ARTIFICIAL INTELLIGENCE IN FINANCIAL FORECASTING: TECHNIQUES AND APPLICATIONS
DOI:
https://doi.org/10.29121/shodhkosh.v5.i6.2024.1817Keywords:
Artificial intelligence (AI), Financial Forecasting, ANN, SVM, Fuzzy LogicAbstract [English]
The capacity of artificial intelligence to swiftly evaluate massive amounts of information and implement high-frequency trades (HFT) has made AI a valuable tool for human operators. The most important studies that use innovative techniques to predict patterns of financial assets are analysed in this article, along with an assessment of their usefulness and potential applications in investing in intricate financial sectors. These structures investigate connections and factors that impact trading performance via the application of machine learning and deep learning algorithms. Forecasts are calculated from either linear or nonlinear methods and often include sentiment evaluation or trend identification from internet-based participants. The majority of papers that have been examined have shown that their artificial intelligence can be used to trade financial markets successfully.
References
Ahmed, D.M., Hassan, M.M. and Mstafa, R.J., 2022. A review on deep sequential models for forecasting time series data. Applied Computational Intelligence and Soft Computing, 2022(1), p.6596397. DOI: https://doi.org/10.1155/2022/6596397
Ahmed, S., Alshater, M.M., El Ammari, A. and Hammami, H., 2022. Artificial intelligence and machine learning in finance: A bibliometric review. Research in International Business and Finance, 61, p.101646. DOI: https://doi.org/10.1016/j.ribaf.2022.101646
Akter, S., McCarthy, G., Sajib, S., Michael, K., Dwivedi, Y.K., D’Ambra, J. and Shen, K.N., 2021. Algorithmic bias in data-driven innovation in the age of AI. International Journal of Information Management, 60, p.102387. DOI: https://doi.org/10.1016/j.ijinfomgt.2021.102387
Apsilyam, N.M., Shamsudinova, L.R. and Yakhshiboyev, R.E., 2024. The Application of Artificial Intelligence in the Economic Sector. Central Asian Journal of Education and Computer Sciences (CAJECS), 3(1), pp.1-12.
Ferreira, F.G., Gandomi, A.H. and Cardoso, R.T., 2021. Artificial intelligence applied to stock market trading: a review. IEEE Access, 9, pp.30898-30917. DOI: https://doi.org/10.1109/ACCESS.2021.3058133
Horak, J., Vochozka, M. and Kaisler, D., 2024, March. Investment Instruments: The Power of Neural Networks in Predicting Gold Price Trends. In Forum Scientiae Oeconomia (Vol. 12, No. 1, pp. 72-95).
Kumar, G., Jain, S. and Singh, U.P., 2021. Stock market forecasting using computational intelligence: A survey. Archives of computational methods in engineering, 28(3), pp.1069-1101. DOI: https://doi.org/10.1007/s11831-020-09413-5
Kumar, V., Ashraf, A.R. and Nadeem, W., 2024. AI-powered marketing: What, where, and how?. International Journal of Information Management, p.102783. DOI: https://doi.org/10.1016/j.ijinfomgt.2024.102783
Malali, A.B. and Gopalakrishnan, S., 2020. Application of artificial intelligence and its powered technologies in the indian banking and financial industry: An overview. IOSR Journal Of Humanities And Social Science, 25(4), pp.55-60.
McCarthy, J., 2020. How Evolution, Stories, and Irrationality Influence Decision Making in Financial Markets: Analyzing Whether We Can Leverage Our Innate Traits and Heuristics to Improve Outcomes (Doctoral dissertation, Duke University).
Mokhtari, S., Yen, K.K. and Liu, J., 2021. Effectiveness of artificial intelligence in stock market prediction based on machine learning. arXiv preprint arXiv:2107.01031. DOI: https://doi.org/10.5120/ijca2021921347
Pallathadka, H., Ramirez-Asis, E.H., Loli-Poma, T.P., Kaliyaperumal, K., Ventayen, R.J.M. and Naved, M., 2023. Applications of artificial intelligence in business management, e-commerce and finance. Materials Today: Proceedings, 80, pp.2610-2613. DOI: https://doi.org/10.1016/j.matpr.2021.06.419
Ruiz-Real, J.L., Uribe-Toril, J., Torres, J.A. and De Pablo, J., 2021. Artificial intelligence in business and economics research: Trends and future. Journal of Business Economics and Management, 22(1), pp.98-117. DOI: https://doi.org/10.3846/jbem.2020.13641
Tschider, C.A., 2020. Beyond the" Black Box". Denv. L. Rev., 98, p.683.
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