Dynamic Interaction Network to Model Co-Integration in IDX Leading Stocks

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Abstract

Most studies in the field of dynamic system analysis and modeling have focused more on the task of predicting movement of contributing variables only, whilst the extraction of co-integration patterns that govern movement of these variables has received little attention. This study is concerned with advances in the analysis and modeling of co-integration between leading stocks in the Indonesian Stock Exchange using a method capable of extracting multiple relationships between variables named the Dynamic Interaction Network. Being able to accomplish such task is expected to lead to a better understanding of co-integration state between leading stocks of the observed market, which in the end would lead toward a better means in predicting their price movement. Results from conducted experiment in this study suggest that: (1) the Dynamic Interaction Network is capable of modeling dynamic pattern of interactions between variables and (2) that the idea of including the states of co-integration between an assembly of time dependent variables into a prediction model appears to be beneficial to tackle the problem of time series prediction.
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 Artikel dapat diakses melalui:DOI: https://doi.org/10.1166/asl.2014.5624

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