Lukmanto, Laura and Lukas, Lukas and Widiputra, Harya Damar (2009) Predicting The Trend of Stock Market by Examining Its Relationship with Macroeconomics Variables. Bachelor thesis, Swiss German University.

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Abstract

Predicting the value of stock market index has been a much discussed topic in both scientific and financial researches. Some of the researches claimed that macroeconomics factors are one of the significant indicators in determining the future values of stock market index. In this study, Dynamic Interaction Network (DIN), which was inspired by a Gene Regulatory Network (GRN) extraction method commonly used in bioinformatics, is used to discover important and complex dynamic relationship between stock market index and macroeconomics factors. The results showed that DIN is capable to reveal and model the patterns of dynamic relationship from the observed variables (i.e. stock market index and macroeconomics factors). Additionally, it is found that extracted network models can be used to predict movement of not only the stock market index but other macroeconomics factors as well in a considerably good-accuracy.

Item Type:	Thesis (Bachelor)
Subjects:	H Social Sciences > HG Finance > HG4551 Stock exchanges T Technology > T Technology (General) > T58.5 Information technology
Divisions:	Faculty of Engineering and Information Technology > Department of Information Technology
Depositing User:	Astuti Kusumaningrum
Date Deposited:	04 Nov 2020 02:43
Last Modified:	04 Nov 2020 02:43
URI:	http://repository.sgu.ac.id/id/eprint/996

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