100% satisfaction guarantee Immediately available after payment Both online and in PDF No strings attached
logo-home
CS 610 Machine Learning Notes $13.99   Add to cart

Class notes

CS 610 Machine Learning Notes

 0 view  0 purchase

This is a comprehensive and detailed note on machine learning;stock price prediction using LSTM.

Preview 2 out of 7  pages

  • November 18, 2024
  • 7
  • 2022/2023
  • Class notes
  • Prof. adrian
  • All classes
All documents for this subject (5)
avatar-seller
anyiamgeorge19
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/348390803



Stock Price Prediction Using LSTM

ArticleinTest Engineering and Management · January 2021



CITATIONS READS
9 14,556


2 authors, including:

Mallikarjuna Shastry Pm
Reva University
13 PUBLICATIONS11 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
info.pramodbs@gmail.com

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

The benefits of buying summaries with Stuvia:

Guaranteed quality through customer reviews

Guaranteed quality through customer reviews

Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.

Quick and easy check-out

Quick and easy check-out

You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.

Focus on what matters

Focus on what matters

Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!

Frequently asked questions

What do I get when I buy this document?

You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.

Satisfaction guarantee: how does it work?

Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.

Who am I buying these notes from?

Stuvia is a marketplace, so you are not buying this document from us, but from seller anyiamgeorge19. Stuvia facilitates payment to the seller.

Will I be stuck with a subscription?

No, you only buy these notes for $13.99. You're not tied to anything after your purchase.

Can Stuvia be trusted?

4.6 stars on Google & Trustpilot (+1000 reviews)

75323 documents were sold in the last 30 days

Founded in 2010, the go-to place to buy study notes for 14 years now

Start selling
$13.99
  • (0)
  Add to cart