Utilizing the empirical data of ten major cryptocurrencies, this article examines the investablitiy and role of diversification in cryptocurrency market, and evaluates the out-of-sample performance of commonly used asset allocation models across cryptocurrencies. We show that portfolio diversification across different cryptocurrencies can significantly improve the investment results. We also find robust evidence that the maximum utility model dominates the out-of-sample utility, although none of the models can consistently beat the naïve 1/N portfolio in Sharpe ratio.

Introduction

As the sharp increase in the trading volume of Bitcoin recently, the cryptocurrency market has drawn explosive attention from the media, financial industry and government institutions. Bitcoin is the first and largest decentralized cryptocurrency built upon blockchain technology, and has accumulated sufficient data of prices for empirical analyses. Therefore, quite a lot of academic research has been conducted on Bitcoin, such as market efficiency (Urquhart, 2016; Nadarajah and Chu, 2017; Bariviera, 2017; Vidal-Tomás and Ibañez, 2018), price volatility (Dyhrberg, 2016; Katsiampa, 2017), price clustering (Urquhart, 2017), and transaction cost (Kim, 2017). On the other hand, different kinds of cryptocurrencies rise immensely in the last couple of years, resulting in rapid expansion of market dimensions. As of April 2018, the number of cryptocurrencies has exceeded 1,500, with more than 500 having a market capitalization over 10 million dollars. Thus, the research on cryptocurrencies beyond Bitcoin has received considerable impetus in recent literatures. There are debates on the cryptocurrencies that they are mainly regarded as a new class of assets rather than traditional currencies (Glaser et al., 2014; Baek and Elbeck, 2015). Several important stylized facts of cryptocurrencies found recently are common in financial assets, such as leptokurtosis (Chan et al., 2017), heteroscedasticity (Gkillas and Katsiampa, 2018) and long-memory (Phillip et al., 2018). Moreover, researches on cryptocurrencies further demonstrate potential possibility of diversification in this emerging market for institutional and retail investors. First, a sufficient amount of cryptocurrencies have large market capitalization at million or billion level, while they usually provide lower transaction costs to individuals than one of the most efficient financial markets (Kim, 2017), which indicates ample liquidity. Second, there are cryptocurrencies that the dynamics are relatively isolated to the others (Corbet et al., 2018), which may offer diversification benefits from investors. Third, the variety of cryptocurrencies is still increasing, and therefore the cryptocurrency market has a growing place in diversification and portfolio management. However, despite the huge growth of the cryptocurrency market, research on the portfolio diversification of cryptocurrencies is rather limited. In this paper, we analyze the investability and role of diversification in the cryptocurrency market with applying six classical portfolilio selection models through an out-of-sample evaluation method. The out-of-sample method means the parameters involved in the models are estimated via a “rolling window” at each rebalancing date instead of using the entire sample (the in-sample method, which cannot reflect the real investment decisions). We compare the out-of-sample performance of different models using various evaluation criteria to understand which model performs the best in one or more specific aspects. We also analyze the portfolio performance by setting different transaction costs, rebalancing periods, as well as the risk aversion parameters, such that the results are robust and instructive for real investment.