National Bombay Stock Trade Market Expectation Utilizing KNN Calculation

Abstract

Predicting stock prices is a fascinating and difficult area of study. The economies of developed nations are compared to their power economies. As a result of their easy profits and low risk rate of return, stock markets are currently regarded as an illustrious trading field. For researchers in data mining and business, the stock market is thought to be a good place to work because of its numerous and constantly changing information sources. In order to assist investors, management, decision-makers, and users in making correct and informed investment decisions, we used the k-nearest neighbour algorithm and a non-linear regression approach in this paper to predict stock prices for a sample of six major companies listed on the Jordanian stock exchange. The results indicate that the KNN algorithm is reliable with a low error ratio; Consequently, the outcomes were reasonable and rational. Additionally, the prediction results were nearly identical to the actual stock prices, depending on the data on the stock price.