The stock market as a leading economic indicator an application of granger causality

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The Stock Market as a Leading Indicator: An Application of Granger Causality

Identification of main differentiating factors among the available solutions. The quality of the interpretation of the sentiment in the online buzz in the social media and the online news can determine the predictability of financial markets and cause huge gains or losses. That is why a number of researchers have turned their full attention to the different aspects of this problem lately.

However, there is no well-rounded theoretical and technical framework for approaching the problem to the best of our knowledge.

We believe the existing lack of such clarity on the topic is due to its interdisciplinary nature that involves at its core both behavioral-economic topics as well as artificial intelligence.

We dive deeper into the interdisciplinary nature and contribute to the formation of a clear frame of discussion. We review the related works that are about market prediction based on online-text-mining and produce a picture of the the stock market as a leading economic indicator an application of granger causality components that they all have.

We, furthermore, compare each system with the rest ira for college investment options identify their main differentiating factors. Our comparative analysis of the systems expands onto the theoretical and technical foundations behind each.

This work should help the research community to structure this emerging field and identify the exact aspects which require further research and are of special significance. Journals Books Register Sign in Sign in using your ScienceDirect credentials Username.

EconStor: Is the stock market a leading indicator of economic activity in nigeria?

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JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Expert Systems with Applications Volume 41, Issue 1615 NovemberPages Author links open the author workspace.

Opens the author workspace Opens the author workspace a. Numbers and letters correspond to the affiliation list. Click to expose these in author workspace Saeed Aghabozorgi.

Click to expose these in author workspace Teh Ying Wah.

Click to expose these in author workspace David Chek Ling Ngo. Abstract The quality of the interpretation of the sentiment in the online buzz in the social media and the online news can determine the predictability of financial markets and cause huge gains or losses. Keywords Online sentiment analysis.

Social media text mining. Stock prediction based on news.

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