Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
arXiv.org e-Print Archive
Other literature type . Preprint . 2021
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
http://arxiv.org/pdf/2103.1329...
Part of book or chapter of book
Data sources: UnpayWall
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2021 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
https://doi.org/10.48550/arxiv...
Article . 2021
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
versions View all 7 versions

Modeling of Crisis Periods in Stock Markets

Authors: Chalkis, Apostolos; Christoforou, Emmanouil; Dalamagkas, Theodore; Emiris, Ioannis Z.;

Modeling of Crisis Periods in Stock Markets

Abstract

We exploit a recent computational framework to model and detect financial crises in stock markets, as well as shock events in cryptocurrency markets, which are characterized by a sudden or severe drop in prices. Our method manages to detect all past crises in the French industrial stock market starting with the crash of 1929, including financial crises after 1990 (e.g. dot-com bubble burst of 2000, stock market downturn of 2002), and all past crashes in the cryptocurrency market, namely in 2018, and also in 2020 due to covid-19. We leverage copulae clustering, based on the distance between probability distributions, in order to validate the reliability of the framework; we show that clusters contain copulae from similar market states such as normal states, or crises. Moreover, we propose a novel regression model that can detect successfully all past events using less than 10% of the information that the previous framework requires. We train our model by historical data on the industry assets, and we are able to detect all past shock events in the cryptocurrency market. Our tools provide the essential components of our software framework that offers fast and reliable detection, or even prediction, of shock events in stock and cryptocurrency markets of hundreds of assets.

11 pages, 10 figures, 1 table

Country
France
Keywords

Computational Geometry (cs.CG), FOS: Computer and information sciences, Statistical Finance (q-fin.ST), Stock market, I.0, [INFO.INFO-CE]Computer Science [cs]/Computational Engineering, Finance, and Science [cs.CE], G.3, Financial portfolio, Quantitative Finance - Statistical Finance, Crisis detection, [INFO.INFO-CG]Computer Science [cs]/Computational Geometry [cs.CG], Investment risk, Clustering, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Economics and business, 62-08, 51.08, Copula, Computer Science - Computational Geometry, G.3; I.0, Bitcoin

11 references, page 1 of 2

[1] M. Billio, M. Getmansky, and L. Pelizzon. Dynamic risk exposures in hedge funds. Comput. Stat. & Data Analysis, 56(11):3517{3532, 2012.

[2] Mary Ann Branch, Thomas F. Coleman, and Yuying Li. A subspace, interior, and conjugate gradient method for large-scale bound-constrained minimization problems. SIAM J. Scienti c Computing, 21(1):1{23, 1999.

[3] L. Cales, A. Chalkis, I. Z. Emiris, and V. Fisikopoulos. Practical volume computation of structured convex bodies, and an application to modeling portfolio dependencies and nancial crises. In B. Speckmann and C.D. Toth, editors, Proc. Intern. Symp. Computational Geometry (SoCG), volume 99 of Leibniz Intern. Proc. Informatics, pages 19:1{15, Dagstuhl, Germany, 2018. [OpenAIRE]

[4] M. Lo Duca, A. Koban, M. Basten, E. Bengtsson, B. Klaus, P. Kusmierczyk, J.H. Lang, C. Detken, and T. Peltonen. A new database for nancial crises in European countries. Technical Report 13, Europ. Central Bank & Europ. Systemic Risk Board, Frankfurt, Germany, 2017.

[5] David Le Bris. Wars, in ation and stock market returns in france, 1870{1945. Financial History Review, 19(3):337{361, 2012.

[6] H. Markowitz. Portfolio selection. J. Finance, 7(1):77{91, 1952.

[7] Andrew Y. Ng, Michael I. Jordan, and Yair Weiss. On spectral clustering: Analysis and an algorithm. In Proc. 14th Intern. Conf. Neural Information Processing Systems: Natural and Synthetic, NIPS'01, pages 849{856, Cambridge, MA, USA, 2001. MIT Press.

[8] Kim Oosterlinck. French stock exchanges and regulation during world war II. Financial History Review, 17(2):211{237, 2010.

[9] O r Pele and Michael Werman. Fast and robust earth mover's distances. In IEEE 12th Intern. Conf. Computer Vision, pages 460{467. IEEE, Sep. 2009.

[10] R.Y. Rubinstein and B. Melamed. Modern simulation and modeling. Wiley, New York, 1998.

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    Powered byBIP!BIP!
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
Related to Research communities
Corona Virus Disease