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

Τύπος:	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	Modeling asset allocations and a new portfolio performance score
Εναλλακτικός τίτλος:	Geometric and statistical tools for financial modeling
Συγγραφέας:	[EL] Χαλκής, Απόστολος[EN] Chalkis, Apostolos [EL] Χριστοφόρου, Εμμανουήλ[EN] Christoforou, Emmanouil [EL] Εμίρης Ιωάννης[EN] Emiris, Ioannis [EL] Δαλαμάγκας, Θεόδωρος[EN] Dalamagas, Theodoros
Ημερομηνία:	02/09/2021
Περίληψη:	We discuss and extend a powerful, geometric framework to represent the set of portfolios, which identifes the space of asset allocations with the points lying in a convex polytope. Based on this viewpoint, we survey certain state-of-the-art tools from geometric and statistical computing to handle important and difcult problems in digital fnance. Although our tools are quite general, in this paper, we focus on two specifc questions. The frst concerns crisis detection, which is of prime interest for the public in general and for policy makers in particular because of the signifcant impact that crises have on the economy. Certain features in stock markets lead to this type of anomaly detection: Given the assets’ returns, we describe the relationship between portfolios’ return and volatility by means of a copula, without making any assumption on investors’ strategies. We examine a recent method relying on copulae to construct an appropriate indicator that allows us to automate crisis detection. On real data the indicator detects all past crashes in the cryptocurrency market and from the DJ600-Europe index, from 1990 to 2008, the indicator identifes correctly 4 crises and issues one false positive for which we ofer an explanation. Our second contribution is to introduce an original computational framework to model asset allocation strategies, which is of independent interest for digital fnance and its applications. Our approach addresses the crucial question of evaluating portfolio management, and is relevant the individual managers as well as fnancial institutions. To evaluate portfolio performance, we provide a new portfolio score, based on the aforementioned framework and concepts. In particular, it relies on statistical properties of portfolios, and we show how they can be computed efciently.
Γλώσσα:	Αγγλικά
Σελίδες:	39
DOI:	10.1007/s42521-021-00040-8
EISSN:	2524-6186
Θεματική κατηγορία:	[EL] Υπολογιστές, Υλικό (hardware) και Αρχιτεκτονική[EN] Computer science, Hardware and Architecture
Λέξεις-κλειδιά:	Crises detection; Allocation strategies; Portfolio score; Copula; Clustering; stock market
Κάτοχος πνευματικών δικαιωμάτων:	© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021, corrected publication 2021
Ηλεκτρονική διεύθυνση του τεκμηρίου στον εκδότη:	https://link.springer.com/article/10.1007/s42521-021-00040-8 https://link.springer.com/article/10.1007/s42521-021-00042-6
Ηλεκτρονική διεύθυνση περιοδικού:	https://link.springer.com/journal/42521
Τίτλος πηγής δημοσίευσης:	Digital Finance
Τόμος:	3
Σελίδες τεκμηρίου (στην πηγή):	333–371
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. The original article has been corrected.
Εμφανίζεται στις συλλογές:	Ερευνητικές ομάδες