application of artificial intelligence algorithms in stock market forecasting

New methods of machine learning in artificial intelligence (ai), changing the parameters and naturally finding the most logical and optimal solution possible based on what has been learned in the past, reducing the search space, reduce decision error. the use of these new methods of calculation, mathematics, and artificial intelligence has increased in recent years in the capital market, but most of the methods of portfolio construction are based on the traditional methods of the past and, of course, more in the category of asset classification. in this paper, most algorithms that had been used in other research are implemented and tested. the results of this research show that pso (particle swarm optimization) and gwo (grey wolf optimizer) are the best algorithms for forecasting financial markets. both algorithms have the same capability and show good results.