Forecasting Direction of BIST 100 Index: An Integrated Machine Learning Approach

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Date

2021

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Springer Science and Business Media B.V.

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Civil Engineering
(2000)
The Atılım University Department of Civil Engineering was founded in 2000 as a pioneer for the Departments of Civil Engineering among the foundation schools of Ankara. It offers education in English. The Department of Civil Engineering has an academic staff qualified in all areas of the education offered. In addition to a high level of academic learning that benefits from learning opportunities through practice at its seven laboratories, the Department also offers a Cooperative Education program conducted in cooperation with renowned organizations in the construction sector. Accredited by MÜDEK (Association of Evaluation and Accreditation of Engineering Programs) (in 2018), our Department has been granted the longest period of accreditation to ever achieve through the association (six years). The accreditation is recognized by ENAEE (European Network for Accreditation of Engineering Education), and other international accreditation boards.
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Industrial Engineering
(1998)
Industrial Engineering is a field of engineering that develops and applies methods and techniques to design, implement, develop and improve systems comprising of humans, materials, machines, energy and funding. Our department was founded in 1998, and since then, has graduated hundreds of individuals who may compete nationally and internationally into professional life. Accredited by MÜDEK in 2014, our student-centered education continues. In addition to acquiring the knowledge necessary for every Industrial engineer, our students are able to gain professional experience in their desired fields of expertise with a wide array of elective courses, such as E-commerce and ERP, Reliability, Tabulation, or Industrial Engineering Applications in the Energy Sector. With dissertation projects fictionalized on solving real problems at real companies, our students gain experience in the sector, and a wide network of contacts. Our education is supported with ERASMUS programs. With the scientific studies of our competent academic staff published in internationally-renowned magazines, our department ranks with the bests among other universities. IESC, one of the most active student networks at our university, continues to organize extensive, and productive events every year.

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Abstract

In recent years trends in analyzing and forecasting financial time series moves from classical Box-Jenkins methodology to machine learning algorithms because of the non-linearity and non-stationary of the time series. In this study, we employed a machine learning algorithm called support vector machine to predict the daily price direction of BIST 100 index. In addition, we use random forest algorithm for feature selection and showed that by removing some features from the model, performance of the model increases. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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Feature selection, Financial time series, ISE 100, Random forest, Support vector machine

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Springer Proceedings in Complexity -- 7th International Symposium on Chaos, Complexity and Leadership, ICCLS 2020 -- 29 October 2020 through 31 October 2020 -- Virtual, Online -- 263269

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Start Page

33

End Page

46

URI

https://doi.org/10.1007/978-3-030-74057-3_5
 https://hdl.handle.net/20.500.14411/4025

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Scopus