PREDICTION OF STOCK VOLUME FROM DOW JONES INDEX USING BUSINESS ANALYTICS CONCEPT

Anastacia Anastacia, Evita Linata, Ivana Jocelyn, Veline Chensiery, Genesis Sembiring

Abstract


Because of human constraints in computational reasoning, rational decision making is confined, which is why people experience bounded rationality. In many cases, a decision support system is required to help researchers make decision, including in predicting variables in stock market. Trading volume is one of the most important factors influencing the stock market's behavior. The higher the trading volume of a stock, the more active and liquid the market is which made it more attractive because the more liquid a stock is, the narrower its spread will be and there will be less risk of them being stuck with an undesired stock position. This study is made on the purpose of predicting trading volume from Dow Jones Index using the Business Analytics concept, including Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics. A managerial contribution was also developed for assisting a trader or investors in determining which index to invest on. Even so, the weighting results showed only minor variances in value among the 16 criteria used.


Keywords


prediction; stock volume; machine learning

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