Nowadays, generative artificial intelligence models have extensive applications, including finance. Artificial intelligence models in finance synthesise data to assist analysts in generating financial reports, detecting risks, predicting market trends, and optimising portfolios for managers and investors. However, it is crucial to determine the effectiveness of these financial functions. Therefore, this study aims to explore the financial capabilities of artificial intelligence in the finance domain and evaluate its performance through a case study on investment analysis. Within the scope of the study, a text-based artificial intelligence engine, Bing AI, was utilised to explore the financial capabilities of artificial intelligence. Bing AI was tasked with creating portfolios for companies listed on the BIST100 index based on their financial statements from 2019-2022, according to modern and traditional portfolio theories. The success of artificial intelligence in the financial field was evaluated by calculating the risk and return of the portfolio recommended by Bing AI for the period January 2023–November 2023. The findings indicate that Bing AI has the potential to partially support individuals with basic financial knowledge, but there is a need for further development in the application of finance.
Araci, D. T. (2019). FinBERT: Financial Sentiment Analysis with Pre-Trained Language Models. arXiv Preprint, Available at: arXiv:1908.10063.
Fatouros, G., Soldatos, J., Kouroumali, K., Makridis, G. & Kyriazi, D. (2023). Transforming Sentiment Analysis in the Financial Domain with ChatGPT, Machine Learning with Applications, 14,100508. doi.org/10.1016/j.mlwa.2023.100508
Adeshola, I., & Adepoju, A. P. (2023). The Opportunities and Challenges of ChatGPT in Education. Interactive Learning Environments, 1-14. doi.org/10.1080/10494820.2023.2253858
Ahangar, R. G., & Fietko, A. (2023). Exploring the Potential of ChatGPT in Financial Decision Making. In Advancement in Business Analytics Tools for Higher Financial Performance, IGI Global, 94-11.
Biswas, S. (2023a). Role of ChatGPT in Education. Available at SSRN: https://ssrn.com/abstract=4369981
Biswas, S. (2023b). Role of ChatGPT in Public Health. Annals of Biomedical Engineering, 51(5), 868-869.
Callanan, E., Mbakwe, A., Papadimitriou, A., Pei, Y., Sibue, M., Zhu, X., Ma, Z., Liu, X. & Shah, S. (2023). Can GPT Models Be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on Mock CFA Exams, doi.org/10.48550/arXiv.2310.08678
Cascella, M., Montomoli, J., Bellini, V. & Bignami, E. (2023). Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios. Journal of Medical Systems, 47(1), 33. doi.org/10.1007/s10916-023-01925-4
Chu, M. N. (2023). Assessing the Benefits of ChatGPT for Business: An Empirical Study on Organizational Performance. IEEE Access. doi.org/10.1109/ACCESS.2023.3297447
Derdiyok, T., Unal, S., & Doğru, Ç. (2023). ChatGPT's Ability to Determine Financial Status of Companies. Ufuk University Social Sciences Institute Journal, 12(23), 6-20. doi.org/10.58635/ufuksbedergi.1285729
Dowling, M., & Lucey, B. (2023). ChatGPT for (Finance) Research: The Bananarama Conjecture. Finance Research Letters, 53, 103662. doi.org/10.1016/j.frl.2023.103662
Forbes, (2023). Artificial Intelligence Applications in Investing, Available at: https://www.forbes.com/sites/qai/2023/02/24/artificial-intelligence-applications-in-investing/?sh=1908d86de216
George, A. S., George, A. H. & Martin, A. S. G. (2023). A Review of ChatGPT AI's Impact on Several Business Sectors. Partners Universal International Innovation Journal, 1(1), 9-23. doi.org/10.5281/zenodo.7644359
Göktaş, F., & Duran. A. (2019). A New Possibilistic Mean-Variance Model Based on the Principal Components Analysis: An Application on the Turkish Holding Stocks. Journal of Multiple-Valued Logic & Soft Computing, 32(5-6), 455-476.
Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences, 13(7), 692. doi.org/10.3390/educsci13070692
Guo, Y., Xu, Z., & Yang, Y. (2023). Is ChatGPT a Financial Expert? Evaluating Language Models on Financial Natural Language Processing. Avaliable at: arXiv preprint arXiv:2310.12664
Güçlü, F. (2022). Does Islamic Sensitivity Affect Portfolio Performance? A Different Perspective on Islamic Equity Investments. Journal of TESAM Academy, 9(1), 105–128. doi.org/10.30626/tesamakademi.1022807
Güçlü, F., & Şekkeli, F. E. (2020). Performance Analysis and Comparison of Islamic and Conventional Stock Mutual Funds in Turkey. Business & Management Studies: An International Journal, 8(5), 4463–4486. doi.org/10.15295/bmij.v8i5.1659
Hofert, M. (2023). Assessing ChatGPT’s Proficiency in Quantitative Risk Management. Risks, 11(9), 166. doi.org/10.3390/risks11090166
Huang, A. H., Wang, H., & Yang, Y. (2023). FinBERT: A Large Language Model for Extracting Information from Financial Text. Contemporary Accounting Research, 40(2), 806-841. doi.org/10.1111/1911-3846.12832
Jurafsky, D., & Martin, J. H. (2014). Speech and Language Processing (3. Edition draft). Available at: https://web.stanford.edu/~jurafsky/slp3/ed3book.pdf
Krause, D., (2023). Large Language Models and Generative AI in Finance: An Analysis of ChatGPT, Bard, and Bing AI. Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4511540
Küçüker, M. (2023). Artificial Intelligence Applications in Accounting: ChatGPT's Accounting Exam. Fırat University Journal of Social Sciences, 33(2), 875-888. doi.org/10.18069/firatsbed.1289885
Li, J., Dada, A., Kleesiek, J., & Egger, J. (2023). ChatGPT in Healthcare: A Taxonomy and Systematic Review. medRxiv, 2023-03. doi.org/10.1101/2023.03.30.23287899
Liu, Z., Huang, D., Huang, K., Li, Z., & Zhao, J. (2021). FinBERT: A Pre-trained Financial Language Representation
Model for Financial Text Mining. Proceedings of the Twenty-Ninth İnternational Conference on International Joint Conferences on Artificial Intelligence, 4513-4519 Available at: https://www.ijcai.org/proceedings/2020/622
Pradana, M., Elisa, H. P., & Syarifuddin, S. (2023). Discussing ChatGPT in Education: A Literature Review and Bibliometric Analysis. Cogent Education, 10(2), 2243134. doi.org/10.1080/2331186X.2023.2243134.
Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2018). Improving Language Understanding by Generative Pre-training. Available at: https://www.mikecaptain.com/resources/pdf/GPT-1.pdf
Rajpoot, P. K., & Parikh, A. (2023). GPT-FinRE: In-context Learning for Financial Relation Extraction Using Large
Language Models. ArXiv Preprint, Available at: https://arxiv.org/pdf/2306.17519.pdf
Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., Rodriguez, A., Joulin, A., Grave, E., Lample G. (2023). LLaMA: Open and Efficient Foundation Language Models. ArXiv Preprint, arXiv:2302.13971. doi.org/10.48550/arXiv.2302.13971
Wang, N., Yang, H., & Wang, C. D. (2023). FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets. ArXiv Preprint, arXiv:2310.04793. doi.org/10.48550/arXiv.2310.04793
Wang, Z., Li, Y., Wu, J., Soon, J. & Zhang, X. (2023). FinVis-GPT: A Multimodal Large Language Model for Financial Chart Analysis. doi.org/10.48550/arXiv.2308.01430
Wenzlaff, K. & Spaeth, S. (2022). Smarter than Humans? Validating How OpenAI’s ChatGPT Model Explains Crowdfunding, Alternative Finance and Community Finance. Available at SSRN: https://ssrn.com/abstract=4302443, http://dx.doi.org/10.2139/ssrn.4302443
Wu, S., Irsoy, O., Lu, S., Dabravolski, V., Dredze, M., Gehrmann, S., Kambadur, P., Rosenberg, D. & Mann, G. (2023). BloombergGPT: A Large Language Model for Finance, arXiv preprint, arXiv:2303.1756, doi.org/10.48550/arXiv.2303.17564
Xie, Q., Han, W., Zhang, X., Lai, Y., Peng, M., Lopez-Lira, A. & Huang. J. (2023). PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance. Cornell University. arXiv preprint, arXiv:2306.05443. doi.org/10.48550/arXiv.2306.05443
Yang, H., Liu, X.Y. & Wang, CD (2023). FinGPT: Open-Source Financial Large Language Models. Cornell University. arXiv preprint, arXiv:2306.06031. doi.org/10.48550/arXiv.2306.06031
Yang, Y., Tang, Y. & Tam, K.Y. (2023). InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning. Available at: https://www.arxiv-vanity.com/papers/2309.13064/
Yang, H., Liu, X.Y. & Wang, C.D. (2023) FinGPT: Opensource Financial Large Language Models. Cornell University. arXiv preprint, arXiv:2306.06031. doi.org/10.48550/arXiv.2306.06031
Zhang, L., Cai, W., Liu, Z., Yang, Z., Dai, W., Liao, Y., Qin, Q., Li,Y., Liu, X., Liu, Z., Zhu, Z. Wu, A. Guo, X. & Chen, Y. (2023). FinEval: A Chinese Financial Domain Knowledge Evaluation Benchmark for Large Language Models. Cornell University. ArXiv Preprint, arXiv:2308.09975. doi.org/10.48550/arXiv.2308.09975
BİLİM KURGUDAN GERÇEK HAYATA: YATIRIM DANIŞMANI OLARAK BING AI
Günümüzde üretken yapay zekâ modelleri finansın da dâhil olduğu oldukça geniş bir kullanım alanına sahiptir. Finans alanında yapay zekâ modelleri verileri sentezleyerek analistlere; finansal rapor oluşturmada, risk tespit etmede, piyasa eğilimlerini tahmin etmede ve portföyleri optimize etmede yöneticilere ve yatırımcılara yardımcı olmaktadır. Ancak bütün bu finansal işlevleri ne derece etkin yerine getirdiğini belirlemek oldukça önemlidir. Bu nedenle çalışmada yapay zekânın finansal yeteneklerinin keşfedilmesi, yatırım analizi örnek olay incelemesi yoluyla performansının değerlendirilmesi amaçlanmıştır. Çalışma kapsamında, yapay zekânın finansal yeteneklerinin keşfedilmesi amacıyla, metin tabanlı bir yapay zekâ motoru olan Bing AI kullanılmıştır. Bing AI’dan BİST100 endeksindeki işletmelerin 2019-2022 dönemindeki finansal tablolarını dikkate alarak, modern ve geleneksel portföy teorilerine göre portföyler oluşturması istenmiştir. Bing AI'nın önerdiği portföyün Ocak 2023-Kasım 2023 dönemindeki risk ve getirisi hesaplanarak, yapay zekânın finansal alandaki başarısı değerlendirilmiştir. Elde edilen bulgular, Bing AI’nın finansal alanda temel bilgiye sahip kişilere kısmen de olsa destek olabilecek durumda olduğunu; ancak finansın uygulama alanında geliştirilmesine ihtiyaç duyduğunu göstermektedir.
The research falls within the category of studies exempt from ethical committee approval, as it exclusively relies on publicly accessible information and does not involve the collection of data from human subjects.
Kaynakça
Araci, D. T. (2019). FinBERT: Financial Sentiment Analysis with Pre-Trained Language Models. arXiv Preprint, Available at: arXiv:1908.10063.
Fatouros, G., Soldatos, J., Kouroumali, K., Makridis, G. & Kyriazi, D. (2023). Transforming Sentiment Analysis in the Financial Domain with ChatGPT, Machine Learning with Applications, 14,100508. doi.org/10.1016/j.mlwa.2023.100508
Adeshola, I., & Adepoju, A. P. (2023). The Opportunities and Challenges of ChatGPT in Education. Interactive Learning Environments, 1-14. doi.org/10.1080/10494820.2023.2253858
Ahangar, R. G., & Fietko, A. (2023). Exploring the Potential of ChatGPT in Financial Decision Making. In Advancement in Business Analytics Tools for Higher Financial Performance, IGI Global, 94-11.
Biswas, S. (2023a). Role of ChatGPT in Education. Available at SSRN: https://ssrn.com/abstract=4369981
Biswas, S. (2023b). Role of ChatGPT in Public Health. Annals of Biomedical Engineering, 51(5), 868-869.
Callanan, E., Mbakwe, A., Papadimitriou, A., Pei, Y., Sibue, M., Zhu, X., Ma, Z., Liu, X. & Shah, S. (2023). Can GPT Models Be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on Mock CFA Exams, doi.org/10.48550/arXiv.2310.08678
Cascella, M., Montomoli, J., Bellini, V. & Bignami, E. (2023). Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios. Journal of Medical Systems, 47(1), 33. doi.org/10.1007/s10916-023-01925-4
Chu, M. N. (2023). Assessing the Benefits of ChatGPT for Business: An Empirical Study on Organizational Performance. IEEE Access. doi.org/10.1109/ACCESS.2023.3297447
Derdiyok, T., Unal, S., & Doğru, Ç. (2023). ChatGPT's Ability to Determine Financial Status of Companies. Ufuk University Social Sciences Institute Journal, 12(23), 6-20. doi.org/10.58635/ufuksbedergi.1285729
Dowling, M., & Lucey, B. (2023). ChatGPT for (Finance) Research: The Bananarama Conjecture. Finance Research Letters, 53, 103662. doi.org/10.1016/j.frl.2023.103662
Forbes, (2023). Artificial Intelligence Applications in Investing, Available at: https://www.forbes.com/sites/qai/2023/02/24/artificial-intelligence-applications-in-investing/?sh=1908d86de216
George, A. S., George, A. H. & Martin, A. S. G. (2023). A Review of ChatGPT AI's Impact on Several Business Sectors. Partners Universal International Innovation Journal, 1(1), 9-23. doi.org/10.5281/zenodo.7644359
Göktaş, F., & Duran. A. (2019). A New Possibilistic Mean-Variance Model Based on the Principal Components Analysis: An Application on the Turkish Holding Stocks. Journal of Multiple-Valued Logic & Soft Computing, 32(5-6), 455-476.
Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences, 13(7), 692. doi.org/10.3390/educsci13070692
Guo, Y., Xu, Z., & Yang, Y. (2023). Is ChatGPT a Financial Expert? Evaluating Language Models on Financial Natural Language Processing. Avaliable at: arXiv preprint arXiv:2310.12664
Güçlü, F. (2022). Does Islamic Sensitivity Affect Portfolio Performance? A Different Perspective on Islamic Equity Investments. Journal of TESAM Academy, 9(1), 105–128. doi.org/10.30626/tesamakademi.1022807
Güçlü, F., & Şekkeli, F. E. (2020). Performance Analysis and Comparison of Islamic and Conventional Stock Mutual Funds in Turkey. Business & Management Studies: An International Journal, 8(5), 4463–4486. doi.org/10.15295/bmij.v8i5.1659
Hofert, M. (2023). Assessing ChatGPT’s Proficiency in Quantitative Risk Management. Risks, 11(9), 166. doi.org/10.3390/risks11090166
Huang, A. H., Wang, H., & Yang, Y. (2023). FinBERT: A Large Language Model for Extracting Information from Financial Text. Contemporary Accounting Research, 40(2), 806-841. doi.org/10.1111/1911-3846.12832
Jurafsky, D., & Martin, J. H. (2014). Speech and Language Processing (3. Edition draft). Available at: https://web.stanford.edu/~jurafsky/slp3/ed3book.pdf
Krause, D., (2023). Large Language Models and Generative AI in Finance: An Analysis of ChatGPT, Bard, and Bing AI. Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4511540
Küçüker, M. (2023). Artificial Intelligence Applications in Accounting: ChatGPT's Accounting Exam. Fırat University Journal of Social Sciences, 33(2), 875-888. doi.org/10.18069/firatsbed.1289885
Li, J., Dada, A., Kleesiek, J., & Egger, J. (2023). ChatGPT in Healthcare: A Taxonomy and Systematic Review. medRxiv, 2023-03. doi.org/10.1101/2023.03.30.23287899
Liu, Z., Huang, D., Huang, K., Li, Z., & Zhao, J. (2021). FinBERT: A Pre-trained Financial Language Representation
Model for Financial Text Mining. Proceedings of the Twenty-Ninth İnternational Conference on International Joint Conferences on Artificial Intelligence, 4513-4519 Available at: https://www.ijcai.org/proceedings/2020/622
Pradana, M., Elisa, H. P., & Syarifuddin, S. (2023). Discussing ChatGPT in Education: A Literature Review and Bibliometric Analysis. Cogent Education, 10(2), 2243134. doi.org/10.1080/2331186X.2023.2243134.
Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2018). Improving Language Understanding by Generative Pre-training. Available at: https://www.mikecaptain.com/resources/pdf/GPT-1.pdf
Rajpoot, P. K., & Parikh, A. (2023). GPT-FinRE: In-context Learning for Financial Relation Extraction Using Large
Language Models. ArXiv Preprint, Available at: https://arxiv.org/pdf/2306.17519.pdf
Touvron, H., Lavril, T., Izacard, G., Martinet, X., Lachaux, M.A., Lacroix, T., Rozière, B., Goyal, N., Hambro, E., Azhar, F., Rodriguez, A., Joulin, A., Grave, E., Lample G. (2023). LLaMA: Open and Efficient Foundation Language Models. ArXiv Preprint, arXiv:2302.13971. doi.org/10.48550/arXiv.2302.13971
Wang, N., Yang, H., & Wang, C. D. (2023). FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets. ArXiv Preprint, arXiv:2310.04793. doi.org/10.48550/arXiv.2310.04793
Wang, Z., Li, Y., Wu, J., Soon, J. & Zhang, X. (2023). FinVis-GPT: A Multimodal Large Language Model for Financial Chart Analysis. doi.org/10.48550/arXiv.2308.01430
Wenzlaff, K. & Spaeth, S. (2022). Smarter than Humans? Validating How OpenAI’s ChatGPT Model Explains Crowdfunding, Alternative Finance and Community Finance. Available at SSRN: https://ssrn.com/abstract=4302443, http://dx.doi.org/10.2139/ssrn.4302443
Wu, S., Irsoy, O., Lu, S., Dabravolski, V., Dredze, M., Gehrmann, S., Kambadur, P., Rosenberg, D. & Mann, G. (2023). BloombergGPT: A Large Language Model for Finance, arXiv preprint, arXiv:2303.1756, doi.org/10.48550/arXiv.2303.17564
Xie, Q., Han, W., Zhang, X., Lai, Y., Peng, M., Lopez-Lira, A. & Huang. J. (2023). PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance. Cornell University. arXiv preprint, arXiv:2306.05443. doi.org/10.48550/arXiv.2306.05443
Yang, H., Liu, X.Y. & Wang, CD (2023). FinGPT: Open-Source Financial Large Language Models. Cornell University. arXiv preprint, arXiv:2306.06031. doi.org/10.48550/arXiv.2306.06031
Yang, Y., Tang, Y. & Tam, K.Y. (2023). InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning. Available at: https://www.arxiv-vanity.com/papers/2309.13064/
Yang, H., Liu, X.Y. & Wang, C.D. (2023) FinGPT: Opensource Financial Large Language Models. Cornell University. arXiv preprint, arXiv:2306.06031. doi.org/10.48550/arXiv.2306.06031
Zhang, L., Cai, W., Liu, Z., Yang, Z., Dai, W., Liao, Y., Qin, Q., Li,Y., Liu, X., Liu, Z., Zhu, Z. Wu, A. Guo, X. & Chen, Y. (2023). FinEval: A Chinese Financial Domain Knowledge Evaluation Benchmark for Large Language Models. Cornell University. ArXiv Preprint, arXiv:2308.09975. doi.org/10.48550/arXiv.2308.09975
Altan, İ. M., & Kılıç, M. (2023). SCIENCE FICTION TO REAL LIFE: BING AI AS AN INVESTMENT ADVISOR. Ekonomi İşletme Ve Yönetim Dergisi, 7(2), 240-260. https://doi.org/10.7596/jebm.31122023.003