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Stock Price Prediction Using LSTM
ArticleinTest Engineering and Management · January 2021
CITATIONS READS
9 14,556
2 authors, including:
Mallikarjuna Shastry Pm
Reva University
13 PUBLICATIONS11 CITATIONS
SEE PROFILE
All content following this page was uploaded by Mallikarjuna Shastry Pm on 11 January 2021.
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, May - June 2020
ISSN: 0193-4120 Page No. 5246-5251
Stock Price Prediction Using LSTM
Pramod B S1*, Mallikarjuna Shastry P. M.2
1
M tech [pt] 6th Semester in CSE, REVA University, Bengaluru
2
Professor, REVA University, Bengaluru
1
Article Info Abstract
Volume 83 The prediction of stock value is a complex task which needs a robust
Page Number: 5246-5251 algorithm background in order to compute the longer term share
Publication Issue: prices. Stock prices are correlated within the nature of market; hence
May - June 2020
it will be difficult to predict the costs. The proposed algorithm using
the market data to predict the share price using machine learning
techniques like recurrent neural network named as Long Short Term
Memory, in that process weights are corrected for each data points
using stochastic gradient descent. This system will provide accurate
outcomes in comparison to currently available stock price predictor
algorithms. The network is trained and evaluated with various sizes
Article History of input data to urge the graphical outcomes.
Article Received: 19 November 2019
Revised: 27 January 2020 Keywords: Machine Learning, Stock Price Prediction, Long Short-
Accepted: 24 February 2020 Term Memory, Stock Market, Artificial neural Networks, National
Publication: 16 May 2020 Stock Exchange
1. Introduction stock exchange entity, the NSE was the first exchange in
The share market is a place where the shares of a public India to provide a modern, provides latest facility to the
company are traded. As discussed in [7] the volatile investors spread across the length and breadth of the
nature of the stock market makes it an area which needs country. It has thoroughly modern with all latest
an abundance of analysis with the old data predicated. facilities, , which provides investors with the facility to
The previous stock trend prediction algorithms use the trade from anywhere in India. This has a decisive role in
historic time series stock data. the typical scientific stock reforming the Indian equity market to add increased
price forecasting procedures are focused on the statistical transparency, convergence and efficiency to the capital
analysis of stock data. In the paper will develop a stock market. NSE's Common Index, The CNX NIFTY, is used
data predictor program that uses previous stock prices prodigiously by the investor across India as well as
and data will be treated as training sets for the program to globally. It provides accommodation for the exchange,
predict the stock prices of a particular share this program settlement and clearing in equity and debt market and
develops a procedure. additionally in derivatives. This is one of India's most
This model considers the historical equity share price astronomically enormous mazuma, currency and index
of a company price and applies RNN (Recurrent) options trading exchanges worldwide. There are
technique called Long Short Term Memory (LSTM). The numerous domestic and ecumenical companies which
proposed approach considers available historic data of a have an interest in the exchange. Several regional
share and it provides prediction on a particular feature. companies include TATA, WIPRO, HDFC and YES
BANK ltd. Among pilgrim investors, few are strategic
The features of shares are Opening price, day High, day
Low, previous day o price, Close price, Date of trading, holdings of the city party, Mauritius limited, Tiger
Total Trade Quantity and Turnover. The proposed model Ecumenical five holdings.
uses the time series analysis in order to predict a share As suggested by [3] The Long Short Term Memory
price for a required time span. the proposed will be (LSTM) networks are a type of recurrent neural network
considering Indian stock exchange Company named as (RNN) capable of addressing linear problems. LSTM is a
deep learning technique. Long-term Memory (LSTM)
The National Stock Exchange of India Limited
(NSE).The National Stock Exchange (NSE) is the Indian Units are enforced to learn very long sequences. This is a
more general version of the gated recurrent system.
LSTM is more benign than other deep learning methods
Published by: The Mattingley Publishing Co., Inc. 5246
Stock Price Prediction Using LSTM
ArticleinTest Engineering and Management · January 2021
CITATIONS READS
9 14,556
2 authors, including:
Mallikarjuna Shastry Pm
Reva University
13 PUBLICATIONS11 CITATIONS
SEE PROFILE
All content following this page was uploaded by Mallikarjuna Shastry Pm on 11 January 2021.
The user has requested enhancement of the downloaded file.
, May - June 2020
ISSN: 0193-4120 Page No. 5246-5251
Stock Price Prediction Using LSTM
Pramod B S1*, Mallikarjuna Shastry P. M.2
1
M tech [pt] 6th Semester in CSE, REVA University, Bengaluru
2
Professor, REVA University, Bengaluru
1
Article Info Abstract
Volume 83 The prediction of stock value is a complex task which needs a robust
Page Number: 5246-5251 algorithm background in order to compute the longer term share
Publication Issue: prices. Stock prices are correlated within the nature of market; hence
May - June 2020
it will be difficult to predict the costs. The proposed algorithm using
the market data to predict the share price using machine learning
techniques like recurrent neural network named as Long Short Term
Memory, in that process weights are corrected for each data points
using stochastic gradient descent. This system will provide accurate
outcomes in comparison to currently available stock price predictor
algorithms. The network is trained and evaluated with various sizes
Article History of input data to urge the graphical outcomes.
Article Received: 19 November 2019
Revised: 27 January 2020 Keywords: Machine Learning, Stock Price Prediction, Long Short-
Accepted: 24 February 2020 Term Memory, Stock Market, Artificial neural Networks, National
Publication: 16 May 2020 Stock Exchange
1. Introduction stock exchange entity, the NSE was the first exchange in
The share market is a place where the shares of a public India to provide a modern, provides latest facility to the
company are traded. As discussed in [7] the volatile investors spread across the length and breadth of the
nature of the stock market makes it an area which needs country. It has thoroughly modern with all latest
an abundance of analysis with the old data predicated. facilities, , which provides investors with the facility to
The previous stock trend prediction algorithms use the trade from anywhere in India. This has a decisive role in
historic time series stock data. the typical scientific stock reforming the Indian equity market to add increased
price forecasting procedures are focused on the statistical transparency, convergence and efficiency to the capital
analysis of stock data. In the paper will develop a stock market. NSE's Common Index, The CNX NIFTY, is used
data predictor program that uses previous stock prices prodigiously by the investor across India as well as
and data will be treated as training sets for the program to globally. It provides accommodation for the exchange,
predict the stock prices of a particular share this program settlement and clearing in equity and debt market and
develops a procedure. additionally in derivatives. This is one of India's most
This model considers the historical equity share price astronomically enormous mazuma, currency and index
of a company price and applies RNN (Recurrent) options trading exchanges worldwide. There are
technique called Long Short Term Memory (LSTM). The numerous domestic and ecumenical companies which
proposed approach considers available historic data of a have an interest in the exchange. Several regional
share and it provides prediction on a particular feature. companies include TATA, WIPRO, HDFC and YES
BANK ltd. Among pilgrim investors, few are strategic
The features of shares are Opening price, day High, day
Low, previous day o price, Close price, Date of trading, holdings of the city party, Mauritius limited, Tiger
Total Trade Quantity and Turnover. The proposed model Ecumenical five holdings.
uses the time series analysis in order to predict a share As suggested by [3] The Long Short Term Memory
price for a required time span. the proposed will be (LSTM) networks are a type of recurrent neural network
considering Indian stock exchange Company named as (RNN) capable of addressing linear problems. LSTM is a
deep learning technique. Long-term Memory (LSTM)
The National Stock Exchange of India Limited
(NSE).The National Stock Exchange (NSE) is the Indian Units are enforced to learn very long sequences. This is a
more general version of the gated recurrent system.
LSTM is more benign than other deep learning methods
Published by: The Mattingley Publishing Co., Inc. 5246
