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Can IPO first day returns be predicted? A multiple linear regression analysis
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Kan förstadagsavkastningen efter börsintroduktioner förutses? En multipel linjär regressionanalys (Swedish)
Abstract [en]

During the last three years the Swedish stock market has showed a strong upwards movement from the lows of 2016. At the same time the IPO activity has been large and a lot of the offerings have had a positive return during the first day of trading in the market.

The goal of this study is to analyze if there is any particular IPO specific data that has a correlation with the first day return and if it can be used to predict the first day return for future IPO’s. If any regressors were shown to have correlation with the first day return, the goal is also to find a subset of regressors with even higher predictability. Then to classify which regressors show the highest correlation with a large positive return. The method which has been used is a multiple linear regression with IPO-data from the period 2017-2018.

The results from the study imply that none of the chosen regressors show any significant correlation with the first day return. It is a complicated process which might be difficult to simplify and quantify into a regression model, but further studies are needed to draw a conclusion if there are any other qualitative factors which correlate with the first day return.

Abstract [sv]

Under de senaste tre åren har den svenska aktiemarknaden visat en kraftigt uppåtgående rörelse från de låga nivåerna 2016. Samtidigt har det varit hög IPO-aktivitet, där många noteringar har haft en positiv avkastning under den första handelsdagen.

Målet med denna studie är att analysera om det finns särskilda IPO-specifika faktorer som påvisar samband med avkastningen från första handelsdagen och om det kan användas för att förutsäga utvecklingen under första handelsdagen för framtida noteringar. Om regressorerna visade korrelation är målet sedan att ta fram de bästa av dessa för att se om det ökar modellens säkerhet. Vidare var det av intresse att visa vilka regressorer som korrelerar med en positiv avkastning. Metoden som användes var en multipel linjär regression med historisk data från perioden 2017-2018.

Studiens resultat visar att ingen av de valda regressorerna har någon signifikant korrelation med avkastningen under första handelsdagen. Börsintroduktioner är komplicerade processer som kan vara svåra att förenkla och kvantifiera i en regressionsmodell, men ytterligare studier behövs för att dra en slutsats om det finns andra kvalitativa faktorer som kan förklara utvecklingen under första handelsdagen.

Place, publisher, year, edition, pages
2019.
Series
TRITA-SCI-GRU ; 2019:162
Keywords [en]
Statistic, applied mathematics, financial mathematics, IPO, regression
Keywords [sv]
Statistik, tillämpad matematik, finansiell matematik, IPO, börsintroduktion, regression
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-254293OAI: oai:DiVA.org:kth-254293DiVA, id: diva2:1334688
Subject / course
Applied Mathematics and Industrial Economics
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Supervisors
Examiners
Available from: 2019-07-03 Created: 2019-07-03 Last updated: 2019-07-03Bibliographically approved

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