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Modeling and Forecasting Stock Index Returns using Intermarket Factor Models: Predicting Returns and Return Spreads using Multiple Regression and Classication
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2015 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The purpose of this thesis is to examine the predictability of stock indices with regression models based on intermarket factors. The underlying idea is that there is some correlation between past price changes and future price changes, and that models attempting to capture this could be improved by including information derived from correlated assets to make predictions of future price changes. The models are tested using the daily returns from Swedish stock indices and evaluated from a portfolio perspective and their statistical signicance. Prediction of the direction of the price is also tested by Support vector machine classication on the OMXS30 index. The results indicate that there is some predictability in the market, in disagreement with the random walk hypothesis.

Abstract [sv]

Syftet med denna uppsats är att undersöka förutsägbara tendenser hos aktieindex med regressionsmodeller baserade på intermarket-faktorer. The bakomliggande idén är att det existerar en viss korrelation mellan föregående prisrörelser och framtida prisrörelser, och att modeller som försöker fånga det kan förbättras genom att inkludera information från korrelerade tillgångar för att förutspå framtida prisförändringar. Modellerna testas med dagliga data på svenska aktieindex och utvärderas från ett portföljperspektiv och deras statistiska signifikans. Förutsägelser av riktningen hos priset testas också genom klassifikation med en Stödvektormaskin på OMXS30-index. Resultaten indikerar att det finns vissa förutsägbara tendenser i motsats till hypotesen om slumpmässiga aktiepriser.

Place, publisher, year, edition, pages
2015. , 23 p.
National Category
Mathematical Analysis
Identifiers
URN: urn:nbn:se:kth:diva-167635OAI: oai:DiVA.org:kth-167635DiVA: diva2:813380
Available from: 2015-05-22 Created: 2015-05-22 Last updated: 2015-05-22Bibliographically approved

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