A Survey on Machine Learning and Deep Learning Models for Predicting Stock Movements

A Survey on Machine Learning and Deep Learning Models for Predicting Stock Movements

Priya Dohre1, Prof. Pankaj Rahguwanshi2

Abstract: The stock prices depend both on time as well as associated variables and finding patterns in among the variables aid forecasting future stock prices which is often termed as stock market forecasting. Stock market prediction extremely challenging due to the dependence of stock prices on several financial, socio-economic and political parameters etc. For real life applications utilizing stock market data, it is necessary to predict stock market data with low errors and high accuracy. This needs design of appropriate artificial intelligence (AI) and machine learning (ML) based techniques which can analyze large and complex data sets pertaining to stock markets and forecast future prices and trends in stock prices with relatively high accuracy. This paper presents a comprehensive review on the various techniques used in recent contemporary papers for stock market forecasting.

Keywords: Time Series Models, Stock Market Forecasting, Artificial Intelligence, Artificial Neural Networks, Forecasting accuracy.