UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 9 Issue 6
June-2022
eISSN: 2349-5162

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

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Published Paper ID:
JETIRFM06025


Registration ID:
403738

Page Number

133-137

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Title

PREDICTION OF TSUNAMIS USING MACHINE LEARNING ALGORITHMS: A SURVEY PAPER

Abstract

This study has been undertaken to investigate the determinants of stock returns in Karachi Stock Exchange (KSE) using two assets pricing models the classical Capital Asset Pricing Model and Arbitrage Pricing Theory model. To test the CAPM market return is used and macroeconomic variables are used to test the APT. The macroeconomic variables include inflation, oil prices, interest rate and exchange rate. For the very purpose monthly time series data has been arranged from Jan 2010 to Dec 2014. The analytical framework contains.

Key Words

Component,formatting,style,styling,insert.

Cite This Article

"PREDICTION OF TSUNAMIS USING MACHINE LEARNING ALGORITHMS: A SURVEY PAPER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.133-137, June-2022, Available :http://www.jetir.org/papers/JETIRFM06025.pdf

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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

"PREDICTION OF TSUNAMIS USING MACHINE LEARNING ALGORITHMS: A SURVEY PAPER", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. pp133-137, June-2022, Available at : http://www.jetir.org/papers/JETIRFM06025.pdf

Publication Details

Published Paper ID: JETIRFM06025
Registration ID: 403738
Published In: Volume 9 | Issue 6 | Year June-2022
DOI (Digital Object Identifier):
Page No: 133-137
Country: -, -, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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