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News Based Trading Framework Using Genetic Programming

B.Sowmiya 1 , V.Geetha 2

Section:Review Paper, Product Type: Journal Paper
Volume-3 , Issue-8 , Page no. 148-152, Aug-2015

Online published on Aug 31, 2015

Copyright © B.Sowmiya , V.Geetha . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: B.Sowmiya , V.Geetha, “News Based Trading Framework Using Genetic Programming,” International Journal of Computer Sciences and Engineering, Vol.3, Issue.8, pp.148-152, 2015.

MLA Style Citation: B.Sowmiya , V.Geetha "News Based Trading Framework Using Genetic Programming." International Journal of Computer Sciences and Engineering 3.8 (2015): 148-152.

APA Style Citation: B.Sowmiya , V.Geetha, (2015). News Based Trading Framework Using Genetic Programming. International Journal of Computer Sciences and Engineering, 3(8), 148-152.

BibTex Style Citation:
@article{_2015,
author = {B.Sowmiya , V.Geetha},
title = {News Based Trading Framework Using Genetic Programming},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2015},
volume = {3},
Issue = {8},
month = {8},
year = {2015},
issn = {2347-2693},
pages = {148-152},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=626},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=626
TI - News Based Trading Framework Using Genetic Programming
T2 - International Journal of Computer Sciences and Engineering
AU - B.Sowmiya , V.Geetha
PY - 2015
DA - 2015/08/31
PB - IJCSE, Indore, INDIA
SP - 148-152
IS - 8
VL - 3
SN - 2347-2693
ER -

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Abstract

The robotized PC programs utilizing data mining and prescient technologies do a fare sum of exchanges in the markets. Information mining is well founded on the hypothesis that the memorable data holds the key memory at that point again foreseeing the future direction. This innovation is composed to help speculators find covered up designs from the memorable data that have probable prescient capacity in their venture decisions. The forecast of stock markets is regarded as a testing assignment of monetary time arrangement prediction. Information investigation is one way of foreseeing in the occasion that future stocks costs will increment at that point again decrease. Five procedures of breaking down stocks were joined to anticipate in the occasion that the day’s shutting cost would increment at that point again decrease. These procedures were Regular Cost (TP), Bollinger Bands, Relative Quality List (RSI), CMI and Moving Normal (MA). This paper discussed different procedures which are able to anticipate with future shutting stock cost will increment at that point again diminish better than level of significance. Also, it investigated different worldwide events and their issues foreseeing on stock markets. It supports numerically and graphically.

Key-Words / Index Term

Information mining, Time arrangement Analysis, Binomial test, Regular Price, Bollinger Bands, Relative Quality List and Moving Average

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