INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15
Prediction of stock price with enhanced deep learning model
Authors Name:
Bhakirathi B
, M. Moogambikai
Unique Id:
IJSDR2009055
Published In:
Volume 5 Issue 9, September-2020
Abstract:
Prediction of the stock price and in specific the trend the stock price will follow is an important task in various perspectives. Recurrent neural networks are used for this task. Experimental analyses were made with different time stepss and different number of Long Short Term Memory (LSTM) layers. The dataset that has been used is the Google stock price of the past five years. It is a time series data which contains stock details of 1274 days. The performance parameters that are used for evaluating the model are explained variance score, r2score and the pearson coefficient . The results show the comparative performance of the recurrent neural network with different number of time steps and different number of LSTM layers. It has been observed that the model with 60 Time steps and 4 LSTM Layer performs better.
Keywords:
Stock price prediction
Cite Article:
"Prediction of stock price with enhanced deep learning model ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 9, page no.345 - 353, September-2020, Available :http://www.ijsdr.org/papers/IJSDR2009055.pdf
Downloads:
000337070
Publication Details:
Published Paper ID: IJSDR2009055
Registration ID:192484
Published In: Volume 5 Issue 9, September-2020
DOI (Digital Object Identifier):
Page No: 345 - 353
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631
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