthere-
search idea. Professors Jennifer Francis and Katherine Schipper provided very helpful
adviceontheresearchdesignandwritingissues. Iprofitedfromthecontinuousadvice
andencouragementfromProfessorPerOlsson,bothduringandaftermyvisitatDuke
University. Finally,IthankmyadvisorProfessorHellmuthMildeforthehelpfuldiscus-
sions and his support and encouragement to visit the Duke PhD program. Professors
MildeandOlssonalsowrotethedissertationreports.
Frank Ecker
Contents
Foreword v
Foreword vii
Preface ix
List of Tables xiii
List of Figures xv
Symbols and Abbreviations xvii
1 Introduction and Motivation 1
2 Valuation under Information Risk 7
2.1 Classificationofinformationrisk. . . . . . . . . . . . . . . . . . . . . . 7
2.2 Empiricalmeasurementofinformationrisk . . . . . . . . . . . . . . . . 8
2.3 Conceptualconsequencesoftheintroductionofinformationrisk . . . . 12
3 Derivation of a Returns-Based Measure of Information Quality 15
4 Abnormal Returns Measurement and Hypotheses Development 25
4.1 Methodologicalissuesinlong-termabnormalreturnsmeasurement . . . 25
4.1.1 Whatreturnisnormal? . . . . . . . . . . . . . . . . . . . . . . 25
4.1.2 Choosingtherightmetric . . . . . . . . . . . . . . . . . . . . . 33
4.1.3 Event-timevs. calendar-timeapproaches . . . . . . . . . . . . . 37
4.1.4 Concludingremarksandproblemsdiscussion . . . . . . . . . . . 40
4.2 ExplainingabnormalIPOperformance . . . . . . . . . . . . . . . . . . 43
5 Tests with Abnormal Portfolio Returns 51
5.1 ConstructionoftheIPOsample . . . . . . . . . . . . . . . . . . . . . . 51
xii Table of Contents
5.2 Calendar-timeportfoliosfromthefullIPOsample . . . . . . . . . . . . 55
5.3 Persistencetests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
5.4 Deviationtests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
5.4.1 Mainresults . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
5.4.2 Theroleofsize . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
5.4.3 Analysisofsubperiods . . . . . . . . . . . . . . . . . . . . . . . 83
6 Robustness Tests 85
6.1 Varyingthecalendar-timeapproach . . . . . . . . . . . . . . . . . . . . 85
6.2 Firm-specifictests. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
6.2.1 DeviationandIPOfirmcharacteristics . . . . . . . . . . . . . . 89
6.2.2 Firm-specificabnormalreturnandsize . . . . . . . . . . . . . . 91
6.2.3 Firm-specificabnormalreturnandoperatingperformance. . . . 92
6.3 FurtherRobustnessTests. . . . . . . . . . . . . . . . . . . . . . . . . . 93
7 Concluding Remarks 97
Appendix 99
Bibliography 127