**1. Introduction**

Cryptocurrencies are digital currencies which can be used for direct retail purchases but also as financial assets in general. They are characterized by some features that make them di fferent from other assets, namely the facts that they are not subject to any centralized institutional authority and that they do not have physical representation. Another important feature, which makes this kind of currency somewhat controversial, is the fact that they are not associated with any tangible assets (Corbet et al. 2019).

Since the creation of Bitcoin in 2009, which was the first cryptocurrency, this particular market has increased its value exponentially, reaching about 260 billion USD of capitalization in May 2019. Bitcoin itself was responsible for about 55% of that capitalization, being by far the most important cryptocurrency. This evolution makes cryptocurrencies very interesting for investors, as well as for researchers, with a growing body of literature on several issues (Urquhart 2018; Corbet et al. 2019). These studies include topics more linked with financial issues like e fficiency or the relationship with other assets (which is addressed in the next section), in addition to analysis issues like regulation or even linkages with possibly illicit activities (see, respectively, the works of Cha ffee (2018) and Campbell-Verduyn (2018) as examples on each of those topics).

Despite the evolution of cryptocurrencies' prices, during 2017 this market experienced a kind of bubble, with prices reaching maximum levels on 15 December 2017, followed by a sharp decrease. With such an episode, and considering Bitcoin as the most relevant cryptocurrency, we can evaluate the possibility of a contagion e ffect in this market. According to Forbes and Rigobon (2002), there is a certain pre-existing integration between assets and, after a given episode of instability, this relationship is intensified, i.e., correlations between those assets increase.

Based on the Detrended Cross-Correlation Analysis correlation coefficient (ρDCCA), we calculated this correlation both before and after that episode. Furthermore, we estimated the ΔρDCCA, which could be considered a measure of contagion. Although the literature on cryptocurrencies is growing rapidly, our paper extends the existing literature by focusing on a specific event, showing the importance of not only that event but also the role of Bitcoin in this particular market. Moreover, the employed methodology allowed us to conduct an analysis of contagion considering different time scales, which could be interesting because short-run impacts (lower time scales) could be different from long-run ones (higher time scales).

Our main results show the existence of a contagion effect between Bitcoin and the other cryptocurrencies studied, excepting Tether, which indicates a more interconnected market now than in the past. The remainder of the work is organized as follows: Section 2 presents a literature review on work involving cryptocurrencies; Section 3 describes the methodology and data; Section 4 presents the results; Section 5 concludes the paper.
