Abstract
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.
Publisher
Granthaalayah Publications and Printers
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