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Predicting Financial Extremes Based on Weighted Visual Graph of Major Stock Indices
Joint Authors
Chen, Dong-Rui
Zhang, Yi-Cheng
Liu, Chuang
Zhang, Zi-Ke
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-10-31
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Understanding and predicting extreme turning points in the financial market, such as financial bubbles and crashes, has attracted much attention in recent years.
Experimental observations of the superexponential increase of prices before crashes indicate the predictability of financial extremes.
In this study, we aim to forecast extreme events in the stock market using 19-year time-series data (January 2000–December 2018) of the financial market, covering 12 kinds of worldwide stock indices.
In addition, we propose an extremes indicator through the network, which is constructed from the price time series using a weighted visual graph algorithm.
Experimental results on 12 stock indices show that the proposed indicators can predict financial extremes very well.
American Psychological Association (APA)
Chen, Dong-Rui& Liu, Chuang& Zhang, Yi-Cheng& Zhang, Zi-Ke. 2019. Predicting Financial Extremes Based on Weighted Visual Graph of Major Stock Indices. Complexity،Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1132078
Modern Language Association (MLA)
Chen, Dong-Rui…[et al.]. Predicting Financial Extremes Based on Weighted Visual Graph of Major Stock Indices. Complexity No. 2019 (2019), pp.1-17.
https://search.emarefa.net/detail/BIM-1132078
American Medical Association (AMA)
Chen, Dong-Rui& Liu, Chuang& Zhang, Yi-Cheng& Zhang, Zi-Ke. Predicting Financial Extremes Based on Weighted Visual Graph of Major Stock Indices. Complexity. 2019. Vol. 2019, no. 2019, pp.1-17.
https://search.emarefa.net/detail/BIM-1132078
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1132078