Predicting the trend of stock market by examining its relationship with macroeconomics variables

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Predicting the trend of stock market by examining its relationship with macroeconomics variables

Lukmanto, Laura - Personal Name; Lukas - Personal Name;

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.

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B00531 (wh) Available

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Series Title: -
Call Number: 531
Publisher: : Swiss German University., 2009
Collation: -
Language: English
ISBN/ISSN: -
Classification: NONE
Content Type: -
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Edition: -
Subject(s): IT
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