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Post Earnings-Announcement Drift: A Comparative Study on the Impact of Measure Calculations
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Post Earnings-Announcement Drift : En jämförelsestudie av måttkonstruktionens påverkan​ (Swedish)
Abstract [en]

This thesis investigate the phenomenon of post earnings-announcement drift where good (bad) interim reports are followed by an upward (downward) drift in stock price. The main question is whether the specific construction of the drift measure has any impact on the drift. The results show that reported earnings are more suited than earnings per share as a measure of earnings. Stock price is seen to affect the decile sorting in many of the measures and as such, using the standard deviation of past expected earnings is recommended. No definitive conclusion can be drawn about the model of unexpected earnings for the standardized unexpected earnings measure. Standardized unexpected earnings outperform earnings announcement returns in the size of drift. 

Abstract [sv]

Examensarbetet undersöker fenomenet “Post-Earnings Announcement Drift” där bra (dåliga) kvartalsrapporter följs av generell uppgång (nedgång) i aktiepris. Huvudfrågeställningen är om en specifik beräkningsmetod av måttet har någon inverkan på resultatet, d.v.s. storleken eller riktning på avkastningen. Resultatet visar att periodens resultat/vinst är mer lämpat i beräkningssyfte än vinst per aktie. Aktiepris visar sig ha en påverkan vid indelning av deciler i många fall, och att använda standarddeviationen som standardiserande nämnare är rekommenderat. Ingen slutgiltig slutsats kan dras rörande modellen för oväntad vinst i fallet då måttet baseras på ”Standardized Unexpected Earnings”-modellen. Nämnda modell beskriver däremot det undersökta fenomenet bättre om man ser till storleken av aktieprisutveckling.

Place, publisher, year, edition, pages
2016.
Series
TRITA-MAT-E, 2016:22
National Category
Mathematical Analysis
Identifiers
URN: urn:nbn:se:kth:diva-187898OAI: oai:DiVA.org:kth-187898DiVA: diva2:934149
Subject / course
Mathematical Statistics
Educational program
Master of Science - Applied and Computational Mathematics
Supervisors
Examiners
Available from: 2016-06-08 Created: 2016-05-31 Last updated: 2016-06-08Bibliographically approved

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