Stock Market Prediction Using Data Mining Techniques with R

Abstract

The Stock Exchange is the place where segments of registered associations are exchanged without inhibitions. Offers are bought and sold based on accessible records. Spending on stocks and assets is an important part of the economy. There are several parts that affect the cost of the offer. In any case, there is no concrete explanation for the costs of going up or down. This makes the adventure subject to various risks. Expenses for future actions are affected by past and current market records. As a result, corporate budget request procedures such as ARIMA and ARMA are used for transitional viewing. This document proposes a model of commercial desire for protections subject to examination of past data and the ARIMA model. This model will help budget professionals buy or sell stocks in a timely manner. The results of the hypotheses are displayed using the R programming language.