Price prediction of the Borsa Istanbul banks index with traditional methods and artificial neural networks

In terms of asset size, the banking system constitutes 83% of the financial markets in Turkiye. Given the importance of the banking system in the Turkish capital market, this study offers a price forecasting analysis of the Borsa Istanbul Banks Index, which represents the domestic banking system, be...

Full description

Bibliographic Details
Main Author: Ilknur Ulku Armagan
Format: Article
Language:English
Published: Elsevier 2023-10-01
Series:Borsa Istanbul Review
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2214845023001126
_version_ 1797646825550774272
author Ilknur Ulku Armagan
author_facet Ilknur Ulku Armagan
author_sort Ilknur Ulku Armagan
collection DOAJ
description In terms of asset size, the banking system constitutes 83% of the financial markets in Turkiye. Given the importance of the banking system in the Turkish capital market, this study offers a price forecasting analysis of the Borsa Istanbul Banks Index, which represents the domestic banking system, between December 27, 1996, to August 31, 2023, using the traditional Autoregressive Integrated Moving Average (ARIMA) Model and two artificial intelligence-based deep learning models, namely, the Facebook Prophet Model (FPM) and Convolutional Neural Networks Model (CNNM). The findings indicate that the CNNM perform better than the other models. The results are useful for researchers working with time series data at the stage of method selection and investment firms and managers that are forecasting future stock price movements. Policy implications of the findings are discussed.
first_indexed 2024-03-11T15:07:24Z
format Article
id doaj.art-fa7537c95d654746a19e0212a4831c07
institution Directory Open Access Journal
issn 2214-8450
language English
last_indexed 2024-03-11T15:07:24Z
publishDate 2023-10-01
publisher Elsevier
record_format Article
series Borsa Istanbul Review
spelling doaj.art-fa7537c95d654746a19e0212a4831c072023-10-30T06:02:34ZengElsevierBorsa Istanbul Review2214-84502023-10-0123S30S39Price prediction of the Borsa Istanbul banks index with traditional methods and artificial neural networksIlknur Ulku Armagan0Isparta University of Applied Sciences, Keciborlu Vocational School, Finance Banking and Insurance Department, Isparta, TurkiyeIn terms of asset size, the banking system constitutes 83% of the financial markets in Turkiye. Given the importance of the banking system in the Turkish capital market, this study offers a price forecasting analysis of the Borsa Istanbul Banks Index, which represents the domestic banking system, between December 27, 1996, to August 31, 2023, using the traditional Autoregressive Integrated Moving Average (ARIMA) Model and two artificial intelligence-based deep learning models, namely, the Facebook Prophet Model (FPM) and Convolutional Neural Networks Model (CNNM). The findings indicate that the CNNM perform better than the other models. The results are useful for researchers working with time series data at the stage of method selection and investment firms and managers that are forecasting future stock price movements. Policy implications of the findings are discussed.http://www.sciencedirect.com/science/article/pii/S2214845023001126C55D53G12G17G21
spellingShingle Ilknur Ulku Armagan
Price prediction of the Borsa Istanbul banks index with traditional methods and artificial neural networks
Borsa Istanbul Review
C55
D53
G12
G17
G21
title Price prediction of the Borsa Istanbul banks index with traditional methods and artificial neural networks
title_full Price prediction of the Borsa Istanbul banks index with traditional methods and artificial neural networks
title_fullStr Price prediction of the Borsa Istanbul banks index with traditional methods and artificial neural networks
title_full_unstemmed Price prediction of the Borsa Istanbul banks index with traditional methods and artificial neural networks
title_short Price prediction of the Borsa Istanbul banks index with traditional methods and artificial neural networks
title_sort price prediction of the borsa istanbul banks index with traditional methods and artificial neural networks
topic C55
D53
G12
G17
G21
url http://www.sciencedirect.com/science/article/pii/S2214845023001126
work_keys_str_mv AT ilknurulkuarmagan pricepredictionoftheborsaistanbulbanksindexwithtraditionalmethodsandartificialneuralnetworks