This paper presents a literature review on methods that have been used in the last two decades to predict Stock Market Indexes. Methods studied range from those enabling to grab the linear characteristics present in the stock market indexes, going through those that focus on non-linear features and finally hybrid methods that are more robust, since they capture linear and non-linear features. In addition, this research includes methods that use macroeconomic variables to predict indexes from different stock exchanges around the world.
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