Stock price prediction using data mining algorithms in the Iranian stock market

Abstract

Uncertainty in the capital market means the difference between the expected values and the values that occur in reality. The design of different analysis and forecasting methods in the capital market is also due to the high value and the need to know prices in the future with more certainty or less uncertainty. To earn profit in the capital market, investors have always sought to find the right share for investment and the right price for buying and selling, and therefore all the forecasting models proposed have always sought to answer three basic questions; What share, in what time frame and at what price should be bought or sold. In this article, we will use the combined method based on LSTM and a neural fuzzy system to predict stock prices in the Iranian market. The results show that the proposed method has an accuracy of over 90% in stock price prediction.