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A Financial Exchange Using Novel Stock Prediction

S.Srividhya 1 , R.Kayalvizhi 2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 1116-1120, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.11161120

Online published on Mar 31, 2019

Copyright © S.Srividhya, R.Kayalvizhi . 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: S.Srividhya, R.Kayalvizhi, “A Financial Exchange Using Novel Stock Prediction,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.1116-1120, 2019.

MLA Style Citation: S.Srividhya, R.Kayalvizhi "A Financial Exchange Using Novel Stock Prediction." International Journal of Computer Sciences and Engineering 7.3 (2019): 1116-1120.

APA Style Citation: S.Srividhya, R.Kayalvizhi, (2019). A Financial Exchange Using Novel Stock Prediction. International Journal of Computer Sciences and Engineering, 7(3), 1116-1120.

BibTex Style Citation:
@article{_2019,
author = {S.Srividhya, R.Kayalvizhi},
title = {A Financial Exchange Using Novel Stock Prediction},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {1116-1120},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3975},
doi = {https://doi.org/10.26438/ijcse/v7i3.11161120}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.11161120}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3975
TI - A Financial Exchange Using Novel Stock Prediction
T2 - International Journal of Computer Sciences and Engineering
AU - S.Srividhya, R.Kayalvizhi
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 1116-1120
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

This paper clarifies the expectation of a stock utilizing Machine Learning. The specialized and crucial or the time arrangement investigation is utilized by the vast majority of the stockbrokers while making the stock expectations. In this setting this investigation utilizes an AI system called Support Vector Machine to foresee stock costs for the vast and little capitalizations and in the three distinct markets, utilizing costs with both every day and regularly updated frequencies. In the money world stock exchanging is a standout amongst the most imperative exercises. Securities exchange expectation is a demonstration of attempting to decide the future estimation of a stock other money related instrument exchanged on a budgetary trade. In this paper, propose a Machine Learning and novel stock prediction approach that will be prepared from the accessible stocks information and increase insight and after that utilizes the procured learning for an exact forecast. The programming language is utilized to foresee the financial exchange utilizing AI.

Key-Words / Index Term

Support vector machine, Machine Learning, Artificial Intelligence

References

[1] Sykes A. O., "An Introduction to Regression Analysis", The Inaugural Coase Lecture, 1993 [2] Yue Xu S., "Stock Price Forecasting Using Information from Yahoo Finance and Google Trend", UC Berkeley, 2012
[3] Duke, “Stationarity and differencing”, [Online], Available: http://people.duke.edu/~rnau/411diff.htm [Accessed January 2017]
[4] Vapnik V. N., "An Overview of Statistical Learning Theory" IEEE TRANSACTIONS ON NEURAL NETWORKS, 1999.
[5] Kim K. "Financial time series forecasting using support vector machines", Department of Information Systems, Dongguk University 2003.
[6] Panigrahi S. S. and Mantri J. K., "A text based Decision Tree model for stock market forecasting," Green Computing and Internet of Things (ICGCIoT), 2015 International Conference on, Noida, 2015.
[7] G. Iuhasz, M. Tirea and V. Negru, "Neural Network Predictions of Stock Price Fluctuations," Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2012 14th International Symposium on, Timisoara, 2012.
[8] Siripurapu A., "Convolutional Networks for Stock Trading", Stanford University, Department of Computer Science, 2014.
[9] Qiu M. and Song Y. “Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network”, Department of Systems Management, Fukuoka Institute of Technology, Fukuoka, Japan, 2016.