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A0275
Title: Conditional tail dependence in major cryptocurrency markets Authors:  Pierangelo De Pace - Pomona College (United States) [presenting]
Jayant Rao - Claremont Graduate University (United States)
Abstract: A daily dataset of five major cryptocurrencies is used to empirically examine the conditional tail dependence of their price returns between April 2013 and March 2020. We do so by adopting a time-varying conditional copula modelling approach. The results are heterogeneous. We show that time variation in the tail dependence is generally pronounced in all pairs of cryptocurrencies. With some exceptions, tail dependences are usually low until mid-2018 and become very large in approximately the last two years of the sample.