Araştırma Makalesi
Yıl 2022,
Cilt: 11 Sayı: 3, 222 - 232, 31.12.2022
Öz
Destekleyen Kurum
TÜBİTAK
Proje Numarası
121E733
Kaynakça
- A. Altan, S. Karasu, The effect of kernel values in support vector machine to forecasting performance of financial time series, The Journal of Cognitive Systems, 4(1), (2019) 17-21.
- O. B. Sezer, M. U. Güdelek, A. M. Özbayoğlu, Financial time series forecasting with deep learning: A systematic literature review: 2005–2019, Applied Soft Computing, 90, (2020) 106181.
- C. Rudin, C. Chen, Z. Chen, H. Huang, L. Semenova, C. Zhong, Interpretable machine learning: Fundamental principles and 10 grand challenges, Statistics Surveys, 16, (2022) 1-85.
- I. K. Nti, A. F. Adekoya, B. A. Weyori, A systematic review of fundamental and technical analysis of stock market predictions, Artificial Intelligence Review, 53, (2020) 3007-3057.
- Y. Huang, Y. Gao, Y. Gan, M. Ye, A new financial data forecasting model using genetic algorithm and long short-term memory network, Neurocomputing, 425, (2021) 207-218.
- Tradingview, Tradingview platform, retrieved from http://www.tradingview.com. Accessed on August 13, 2022.
- Y. Santur, Candlestick chart based trading system using ensemble learning for financial assets, Sigma Journal of Engineering and Natural Sciences, 40(2), (2022) 370-379.
- J. Roeder, M. Palmer, J. Muntermann, Data-driven decision-making in credit risk management: The information value of analyst reports, Decision Support Systems, 158, (2022) Article ID: 113770.
- Fundamental Analysis Ratios, retrieved from https://www.wallstreetmojo.com/ratio-analysis. Accessed on August 13,2022.
- N. R. Mustika, N. Novrina, Automated Black Box Testing using Selenium Python, International Journal of Computer Science and Software Engineering, 7(9), (2018) 201-204.
- KAP, Public Disclosure Platform, retrieved from https://www.kap.org.tr/en. Accessed on August 13, 2022.
- Yahoo Finance. Finance, retrieved from yahoo.com. Accessed on August 13, 2022.
- Ü. Aycel, Y. Santur, A new moving average approach to predict the direction of stock movements in algorithmic trading, Journal of New Results in Science, 11(1), (2022) 13-25.
- M. Etemad, A. Soares, P. Mudroch, S. A. Bailey, S. Matwin, Developing an advanced information system to support ballast water management, Management of Biological Invasions, 13(1), (2022) 68-80.
- Y. Santur, Deep learning-based regression approach for algorithmic stock trading: A case study of the Bist30, Gümüşhane University Journal of Science and Technology, 10(4), (2020) 1195-1211.
- E. Özhan, E. Uzun, The Analysis of Big Financial Data Through Artificial Intelligence Methods, Impact of Artificial Intelligence on Governance, Economics and Finance, Springer Nature Singapore, 1, (2021) 51-79.
- U. Erkan, A precise and stable machine learning algorithm: eigenvalue classification (EigenClass), Neural Computing and Applications, 33(10), (2021) 5381-5392.
- S. Memiş, S. Enginoğlu, U. Erkan, Numerical data classification via distance-based similarity measures of fuzzy parameterized fuzzy soft matrices, IEEE Access, 9, (2021) 88583-88601.
- Ü. Aycel, Y. Santur, A new algorithmic trading approach based on ensemble learning and candlestick pattern recognition in financial assets, Turkish Journal of Science and Technology, 17(2), (2022) 167-184.
Yıl 2022,
Cilt: 11 Sayı: 3, 222 - 232, 31.12.2022
Öz
There are two main benefits of using fundamental analysis for investors and portfolio managers. First, investing in a company with good ratios has lower risks. The second reason is that it is possible to evaluate share prices with internal valuation methods based on ratios. These price valuations can be more meaningful when combined with technical analysis data. Many data terminals provide processes such as fundamental analysis data and price valuation on a paid and licensed basis. However, the balance sheet data of publicly traded markets are publicly available and can be obtained and interpreted by web scraping methods. This study presents an approach in which basic analysis and price evaluation are made with balance sheets and ratios using open-source tools and web scraping.
Anahtar Kelimeler
Django Financial forecasting Fundamental analysis Selenium Web scraping
Proje Numarası
121E733
Kaynakça
- A. Altan, S. Karasu, The effect of kernel values in support vector machine to forecasting performance of financial time series, The Journal of Cognitive Systems, 4(1), (2019) 17-21.
- O. B. Sezer, M. U. Güdelek, A. M. Özbayoğlu, Financial time series forecasting with deep learning: A systematic literature review: 2005–2019, Applied Soft Computing, 90, (2020) 106181.
- C. Rudin, C. Chen, Z. Chen, H. Huang, L. Semenova, C. Zhong, Interpretable machine learning: Fundamental principles and 10 grand challenges, Statistics Surveys, 16, (2022) 1-85.
- I. K. Nti, A. F. Adekoya, B. A. Weyori, A systematic review of fundamental and technical analysis of stock market predictions, Artificial Intelligence Review, 53, (2020) 3007-3057.
- Y. Huang, Y. Gao, Y. Gan, M. Ye, A new financial data forecasting model using genetic algorithm and long short-term memory network, Neurocomputing, 425, (2021) 207-218.
- Tradingview, Tradingview platform, retrieved from http://www.tradingview.com. Accessed on August 13, 2022.
- Y. Santur, Candlestick chart based trading system using ensemble learning for financial assets, Sigma Journal of Engineering and Natural Sciences, 40(2), (2022) 370-379.
- J. Roeder, M. Palmer, J. Muntermann, Data-driven decision-making in credit risk management: The information value of analyst reports, Decision Support Systems, 158, (2022) Article ID: 113770.
- Fundamental Analysis Ratios, retrieved from https://www.wallstreetmojo.com/ratio-analysis. Accessed on August 13,2022.
- N. R. Mustika, N. Novrina, Automated Black Box Testing using Selenium Python, International Journal of Computer Science and Software Engineering, 7(9), (2018) 201-204.
- KAP, Public Disclosure Platform, retrieved from https://www.kap.org.tr/en. Accessed on August 13, 2022.
- Yahoo Finance. Finance, retrieved from yahoo.com. Accessed on August 13, 2022.
- Ü. Aycel, Y. Santur, A new moving average approach to predict the direction of stock movements in algorithmic trading, Journal of New Results in Science, 11(1), (2022) 13-25.
- M. Etemad, A. Soares, P. Mudroch, S. A. Bailey, S. Matwin, Developing an advanced information system to support ballast water management, Management of Biological Invasions, 13(1), (2022) 68-80.
- Y. Santur, Deep learning-based regression approach for algorithmic stock trading: A case study of the Bist30, Gümüşhane University Journal of Science and Technology, 10(4), (2020) 1195-1211.
- E. Özhan, E. Uzun, The Analysis of Big Financial Data Through Artificial Intelligence Methods, Impact of Artificial Intelligence on Governance, Economics and Finance, Springer Nature Singapore, 1, (2021) 51-79.
- U. Erkan, A precise and stable machine learning algorithm: eigenvalue classification (EigenClass), Neural Computing and Applications, 33(10), (2021) 5381-5392.
- S. Memiş, S. Enginoğlu, U. Erkan, Numerical data classification via distance-based similarity measures of fuzzy parameterized fuzzy soft matrices, IEEE Access, 9, (2021) 88583-88601.
- Ü. Aycel, Y. Santur, A new algorithmic trading approach based on ensemble learning and candlestick pattern recognition in financial assets, Turkish Journal of Science and Technology, 17(2), (2022) 167-184.
Toplam 19 adet kaynakça vardır.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Mühendislik |
| Bölüm | Articles |
| Yazarlar | |
| Proje Numarası | 121E733 |
| Yayımlanma Tarihi | 31 Aralık 2022 |
| Yayımlandığı Sayı | Yıl 2022 Cilt: 11 Sayı: 3 |
Kaynak Göster
EBSCO |
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