An Effective Time Series Analysis for Equity Market Prediction Using Deep Learning Model

Akshay Sachdeva · Geet Jethwani · Chinthakunta Manjunath · M. Balamurugan

29 citations0/0 files storedInternational Conference on Data Science and Communication (IconDSC)

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Stock Market Forecasting Methods Forecasting Techniques and Applications Time Series Analysis and Forecasting

Abstract

A stock Exchange is a market where securities are traded. Every day, billions are traded at various stock exchanges across the world. In recent years prediction of movement of stock market is regarded as fascinating and has created a demand in financial market time series prediction. A precise forecasting of equity market is needed to provide higher returns for investors. Since there is high complexity in predicting stock market profits, developing models for it becomes difficult. The data mining and machine learning techniques has played an important role in Prediction of stock market movement. This study attempted to develop a deep learning model using Recurrent Neural Network for forecasting movement in the National Stock Exchange of India's benchmark broad based stock market index(NIFTY 50) for the Indian equity market. In this paper the NIFTY 50 index and INFYOSYS Ltd historical data from Yahoo finance companies has been selected for forecasting and analysis.

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References

2001Application of support vector machines in financial time series forecasting 2011Using artificial neural network models in stock market index prediction 2018NSE Stock Market Prediction Using Deep-Learning Models 2018An innovative neural network approach for stock market prediction 1996A comparison of artificial neural network and time series models for forecasting commodity prices 2016Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model 2010Forecasting stock exchange movements using neural networks: Empirical evidence from Kuwait 2017A Deep Neural-Network Based Stock Trading System Based on Evolutionary Optimized Technical Analysis Parameters

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