UGC APPROVED ISSN 2278-1412

Archive

  Volume 13 | Issue 11

  Volume 13 | Issue 10

  Volume 13 | Issue 9

  Volume 13 | Issue 8

  Volume 13 | Issue 7

  Volume 13 | Issue 6

  Volume 13 | Issue 5

  Volume 13 | Issue 3

  Volume 13 | Issue 1

  Volume 12 | Issue 12

  Volume 12 | Issue 11

  Volume 12 | Issue 10

  Volume 12 | Issue 9

  Volume 12 | Issue 8

  Volume 12 | Issue 7

  Volume 12 | Issue 6

  Volume 12 | Issue 5

  Volume 12 | Issue 4

  Volume 12 | Issue 3

  Volume 12 | Issue 2

  Volume 12 | Issue 1

  Volume 11 | Issue 12

  Volume 11 | Issue 11

  Volume 11 | Issue 10

  Volume 11 | Issue 8

  Volume 11 | Issue 7

  Volume 11 | Issue 6

  Volume 11 | Issue 3

  Volume 11 | Issue 1

  Volume 10 | Issue 12

  Volume 10 | Issue 8

  Volume 10 | Issue 6

  Volume 10 | Issue 3

  Volume 10 | Issue 2

  Volume 10 | Issue 1

  Volume 9 | Issue 10

  Volume 8 | Issue 11

  Volume 8 | Issue 7

  Volume 7 | Issue 8

  Volume 7 | Issue 7

  Volume 7 | Issue 6

  Volume 7 | Issue 5

  Volume 7 | Issue 4

  Volume 7 | Issue 3

  Volume 7 | Issue 2

  Volume 7 | Issue 1

  Volume 6 | Issue 12

  Volume 6 | Issue 10

  Volume 6 | Issue 9

  Volume 6 | Issue 8

  Volume 6 | Issue 7

  Volume 6 | Issue 6

  Volume 6 | Issue 5

  Volume 6 | Issue 4

  Volume 6 | Issue 3

  Volume 6 | Issue 2

  Volume 6 | Issue 1

  Volume 5 | Issue 12

  Volume 5 | Issue 11

  Volume 5 | Issue 10

  Volume 5 | Issue 9

  Volume 5 | Issue 8

  Volume 5 | Issue 7

  Volume 5 | Issue 6

  Volume 5 | Issue 5

  Volume 5 | Issue 4

  Volume 5 | Issue 3

  Volume 5 | Issue 2

  Volume 5 | Issue 1

  Volume 4 | Issue 12

  Volume 4 | Issue 10

  Volume 4 | Issue 8

  Volume 4 | Issue 7

  Volume 4 | Issue 6

  Volume 4 | Issue 5

  Volume 4 | Issue 4

  Volume 4 | Issue 2

  Volume 4 | Issue 1

  Volume 3 | Issue 10

  Volume 3 | Issue 8

  Volume 3 | Issue 6

  Volume 3 | Issue 5

  Volume 3 | Issue 4

  Volume 3 | Issue 3

  Volume 3 | Issue 2

  Volume 3 | Issue 1

  Volume 2 | Issue 12

  Volume 2 | Issue 11

  Volume 2 | Issue 10

  Volume 2 | Issue 9

  Volume 2 | Issue 8

  Volume 2 | Issue 7

  Volume 2 | Issue 2

  Volume 1 | Issue 9

  Volume 1 | Issue 8

  Volume 1 | Issue 7

  Volume 1 | Issue 6

  Volume 1 | Issue 4

  Volume 1 | Issue 3

  Volume 1 | Issue 2

  Volume 1 | Issue 1

Current Volume 13 | Issue 12

Survey of Stock Price Volatility and Forecasting using Neural Network Technique


Volume:  13 - Issue: 05 - Date: 01-05-2024
Approved ISSN:  2278-1412
Published Id:  IJAECESTU384 |  Page No.: 116-120
Author: Nikita Sharma
Co- Author:  Swati Khanve,Dr .Sneha Soni
Abstract:-In finance, a technique for analyzing securities is known as technical analysis. It looks at previous market facts, primarily cost and amount, to forecast price fluctuations. This strategy makes use of charts as well as a number of procedures for identifying samples that direct further action. Technical analysts use this phenomenon to predict future market outcomes based on previous share and market behavior. However, since technical analysis is subjective, it is possible for our own prejudices to show up in the analysis. Statistical approaches are applied, such as the exponential moving average. By examining the fundamental aspects that take into account a country's wealth, trade, and organizations, fundamental analysis is used to determine the essential value of securities. Fundamental analysts strive to gain a great deal of knowledge in order to appraise securities, which include macro financial factors (similar to the overall financial system and industry situations) and company-specific aspects (similar to financial state and organization). The early stage of the share market was very familiar for average investor. Now the markets are wide enough to invest. There are different markets like bond market, forex market, derivative market and other specialty markets. Analysis of the stock price we take the price. By using the artificial neural network, we develop a model within the neural network, we use a recurrent neural network that remembers each and each information through time.
Key Words:-Neural Network, Stock Market, Price Volatility
Area:-Science & Technology
Download Paper: 
Preview This Article

Unable to display PDF file. Download instead.


Download Paper

Downlaod Paper

No. of Download

000243

Impact Factor

7.4


ijaece

Upcoming Events


Special Issue For Paper


Upcoming Conference


Call For Paper