Geodesic
Tail and memory behaviour of the cryptocurrency prices and stock market indices
Mathematica Applicanda, Tome 52 (2024) no. 1, pp. 85-117.

Voir la notice de l'article provenant de la source Annales Societatis Mathematicae Polonae Series

Cryptocurrency markets are characterised by high volatility, high returns and immaturity relative to equity markets. In this paper, we aim to gain insight into the statistical differences between the markets. To this end, we analyse Bitcoin (BTC) and Ethereum (ETH) prices, Dow Jones Industrial Average (DJIA) index and Hang Seng Index (HSI). We concentrate here on the comparison of two important characteristics of the data, namely the distribution and memory. We find that the normal inverse distribution can stand for a universal distribution, double Weibull is very well fitted to BTC and ETH, and Student's t to BTC and HSI. Memory analysis performed with the use of various statistics indicates that the log-returns of DJIA show the strongest dependence (but not the long memory). Moreover, analysis of the heteroskedatic effect shows that the implied volatility of HSI can be very well described by the generalised autoregressive conditional heteroskedasticy (GARCH) model. We note that the procedure for testing the tail and memory behaviour introduced here can be applied to other datasets. 
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Julia Kończal; Michał Wronka. Tail and memory behaviour of the cryptocurrency prices and stock market indices. Mathematica Applicanda, Tome 52 (2024) no. 1, pp.  85-117. doi : 10.14708/ma.v52i1.7305. http://geodesic.mathdoc.fr/articles/10.14708/ma.v52i1.7305/

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