Forecasting based on artificial intelligence tools found to be more efficient than other economic models.
Swati Sharma, Assistant Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India.
Financial forecasting is a major topic for research studies and number of forecasting methods are explored in these studies. The present study attempts to identify the role and significance of using artificial intelligence tools in financial forecasting by exploring existing literature on this theme. Literature on financial forecasting includes studies on forecasting of price, return, financial crisis, exchange rates, credit score, net assets value, financial performance indicators etc. Year-wise, Author-wise, Citation-wise, Affiliation-wise, Keywords-wise, Country-wise and Source-wise listing of literature are the parameter to conduct present study. Bibliometric method on Scopus database is employed.
This study provides insights on trends and future scope of Artificial Intelligence in Financial Forecasting. Neural Network, Decision Tree and Genetic Algorithm are the tools of AI used heavily for forecasting and performs better than other such AI tools. Stock trading, investment analysis and financial distress prediction are the decision for which AI tools are found to be used mostly. Hybrid and integrated model of AI has also been very much used and their prediction accuracy also found to be high. Generally, forecasting based on artificial intelligence tools found to be more efficient than other economic models.
Published in: AIP Conference Proceedings, 5th International Conference on ICT Integration in Technical Education, ETLTC 2023 in collaboration with the 2nd International Conference on Entertainment Technology and Management, ICETM 2023, Aizuwakamatsu, 24 January 2023 through 27 January 2023.
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