The Stock Price Prediction Formula Using the Concept of Equality in the Amount of Data Between the Average Difference of Order One and Two at Levels n and n+1

Abstract

Technological developments are getting faster, as is the dissemination of existing information, especially on the capital market. In order for investors to avoid losses from the capital market, a method is needed that is able to analyze the movement of the stock price. This study focuses on the application of the Data Scales Analysis (DSA) method which uses a formula with the concept of the same amount of data between the first and second order average differences at levels n and n + 1 for predicting the stock price of issuers, in predicting stock prices in the capital market. The resulting formula is named JIC-FLY 2 which is a new formula used to predict stock prices in the capital market. The population used in this study are issuers who are members of IDX 30 from the banking sub-sector with the sample used is the issuer of BBCA (PT Bank Central Asia Tbk). The results of this study note that the DSA method with this formula is able to produce the best predictive value, namely DSA 12 with an error percentage of 0.035%.