Early warning on stock market bubbles via methods of optimization, clustering and inverse problems

Efsun Kürüm (), Gerhard-Wilhelm Weber () and Cem Iyigun ()
Additional contact information
Efsun Kürüm: Near East University
Gerhard-Wilhelm Weber: METU
Cem Iyigun: METU

Annals of Operations Research, 2018, vol. 260, issue 1, No 14, 293-320

Abstract: Abstract In order to avoid destructive results of financial bubbles which affect the entire economy, it is important to develop an early-warning signalling. By using optimization-supported tools, we introduce a new method for an early-warning signalling which approaches the bubble concept geometrically by determining and evaluating ellipsoids. We generate a volume-based index via minimum-volume covering ellipsoid clustering method, and to visualize these ellipsoids, we utilize Radon transform from the theory of the Inverse Problems. The analyses were conducted for US, Japan and China stock markets. In our study, we observe that when the bubble-burst time approaches, the volumes of the ellipsoids gradually decrease and, correspondingly, the figures obtained by Radon transform become more “brilliant”, i.e., more strongly warning.

Keywords: Optimization; Financial bubbles; Early-warning; Clustering; Radon transform; Ellipsoid (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://link.springer.com/10.1007/s10479-017-2496-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:260:y:2018:i:1:d:10.1007_s10479-017-2496-1

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-017-2496-1

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().