Crypto price discovery through correlation networks

We aim to understand the dynamics of crypto asset prices and, specifically, how price information is transmitted among different bitcoin market exchanges, and between bitcoin markets and traditional ones. To this aim, we hierarchically cluster bitcoin prices from different exchanges, as well as clas...

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Veröffentlicht in:Annals of operations research Jg. 299; H. 1-2; S. 443 - 457
Hauptverfasser: Giudici, Paolo, Polinesi, Gloria
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.04.2021
Springer
Springer Nature B.V
Schlagworte:
Autocorrelation (Statistics)
Business and Management
Combinatorics
Crypto-currencies
Digital currencies
Economic models
Exchanging
Forecasts and trends
Graph theory
Operations research
Operations Research/Decision Theory
Prices
Prices and rates
Pricing
S.I.: Recent Developments in Financial Modeling and Risk Management
Securities
Theory of Computation
Italy
Correlation networks
Random matrix theory
Minimum spanning trees
Bitcoin exchanges
Bitcoin price discovery
ISSN:0254-5330, 1572-9338
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Beschreibung
Zusammenfassung:We aim to understand the dynamics of crypto asset prices and, specifically, how price information is transmitted among different bitcoin market exchanges, and between bitcoin markets and traditional ones. To this aim, we hierarchically cluster bitcoin prices from different exchanges, as well as classic assets, by enriching the correlation based minimum spanning tree method with a preliminary filtering method based on the random matrix approach. Our main empirical findings are that: (i) bitcoin exchange prices are positively related with each other and, among them, the largest exchanges, such as Bitstamp, drive the prices; (ii) bitcoin exchange prices are not affected by classic asset prices, but their volatilities are, with a negative and lagged effect.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0254-5330
1572-9338
DOI:10.1007/s10479-019-03282-3