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Magic of Fibonacci Sequence in Prediction of Stock Behavior

by Rajesh Kumar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 93 - Number 11
Year of Publication: 2014
Authors: Rajesh Kumar
10.5120/16262-5926

Rajesh Kumar . Magic of Fibonacci Sequence in Prediction of Stock Behavior. International Journal of Computer Applications. 93, 11 ( May 2014), 36-40. DOI=10.5120/16262-5926

@article{ 10.5120/16262-5926,
author = { Rajesh Kumar },
title = { Magic of Fibonacci Sequence in Prediction of Stock Behavior },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 93 },
number = { 11 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 36-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume93/number11/16262-5926/ },
doi = { 10.5120/16262-5926 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:14:36.840392+05:30
%A Rajesh Kumar
%T Magic of Fibonacci Sequence in Prediction of Stock Behavior
%J International Journal of Computer Applications
%@ 0975-8887
%V 93
%N 11
%P 36-40
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Predicting the return of a financial product is a very risky task. It involves subjectivity and experts knowledge. In the development of an expert system, domain knowledge is one of the important component. For a software to be artificial intelligent, some heuristics are required, which can help in decision making. It is admitted by the technical experts of financial sectors that in predicting the support or resistance backtracking is required when prediction of support or resistance fails. In this paper ,an attempt has been made to restrict the back tracking of support and resistance to a maximum of two attempts. Proposed model can be further used in machine learning to remove the subjectivity.

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Index Terms

Computer Science
Information Sciences

Keywords

Fibonacci sequence Factor analysis principal component analysis RSI MFI.

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