Review
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Finansal Zaman Serilerini Tahminlemede Kullanılan Yöntemlere Genel Bir Bakış

Year 2022, Volume: 9 Issue: 1, 653 - 671, 30.06.2022
https://doi.org/10.35193/bseufbd.1087654

Abstract

Geçmişte olduğu gibi günümüzde de yatırımcılar için finansal verilerin trendinin tahmin edilebilmesi ve bu bilgi kullanılarak bir finansal strateji oluşturulması oldukça önemlidir. Fakat günümüzde hızlı internet bağlantıları ile finansal verilerin hızlı ulaşması ve bilişim ve bulut sistemlerindeki gelişmeler, finansal tahminlemek için yapay zekâ algoritmalarının kullanılması bu alanda rekabeti artırmaktadır. Fintech içinde portföy yönetimi gibi alanlarda yapay zekâ uygulamalarının kullanım payı gittikçe artmaktadır. Bu çalışmanın amacı finansal zaman serisi verileri tahminlemek için yapılan daha önceki akademik çalışmaları derlemek, zaman serilerinin tahmin etmek için kullanılan yapay zekâ algoritmalarını açıklamak ve tahmin edilen bazı finansal veri tiplerini ve bağımlılıklarını irdelemektir. Çalışma sonunda incelenen makalelerde kullanılan tekniklerin yeterlilikleri ve hangi veri tipi için hangi metodun daha başarılı sonuçlar verebileceği gibi çıkarımlar yapılmıştır.

References

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A General Review of the Methods Used Financial Time Series Forecasting

Year 2022, Volume: 9 Issue: 1, 653 - 671, 30.06.2022
https://doi.org/10.35193/bseufbd.1087654

Abstract

As in the past, it is very important for investors to be able to predict the trend of financial data and to create a financial strategy using this information. However, nowadays, rapid access to financial data with fast Internet connections, developments in informatics, and cloud systems, the use of artificial intelligence algorithms for financial forecasting increase competition in this field. The share of artificial intelligence applications in areas such as portfolio management in Fintech is increasing. The aim of this study is to compile previous academic studies to predict financial time series data, to explain artificial intelligence algorithms used to predict time series, and to examine some predicted financial data types and their dependencies. At the end of the study, inferences were made such as the adequacy of the techniques used in the articles examined and which method could yield more successful results for which data type.

References

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  • ‘The Dow Theory’ (2016) in Technical Analysis and Chart Interpretations. John Wiley & Sons, Ltd, 19–26. doi:10.1002/9781119204800.ch4.
  • Bustos, O. & Pomares-Quimbaya, A. (2020) ‘Stock market movement forecast: A Systematic review’, Expert Systems with Applications, 156, 113464–113464. doi:10.1016/j.eswa. 2020.113464.
  • Puschmann, T. (2017) ‘Fintech’, Business & Information Systems Engineering, 59(1), 69–76. doi:10.1007/s12599-017-0464-6.
  • Oleksiuk, A. (2019) ‘Machine Learning Use Cases in Banking and Finance’, Intellias [Preprint]. Available at: https://intellias.com/5-use-cases-of-machine-learning-in-fintech-and-banking/.
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  • Sezer, O.B., Gudelek, M.U. and Ozbayoglu, A.M. (2020) ‘Financial time series forecasting with deep learning: A systematic literature review: 2005–2019’, Applied Soft Computing Journal, 90, 106181–106181. doi:10.1016/j.asoc.2020.106181.
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  • Karakaş, E. (2019) ‘Çocuk Yoğun Bakım Ünitesine Olan Talebin Zaman Serisi Yöntemleri ile Tahmin Edilmesi’, European Journal of Science and Technology, 454–462. doi:10.31590/ejosat.624407.
  • Johannet, A. (2010) ‘Artificial Neural Network Models’, in Mathematical Models. John Wiley & Sons, Ltd, 419–443. doi:10.1002/9781118557853.ch14.
  • Yildiran, A. & Kandemı̇r, S.Y. (2018) ‘Yağış Miktarının Yapay Sinir Ağları ile Tahmini’, Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi, 5(2), 97–104.
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There are 65 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Nuh Yurduseven 0000-0001-7108-4940

Ahmet Anıl Müngen 0000-0002-5691-6507

Publication Date June 30, 2022
Submission Date March 18, 2022
Acceptance Date June 19, 2022
Published in Issue Year 2022 Volume: 9 Issue: 1

Cite

APA Yurduseven, N., & Müngen, A. A. (2022). Finansal Zaman Serilerini Tahminlemede Kullanılan Yöntemlere Genel Bir Bakış. Bilecik Şeyh Edebali Üniversitesi Fen Bilimleri Dergisi, 9(1), 653-671. https://doi.org/10.35193/bseufbd.1087654