Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Predicting share price by using Multiple Linear Regression.
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering.
2013 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The aim of the project was to design a

multiple linear regression model and use it to predict the share’s closing price for 44 companies listed on the OMX Stockholm stock exchange’s Large Cap list. The model is intended to be used as a day trading guideline i.e. today’s information is used to predict tomorrow’s closing price. The regression was done in Microsoft Excel 2010[18] by using its built-in function LINEST. The LINEST-function uses the dependent variable y and all the covariates x to calculate the β-value belonging to each covariate. Several multiple linear regression models were created and their functionality was tested, but only seven models were better than chance i.e. more than 50 % in the right direction. To determine the most suitable model out of the remaining seven, Akaike’s Information Criterion (AIC), was applied. The covariates used in the final model were; Dow Jones closing price, Shanghai opening price, conjuncture, oil price, share’s opening price, share’s highest price, share’s lowest price, lending rate, reports, positive/negative insider trading, payday, positive/negative price target, number of completed transactions during one day, OMX Stockholm closing price, TCW index, increasing closing price three days in a row and decreasing closing price three days in a row.

The maximum average deviation between the predicted closing price and the real closing price of all the

44 shares predicted were 6,60 %. In predicting the correct direction (increase or decrease) of the 44 shares an average of 61,72 % were achieved during the time period 2012-02-22 to 2013-02-20. If investing 50.000 SEK in each company i.e. a total investment of 2.2 million SEK, the total yield when using the regression model during the year 2012-02-22 to 2013-02-20 would have been 259.639 SEK (11,80 %) compared to 184.171 SEK (8,37 %) if the shares were never to be traded with during the same period of time. Of the 44 companies analysed, 31 (70,45 %) of them were profitable when using the regression model during the year compared to 30 (68,18 %) if the shares were never to be sold during the same period of time. The difference in yield in percentage between the model and keeping the shares for the year was 40,98 %.

Place, publisher, year, edition, pages
2013. , 96 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-140645OAI: oai:DiVA.org:kth-140645DiVA: diva2:692167
Examiners
Available from: 2014-01-30 Created: 2014-01-30 Last updated: 2014-01-30Bibliographically approved

Open Access in DiVA

Gustaf Forslund & David Åkesson kandidatex.jobb. A Bachelor Thesis in Mathematical Statistics(2018 kB)6606 downloads
File information
File name FULLTEXT01.pdfFile size 2018 kBChecksum SHA-512
19c102e4870f054fe09524189b6e7a249d94b5105532e13e9197f3fcbcb90a5bfb0967af73a3acbedbd4bd8d421d61ce49610e1572665a5fe53afa25414c9ee5
Type fulltextMimetype application/pdf

By organisation
Aeronautical and Vehicle Engineering
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 6606 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 1516 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf