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09-08-2017 | Methodologies and Application

Forecasting financial indicators by generalized behavioral learning method

Authors: Ömer Faruk Ertuğrul, Mehmet Emin Tağluk

Published in: Soft Computing | Issue 24/2018

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Abstract

Forecasting financial indicators (indexes/prices) is a complex and a quite difficult issue because they depend on many factors such as political events, financial ratios, and economic variables. Also, the psychological facts or decision-making styles of investors or experts are other major reasons for this difficulty. In this study, a generalized behavioral learning method (GBLM) was employed to forecast financial indicators, which are the indexes/prices of 34 different financial indicators (24 stock indexes, 2 forexes, 3 financial futures, and 5 commodities). The achieved results were compared with the reported results in the literature and the obtained results by artificial neural network, which is widely used and suggested for forecasting financial indicators. These results showed that GBLM can be successfully employed in short-term forecasting financial indicators by detecting hidden market behavior (pattern) from their previous values. Also, the results showed that GBLM has the ability to track the fluctuation and the main trend.

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Title: Forecasting financial indicators by generalized behavioral learning method
Authors: Ömer Faruk Ertuğrul
Mehmet Emin Tağluk
Publication date: 09-08-2017
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 24/2018
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-017-2768-3

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