Abstract
This study examines the low volatility anomaly in the cryptocurrency market. Constructing long-short portfolios for a sample of 1000 cryptocurrencies for the period April 28, 2013 – November 1, 2019, we find no evidence of a significant low volatility premium. This result is in contrast to the empirical findings from the equity, bond, and commodity markets and contributes to the debate on the efficiency of cryptocurrencies. In contrast to earlier studies, we find that the cryptocurrency market is far more efficient than expected, even after controlling for different sample sizes, rebalancing periods and / or portfolio construction methodologies.
1. Introduction
Stocks with high volatility should yield high expected return. This is one of the most fundamental principles in finance. However, a wide strand of empirical evidence has put this concept on trial, showing that in fact the opposite is true – Low volatility stocks has historically outperformed high volatility stocks.1 Haugen and Heins (1975, 1972) were the first to document the lack of positive relationship between risk and return in the empirical cross-section of stock market returns. Later studies confirm these findings by demonstrating its robustness across regions (Ang et al., 2006; 2009; Peswani, 2017; Joshipura and Joshipura, 2016), asset classes (Frazzini and Pedersen, 2014), and alternative measures of risk (Chan et al., 1999; Clarke et al., 2006).
4. Conclusion
In this study, we examined the low volatility anomaly for a sample of 1000 cryptocurrencies for the period April 28, 2013–November 1, 2019. Unlike earlier research for traditional asset classes, we cannot find evidence that this effect is present in cryptocurrency markets. While both buy and sell strategies generate positive returns, the zero-cost long-short strategy generates significant negative returns, even after controlling for different sample sizes, rebalancing periods, data preprocessing and portfolio construction methodologies. Potential explanations include agency issues, skewness preferences, and behavioral biases.
