Modelling in finance is a challenging task: the data often has complex statistical properties
and its inner workings are largely unknown. Deep learning algorithms are making progress in …

With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling
of cryptocurrencies. This paper provides the first GARCH modelling of the seven most …

We analyze statistical properties of the largest cryptocurrencies (determined by market
capitalization), of which Bitcoin is the most prominent example. We characterize their exchange …

We provide an extreme value analysis of the returns of Bitcoin. A particular focus is on the
tail risk characteristics and we will provide an in-depth univariate extreme value analysis. …

Cryptocurrencies became popular with the emergence of Bitcoin and have shown an
unprecedented growth over the last few years. As of November 2016, more than 720 …

Artificial Intelligence (AI) has created the single biggest technology revolution the world has
ever seen. For the finance sector, it provides great opportunities to enhance customer …

In this era of Big Data and the advancement of sophisticated analytical techniques, the
financial industry has the capacity to implement innovative technologies within their systems to …

… Osterrieder, J., 2016. The statistics of bitcoin and cryptocurrencies. Available at SSRN: https:/…
Osterrieder, J., Lorenz, J., 2016. A statistical risk assessment of bitcoin and its extreme tail …

We show the statistical properties of the most important cryptocurrencies, of which Bitcoin is
the most prominent example. We characterize their exchange rates versus the US Dollar by …

… j , the Gower’s distance d i j is calculated as: d i j = w i j = ∑ p = 1 P 1 P × d i j p max ( x ⋅ p )
− min ( x ⋅ p ) , where d i j p = | x i p − x j … j p , 0 if x p is a categorical variable and x i p = x j p . …