Physica A 559 (2020) 125077 Contents lists available at ScienceDirect Physica A journal homepage: www.elsevier.com/locate/physa Dynamic interdependence of cryptocurrency markets: An analysis across time and frequency Saba Qureshi a , Muhammad Aftab b , Elie Bouri c ,∗ , Tareq Saeed d a Institute of Business Administration, University of Sindh, Pakistan b Department of Management Sciences, COMSATS University Islamabad, Pakistan c USEK Business School, Holy Spirit University of Kaslik, Jounieh, POBOX 446, Lebanon d Nonlinear Analysis and Applied Mathematics (NAAM)-Research Group, Department of Mathematics, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia article info Article history: Received 7 April 2020 Received in revised form 9 August 2020 Available online 19 August 2020 Keywords: Cryptocurrencies Wavelet analysis Interdependencies Market integration Contagion abstract The extreme price swings and complexity in cryptocurrency markets drives multifarious research into co-movements, in both time and frequency, among cryptocurrencies. In this paper, we investigate the dynamics of multiscale interdependencies among five leading and liquid cryptocurrencies (Bitcoin, Ethereum, Ripple, Litecoin, and Bitcoin Cash) using wavelet-based analyses that account for the heterogeneous behaviour of crypto-traders and crypto-investors. The results provide evidence of high levels of dependency from 2016 to 2018 at daily frequency scales. The cross wavelet transforms demonstrate Ripple and Ethereum to be trivial origins of market contagion. The results of wavelet coherence confirm the short-run and long-run market integration among some cryptocurrency pairs. However, the coherence is found to fluctuate at higher frequencies and be significantly stable at lower frequencies. Furthermore, the switch in the lead and lag relations of cryptocurrency returns suggests alternating time and frequency interdependencies. Our findings are useful to scale-conscious traders and multi-prospect (various investment horizon) investors and portfolio managers. © 2020 Elsevier B.V. All rights reserved. 1. Introduction Cryptocurrencies have emerged as a new global investment asset [1–4] and an alternative to the traditional monetary system. 1 They have attracted much attention owing to their unique characteristics such as decentralization, blockchain technology, and scarcity. Cryptocurrencies offer very high returns 2 that eclipse the returns of assets such as stocks or commodities, and therefore investors consider them as part of investment strategies, such as buy-and-hold [7] or for hedging purposes [2,8], because of their decentralization and detachment from conventional assets. However, cryptocurrencies exhibit high volatility 3 and are often associated with speculative bubbles, potential financial instability, and contagion risk [9,10]. ∗ Corresponding author. E-mail addresses: qureshisaba1990@gmail.com (S. Qureshi), maftab@comsats.edu.pk (M. Aftab), eliebouri@usek.edu.lb (E. Bouri), tsalmalki@kau.edu.sa (T. Saeed). 1 However, Stosic et al. [5] argue that cryptocurrency markets exhibit a certain similarity to stock markets with some differences from traditional currencies. 2 As of December 2019, the size of the cryptocurreny market reached $200bn compared to less than $18bn at the start of 2017. For example, the Bitcoin price jumped by 1358% in the year 2017 [6]. 3 There is long memory and persistence in the volatility of Bitcoin [7]. https://doi.org/10.1016/j.physa.2020.125077 0378-4371/© 2020 Elsevier B.V. All rights reserved.