With topological data analysis, predicting stock market crashes

IJIIS : International Journal of Informatics and Information Systems

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Field Value
 
Title With topological data analysis, predicting stock market crashes
 
Creator Prabowo, Nugroho Agung
Widyanto, R Arri
Hanafi, Mukhtar
Pujiarto, Bambang
Avizenna, Meidar Hadi
 
Subject TDA, Market Crashes, Stock Detection, Topology
 
Description We are investigating the evolution of four big US stock market indexes' regular returns after the 2000 technology crash and the 2007-2009 financial crisis. Our approach is based on topological data processing (TDA). To identify and measure topological phenomena occurring in multidimensional time series, we use persistence homology. We obtain time-dependent point cloud data sets using a sliding window, which we connect a topological space for. Our research indicates that a new method of econometric analysis is offered by TDA, which complements the traditional statistical tests. The tool may be used to predict early warning signs of market declines that are inevitable.
 
Publisher Bright Publisher
 
Contributor
 
Date 2021-03-01
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://ijiis.org/index.php/IJIIS/article/view/78
10.47738/ijiis.v4i1.78
 
Source International Journal of Informatics and Information Systems; Vol 4, No 1: March 2021; 63-70
2579-7069
10.47738/ijiis.v4i1
 
Language eng
 
Relation http://ijiis.org/index.php/IJIIS/article/view/78/37
 
Rights Copyright (c) 2021 IJIIS: International Journal of Informatics and Information Systems
https://creativecommons.org/licenses/by-sa/4.0
 

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