EFFECT OF STOCK INDEX PARAMETERS ON FORECASTING THE HIGH STOCK VALUE OF VISA STEEL USING DEEP LEARNING NEURAL NETWORK MODEL

Authors

  • Sasmita Kumari Nayak , Mohammed Siddique

Abstract

The stock markets contribute a largescope in economic development of India. The banking industrygrip majority
share between other industries in Indian stock trading consequence. The investors in the stock market use to
bear certain risk for their predictable returns in the future. Investment decisions are usually taken by considering
different fundamental factors both internal and external. Apart from fundamental factors which replicated in the
security prices, there are numerous additional factors that can influence investment are stock prices, volume of
trading, spread, turnover etc.The paper explores the effect of different variables on the high stock price of Visa
Steelconsidering daily data over the period 4 Jan 2010 to 23 Apr 2020. For the study the weighted average
price (WAP), number of shares, number of trades, total turnover (in INR), deliverable quantity, percent
deliverable quantity to traded quantity, spread high and low, spread open and close and the high stock price of
the organizationare noted. High stock price is considered as output while other parameters are used as input.
Pipeline Pilot module of Biovia software (DassaultSystems of France) is used for analysis. The software
provides different built-in components to develop a machine learning model and use the model for prediction.

Downloads

Published

2020-12-01

How to Cite

Sasmita Kumari Nayak , Mohammed Siddique. (2020). EFFECT OF STOCK INDEX PARAMETERS ON FORECASTING THE HIGH STOCK VALUE OF VISA STEEL USING DEEP LEARNING NEURAL NETWORK MODEL. International Journal of Modern Agriculture, 9(4), 227 - 236. Retrieved from http://modern-journals.com/index.php/ijma/article/view/207

Issue

Section

Articles