UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
Call for Paper
Volume 11 | Issue 9 | September 2024

JETIREXPLORE- Search Thousands of research papers



WhatsApp Contact
Click Here

Published in:

Volume 5 Issue 9
September-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

7.95 impact factor calculated by Google scholar

Unique Identifier

Published Paper ID:
JETIRA006335


Registration ID:
189167

Page Number

80-87

Share This Article


Jetir RMS

Title

ARTIFICIAL INTELLIGENCE BASED SYSTEM FOR FINANCIAL DECISION SUPPORT

Abstract

The stock market is a complex, non-stationary and chaotic dynamic system. It is a popular investment platform that appeals to a wide variety of masses. While the stock market remains a significant way to earn profit, it is often considered one of the most risky forms of investment due to the underlying nature of the financial domain and a host of various factors that often elude the attention of naïve investors. The stock market is a hostile environment that demands undivided attention to the events that transpire throughout the day along with a certain consideration to the effects of the past and the implications on the future. Hence, many investors, face (or stand a risk) of failure on a daily basis. Therefore, the need of the hour is a Decision Support System (DSS) that takes into account market trends, financial analysis and strategies to identify the best time to purchase stocks and the actual stocks to purchase. In this paper, we propose development of anArtificial Intelligence based decision support system (DSS) for guiding individual investors to buy and sell stocks. The Financial decision support shall be based on mathematical modeling of the various financial parameters to predict stock prices on a long term basis with a reasonable degree of accuracy and eliminate the behavioral biases of human decisions. This study mainly focuses on the using two Machine Learning Models namely Linear Regression and Artificial Neural Networks (ANNs), we found that the ANNs have better accuracy due to ability to generate non-linear outputs; they can be deployed for deep learning through multiple hidden layers and can solve complex financial regression problems. AI / Machine learning neural networks can revolutionize virtually every aspect of financial and investment decision making. Financial firms worldwide can employ neural networks to tackle difficult tasks involving intuitive judgement or requiring the detection of data patterns which elude conventional analytic techniques.

Key Words

Decision Support Systems (DSS), Stock Markets, Artificial Intelligence (AI), Machine Learning (ML), Mathematical Modeling (MM)

Cite This Article

"ARTIFICIAL INTELLIGENCE BASED SYSTEM FOR FINANCIAL DECISION SUPPORT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.80-87, September-2018, Available :http://www.jetir.org/papers/JETIRA006335.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"ARTIFICIAL INTELLIGENCE BASED SYSTEM FOR FINANCIAL DECISION SUPPORT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp80-87, September-2018, Available at : http://www.jetir.org/papers/JETIRA006335.pdf

Publication Details

Published Paper ID: JETIRA006335
Registration ID: 189167
Published In: Volume 5 | Issue 9 | Year September-2018
DOI (Digital Object Identifier):
Page No: 80-87
Country: --, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


Preview This Article


Downlaod

Click here for Article Preview

Download PDF

Downloads

0003017

Print This Page

Current Call For Paper

Jetir RMS