Short term stock prediction using SOM

In this paper, we propose a stock movement prediction model using self organization map. The correlation is adapted to select inputs from technical indexes. The self-organization map is utilized to make decision of stock selling or buying. The proposed model is tested on the Microsoft and General El...

Full description

Saved in:

Bibliographic Details
Main Authors:	Prompong Sugunsil, Samerkae Somhom
Format:	Book Series
Published:	2018
Subjects:	Business, Management and Accounting Computer Science Decision Sciences Engineering Mathematics
Online Access:	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=65349093947&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/59424
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Chiang Mai University

id	th-cmuir.6653943832-59424
record_format	dspace
spelling	th-cmuir.6653943832-594242018-09-10T03:21:00Z Short term stock prediction using SOM Prompong Sugunsil Samerkae Somhom Business, Management and Accounting Computer Science Decision Sciences Engineering Mathematics In this paper, we propose a stock movement prediction model using self organization map. The correlation is adapted to select inputs from technical indexes. The self-organization map is utilized to make decision of stock selling or buying. The proposed model is tested on the Microsoft and General Electric. Through the experimental test, the method has correctly predicted the movement of stock with close to 90% accuracy in trainnig dataset and 75% accuracy in datatest. The results can be further improved for higher accuracy. © 2009 Springer Berlin Heidelberg. 2018-09-10T03:15:01Z 2018-09-10T03:15:01Z 2009-01-01 Book Series 18651348 2-s2.0-65349093947 10.1007/978-3-642-01112-2_27 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=65349093947&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/59424
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
topic	Business, Management and Accounting Computer Science Decision Sciences Engineering Mathematics
spellingShingle	Business, Management and Accounting Computer Science Decision Sciences Engineering Mathematics Prompong Sugunsil Samerkae Somhom Short term stock prediction using SOM
description	In this paper, we propose a stock movement prediction model using self organization map. The correlation is adapted to select inputs from technical indexes. The self-organization map is utilized to make decision of stock selling or buying. The proposed model is tested on the Microsoft and General Electric. Through the experimental test, the method has correctly predicted the movement of stock with close to 90% accuracy in trainnig dataset and 75% accuracy in datatest. The results can be further improved for higher accuracy. © 2009 Springer Berlin Heidelberg.
format	Book Series
author	Prompong Sugunsil Samerkae Somhom
author_facet	Prompong Sugunsil Samerkae Somhom
author_sort	Prompong Sugunsil
title	Short term stock prediction using SOM
title_short	Short term stock prediction using SOM
title_full	Short term stock prediction using SOM
title_fullStr	Short term stock prediction using SOM
title_full_unstemmed	Short term stock prediction using SOM
title_sort	short term stock prediction using som
publishDate	2018
url	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=65349093947&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/59424
_version_	1681425248766918656

Short term stock prediction using SOM

Similar Items