The goal of this review is to describe the various methods used to predict the stock market, gold price and fuel price. The following paper describes the work that was done on investigating the application of regression, SVM, ELM, ANFIS techniques on the stock market price prediction. The report describes the various technologies with their accuracy level and efficiency in the test phase. It was found that support vector regression was the most effective out of the models used, although there are opportunities to expand this research further using additional techniques to incorporate the current affairs into the prediction features.