File Download

There are no files associated with this item.

  • Find it @ UNIST can give you direct access to the published full text of this article. (UNISTARs only)
Related Researcher

서병기

Seo, Byoung Ki
Trading Engineering Lab.
Read More

Views & Downloads

Detailed Information

Cited time in webofscience Cited time in scopus
Metadata Downloads

Full metadata record

DC Field Value Language
dc.citation.conferencePlace AT -
dc.citation.conferencePlace 호주 시드니 -
dc.citation.title Quantitative Methods in Finance Conference 2019 -
dc.contributor.author Jang, Hyeonung -
dc.contributor.author Jho, Yongseok -
dc.contributor.author Seo, Byoung Ki -
dc.date.accessioned 2024-01-31T23:08:34Z -
dc.date.available 2024-01-31T23:08:34Z -
dc.date.created 2020-01-13 -
dc.date.issued 2019-12-18 -
dc.description.abstract Recent studies have attempted to understand market crash using the concept of phase transition in statistical physics. This study finds certain behavior in the financial market such as the critical phenomena that occur during phase transition. We apply model-free framework using convolutional neural network methods instead of the complex mathematical models studied previously. The results show that the financial market crash has a similar behavior to the phase transition of particles. Furthermore, we find that the
similar behavior between financial market crash and phase transition gives better understanding on the market crash and detecting it.
-
dc.identifier.bibliographicCitation Quantitative Methods in Finance Conference 2019 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/78653 -
dc.language 영어 -
dc.publisher University of Techchology Sydney -
dc.title Financial Market Crash and Phase Transition: Through Model-Free Framework with Machine Learning -
dc.type Conference Paper -
dc.date.conferenceDate 2019-12-17 -

qrcode

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.