1. Αποθετήριο Παραδοτέων Υποτρόφων Δράσεων ΕΣΠΑ Τριτοβάθμιας Εκπαίδευσης 2017-2023
2. Όλο το Αποθετήριο
3. Ερευνητικές ομάδες

Τύπος:	Ανακοίνωση σε συνέδριο; Πρακτικά συνεδρίου
Τίτλος:	Modeling of crisis periods in stock markets
Συγγραφέας:	[EL] Χαλκής, Απόστολος[EN] Chalkis, Apostolos [EL] Χριστοφόρου, Εμμανουήλ[EN] Christoforou, Emmanouil [EL] Δαλαμάγκας, Θεόδωρος[EN] Dalamagas, Theodoros [EL] Εμίρης Ιωάννης[EN] Emiris, Ioannis
Ημερομηνία:	09/12/2021
Περίληψη:	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.
Γλώσσα:	Αγγλικά
Σελίδες:	11
DOI:	10.1007/978-3-030-92121-7_5
ISBN:	978-3-030-92121-7
Θεματική κατηγορία:	[EL] Υπολογιστές, Υλικό (hardware) και Αρχιτεκτονική[EN] Computer science, Hardware and Architecture
Λέξεις-κλειδιά:	copula; crisis detection; stock market; clustering; financial portfolio; Bitcoin; investment risk
Κάτοχος πνευματικών δικαιωμάτων:	© 2021 Springer Nature Switzerland AG
Ηλεκτρονική διεύθυνση του τεκμηρίου στον εκδότη:	https://link.springer.com/chapter/10.1007/978-3-030-92121-7_5
Ηλεκτρονική διεύθυνση περιοδικού:	https://link.springer.com/book/10.1007/978-3-030-92121-7
Τίτλος πηγής δημοσίευσης:	15th International Conference, LION 15 Conference proceedings
Σελίδες τεκμηρίου (στην πηγή):	55–65
Σειρά δημοσίευσης:	Lecture Notes in Computer Science (LNTCS,volume 12931)
Όνομα εκδήλωσης:	Learning and Intelligent Optimization 15th International Conference, LION 15
Τοποθεσία εκδήλωσης:	Athens, Greece
Ημ/νία έναρξης εκδήλωσης:	20/06/2021
Ημ/νία λήξης εκδήλωσης:	25/06/2021
Σημειώσεις:	This research is carried out in the context of the project “PeGASUS: Approximate geometric algorithms and clustering with applications in finance” (MIS 5047662) under call “Support for researchers with emphasis on young researchers: cycle B” (EDBM103). The project is co-financed by Greece and the European Union (European Social Fund-ESF) by the Operational Programme Human Resources Development, Education and Lifelong Learning 2014-2020.
Εμφανίζεται στις συλλογές:	Ερευνητικές ομάδες