Predictive elements of the stock market in the foothball industry.

In our study, we seek to establish a relationship between football clubs’ match results and their respective stock market performance. With the increasing commercialism of the football industry, more investors have been exploring opportunities to invest in this industry. Our study aims to explore...

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Main Authors: Seek, Kah Hoe., Tay, Henry Yong Qiang., Wong, Tracee Sze Wah.
Other Authors: Leon Chuen Hwa
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/51424
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-514242023-05-19T03:30:08Z Predictive elements of the stock market in the foothball industry. Seek, Kah Hoe. Tay, Henry Yong Qiang. Wong, Tracee Sze Wah. Leon Chuen Hwa Nanyang Business School DRNTU::Business::Finance::Banking DRNTU::Business::Industries and labor In our study, we seek to establish a relationship between football clubs’ match results and their respective stock market performance. With the increasing commercialism of the football industry, more investors have been exploring opportunities to invest in this industry. Our study aims to explore the potential relationship between the football clubs’ match performances and their stock returns. We identified six European football clubs, over the period from 2007 to 2012, for our analysis. The six clubs are as follows; Ajax (Holland), Besiktas (Turkey), Dortmund (Germany), Fenerbahce (Turkey), Juventus (Italy) and Lazio (Italy). At the 5% significant level, we concluded that there is significant evidence of a direct relationship between the two variables - match results and stock returns of football clubs. Additionally, we categorized our data into different competitions namely; domestic league, domestic cups and international competitions. In our findings, we identified that results from the domestic league have the strongest influence on stock returns as its beta is approximately five times more than the other two independent variables. Finally, with an adjusted R-square of 14%, there is an existence of a regression model to forecast the stock returns after knowing the match results. Therefore, investors may use this model to forecast the movement of these football clubs’ stock prices. BUSINESS 2013-04-02T09:10:00Z 2013-04-02T09:10:00Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/51424 en Nanyang Technological University 38 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Business::Finance::Banking
DRNTU::Business::Industries and labor
spellingShingle DRNTU::Business::Finance::Banking
DRNTU::Business::Industries and labor
Seek, Kah Hoe.
Tay, Henry Yong Qiang.
Wong, Tracee Sze Wah.
Predictive elements of the stock market in the foothball industry.
description In our study, we seek to establish a relationship between football clubs’ match results and their respective stock market performance. With the increasing commercialism of the football industry, more investors have been exploring opportunities to invest in this industry. Our study aims to explore the potential relationship between the football clubs’ match performances and their stock returns. We identified six European football clubs, over the period from 2007 to 2012, for our analysis. The six clubs are as follows; Ajax (Holland), Besiktas (Turkey), Dortmund (Germany), Fenerbahce (Turkey), Juventus (Italy) and Lazio (Italy). At the 5% significant level, we concluded that there is significant evidence of a direct relationship between the two variables - match results and stock returns of football clubs. Additionally, we categorized our data into different competitions namely; domestic league, domestic cups and international competitions. In our findings, we identified that results from the domestic league have the strongest influence on stock returns as its beta is approximately five times more than the other two independent variables. Finally, with an adjusted R-square of 14%, there is an existence of a regression model to forecast the stock returns after knowing the match results. Therefore, investors may use this model to forecast the movement of these football clubs’ stock prices.
author2 Leon Chuen Hwa
author_facet Leon Chuen Hwa
Seek, Kah Hoe.
Tay, Henry Yong Qiang.
Wong, Tracee Sze Wah.
format Final Year Project
author Seek, Kah Hoe.
Tay, Henry Yong Qiang.
Wong, Tracee Sze Wah.
author_sort Seek, Kah Hoe.
title Predictive elements of the stock market in the foothball industry.
title_short Predictive elements of the stock market in the foothball industry.
title_full Predictive elements of the stock market in the foothball industry.
title_fullStr Predictive elements of the stock market in the foothball industry.
title_full_unstemmed Predictive elements of the stock market in the foothball industry.
title_sort predictive elements of the stock market in the foothball industry.
publishDate 2013
url http://hdl.handle.net/10356/51424
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