A Novel AI-Based Stock Market Prediction Using Machine Learning Algorithm

Autor: Iyyappan. M, Sultan Ahmad, Sudan Jha, Afroj Alam, Muhammad Yaseen, Hikmat A. M. Abdeljaber
Rok vydání: 2022
Předmět:
Zdroj: Scientific Programming. 2022:1-11
ISSN: 1875-919X
1058-9244
DOI: 10.1155/2022/4808088
Popis: The time series forecasting system can be used for investments in a safe environment with minimized chances of loss. The Holt–Winters algorithm followed various procedures and observed the multiple factors applied to the neural network. The final module helps filter the system to predict the various factors and provides a rating for the system. This research work uses real-time dataset of fifteen stocks as input into the system and, based on the data, predicts or forecasts future stock prices of different companies belonging to different sectors. The dataset includes approximately fifteen companies from different sectors and forecasts their results based on which the user can decide whether to invest in the particular company or not; the forecasting will give an accurate result for the customer investments.
Databáze: OpenAIRE
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