Feed-Forward Deep Learning Model for Data Analysis and Prediction

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2018 by IJCTT Journal
Volume-63 Number-1
Year of Publication : 2018
Authors : Er.Hari K.C, Er.Rammani Adhikari, Er.Sharan Thapa
  10.14445/22312803/IJCTT-V63P102

MLA

MLA Style: Er.Hari K.C, Er.Rammani Adhikari, Er.Sharan Thapa "Feed-Forward Deep Learning Model for Data Analysis and Prediction" International Journal of Engineering Trends and Technology 63.1 (2018): 8-10.

APA Style: Er.Hari K.C, Er.Rammani Adhikari, Er.Sharan Thapa (2018).Feed-Forward Deep Learning Model for Data Analysis and Prediction. International Journal of Engineering Trends and Technology, 63(1), 8-10.

Abstract
Stock Market is a volatile market. Predicting the behaviour of stock is a difficult and challenging task. Investor from different sectors invests the money in stock market for the sake of high return but involves high risk. Feed forward deep learning model can be helpful to minimize the certain risk process by forecasting the behaviour of market by analyzing the data from previous years. The stock price of the company is analyzed to view the future behaviour and price using the neural network. The factors taken are maximum price, closing price and minimum price of stock. Forecasting the stock price using deep learning model is a new concept in the stock market of Nepal. It will surely motivate investors and traders to invest their money with less risk and high returns.

Reference
[1] S. Fatima and G. Hussain, "Statistical Modeling of KSE-100 Index using Hybrid financial System in NeuroComputing. Vol: 71. pp 2742-2746, 2008.
[2] A. Lu and A. Mackinley,"Stock Market Prices do not follow RandomWalks,"in doi.org/10.1093/rfs/1.1.41. Oxford Academic, 03 April,2015.
[3] D.Xiao, Z.Yue, L.Ting and D.Junwan, “Deep Learning for Event –Driven Stock Prediction” in IJCAI, pp 2327-2333, 2015
[4] Singh, R. & Srivastava, S. Multimed, “Stock Prediction using deep learning”, (2017) 76: 18569. https://doi.org/10.1007/s11042-016-4159-7
[5] S. Bobde and V. Rajput, "Stock Market Prediction using Hybrid Approach," in SBN:987-1-5090-1666. 2016/IEEE, 2016.
[6] I. Ali, K. Rehman, M. Khan and H. Afzal, "Casual Relationship between macro economic indicators and stock exchanges prices in Pakistan," in African Journal of Business Management vol 04, no:3 pp 312-314,2010, 2010
[7] S. Shen, H. Jiang and T. Zhang, "Stock Market Forecasting using Machine Learning Algorithm," in Standford University, 2012.
[8] N. Hung and Y. Zhawjun, "Profitability of Applying Simple Moving Average Trading Rules for Vietamese stock Market," in vol 02, no:03,pp 22-31Journal of Business Management, 2013.

Keywords
Deep learning, Neural network, Tensorflow, Stock Market, Feed-forward, Artificial Intelligence, time series forecasting, data analysis