Estimating Prediction Accuracy of Stock Price Using Artificial Neural Network

H. L. Gururaj*, Hong Lin, B. R. Sunil Kumar, M. N. Manu, V. Ravi Kumar

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Presently, all over the world, an enormous amount of investment is being made to the Stock Markets. Nationwide economic systems are sturdily associated and closely inclined to the achievement of their Stock Markets. Additionally, nowadays, trading has become too reachable capital expenditure medium, for both planned investors as well as common man also. Artificial Neural Networks (ANN), which is a subset of Artificial Intelligence (AI), is a way that is anticipated to select out samples (styles) and gain an information model. Significant dispositions of ANN are its capability for precise troubles with step by step analyzing and input-output mapping. The neural network is a superior big approach to categorize anonymous, unnoticed samples in input values that is suitable to be looking for the inventory market. Feed forward neural networks with back propagation schooling algorithms were taken via way of the use of way humans to make predictions.

Original languageEnglish
Title of host publication2022 12th International Workshop on Computer Science and Engineering, WCSE 2022
PublisherInternational Workshop on Computer Science and Engineering (WCSE)
Pages176-185
Number of pages10
ISBN (Electronic)9789811839597
DOIs
Publication statusPublished - 2022
Event2022 12th International Workshop on Computer Science and Engineering, WCSE 2022 - Xiamen, China
Duration: 24-06-202227-06-2022

Publication series

Name2022 12th International Workshop on Computer Science and Engineering, WCSE 2022

Conference

Conference2022 12th International Workshop on Computer Science and Engineering, WCSE 2022
Country/TerritoryChina
CityXiamen
Period24-06-2227-06-22

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications
  • Computer Science Applications

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