Forex exchange using big data analytics. Issue 4 (July 2021)
- Record Type:
- Journal Article
- Title:
- Forex exchange using big data analytics. Issue 4 (July 2021)
- Main Title:
- Forex exchange using big data analytics
- Authors:
- Sadhasivam, Jayakumar
Arun, M.
Deepa, R
Muthukumaran, V
Lokesh Kumar, R
Prasanna Kumar, R B - Abstract:
- Abstract: Analysis and Prediction of forex has gained immense value in today's economy. The stock price prediction is a difficult process owing to the irregularities in stock prices. Every trader wants to know if the pattern has been repeated in past to know what the possible output of the current situation will be. The primary objective is to propose a methodology that will use a historical dataset and provide a more accurate prediction on stock price. In this paper, we will be using machine learning pattern recognition algorithm on forex tick dataset. The learned model then will produce pattern from the given dataset and on the pattern of increasing or decreasing, the buyer will initiate a buy or sell the stock respectively. We will use python coding to execute the algorithm in jupyter notebook. Matplot library will help us to perform graphing in the process and Numpy will be helpful in doing statistical analysis of data.
- Is Part Of:
- Journal of physics. Volume 1964:Issue 4(2021)
- Journal:
- Journal of physics
- Issue:
- Volume 1964:Issue 4(2021)
- Issue Display:
- Volume 1964, Issue 4 (2021)
- Year:
- 2021
- Volume:
- 1964
- Issue:
- 4
- Issue Sort Value:
- 2021-1964-0004-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-07
- Subjects:
- Physics -- Congresses
530.5 - Journal URLs:
- http://www.iop.org/EJ/journal/1742-6596 ↗
http://ioppublishing.org/ ↗ - DOI:
- 10.1088/1742-6596/1964/4/042060 ↗
- Languages:
- English
- ISSNs:
- 1742-6588
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5036.223000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17622.xml