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Are cryptocurrencies priced in the cross-section? A portfolio approach

15 April 2020

The article at a glance

Most papers, that study determinants of cryptocurrency prices, find no relation to existing market factors. In a work-in-progress, CCFin/CERF Research Associate Adelphe …

Adelphe Ekponon
Dr Adelphe Ekponon

Most papers, that study determinants of cryptocurrency prices, find no relation to existing market factors. In a work-in-progress, CCFin/CERF Research Associate Adelphe Ekponon and Kassi Assamoi (Liquidity Analyst at MUFG Securities and University of Warwick) examine a portfolio approach to explore cross-sectional pricing within crypto-market. At its inception, Bitcoin meant to be an alternative to fiat currencies. Yet high returns in this market may have also attracted usual investors as well, as they are looking for more investments and diversification venue. Since Bitcoin, the number of cryptocurrencies has reached more than 6,000 as of the beginning of 2020, according to coingecko.com. Hence, investors have more choices when they decide to enter into the crypto-market. So, they have an incentive to understand the crypto-market interaction with their current investment.

Their paper belongs to two trends. The first one explores portfolio strategies and cross-sectional pricing to study factors embedded into major asset classes, stocks or/and bonds as in Fama-French (1989, 1992), Cochrane and Piazzesi (2008), and Koijen, Lustig, and Van Nieuwerburgh (2017); currencies as in Lustig and Verdelhan (2005); and commodity as in Fama-French (1987), and Bakshi, Gao, and Rossi (2015). The second line examines the determinants of cryptocurrency prices and returns. See, among others, Canh et al (2019), Liu and Tsyvinski (2018), Balcilar et al (2017), Bouri et al (2016), and Yermack (2015). They find that cryptocurrencies have no exposure to most market and macroeconomic factors or currency and commodity markets.

In closely related papers, Adam Hayes (2014) uses data from 66 of the most active cryptocurrencies and notes that three of the main drivers come from the blockchain technology. Bouri et al (2016) explore, in time-series analysis, the ability of Bitcoin to hedge against risk embedded within leading stock markets, bonds, oil, gold, the commodity index, and the US dollar index. They conclude that Bitcoin’s ability to hedge is weak but is suitable for diversification purposes. Moreover, its hedging and safe-haven properties depend on the horizon.

In their study, Ekponon and co-author examine 10 factors from equity, currency, and commodity markets. The study uses 95+ cryptocurrencies daily quotes, from 17 July 2010 to 9 September 2019. They determine cryptocurrencies’ exposure (beta) to these factors and perform cross-sectional regressions of cryptos average returns on exposures. They alternatively build portfolios sorted on exposures to each factor. Their findings confirm most of the previous results and produce some novel insight. Two out of the 10 factors, size and commodity index, have a negative and highly significant correlation with the cross-section of cryptocurrency returns. Long-short strategies do not deliver significant returns for all 10 factors. Yet they might provide excellent investment opportunities for commodities portfolios and in size factor. For example, buy/sell cryptos with negative/positive correlation to diversify a commodity portfolio or investments in blue-chip stocks. As the crypto-market is uncorrelated to market volatility (VIX), these strategies would likely be accurate in any state of the economy. Finally, these results support the market participants’ view that cryptocurrencies are still too volatile to serve as a store of value. In the sense that, cryptos with a negative sensitivity to safe-haven assets, like gold or precious metals, are appreciated by investors.


Bouri, E., Azzi, G. and Dyhrberg, A.H. (2016) “On the return-volatility relationship in the Bitcoin market around the price crash of 2013.” Social Science Research Network No.2869855

Hayes, A. (2016) “What factors give cryptocurrencies their value: an empirical analysis.” Social Science Research Network No.2579445