Why cryptocurrency markets are inefficient: The impact of liquidity and volatility
By K. Al-Yahyaee, Walid Mensi, Hee-un Ko, Seong‐Min Yoon, Sang Hoon Kang. 2020
125 citations recorded by the source corpus.
Abstract In this research, we study the multifractality, long-memory process, and efficiency hypothesis of six major cryptocurrencies (Bitcoin, Ethereum, Monero, Dash, Litecoin, and Ripple) using the time-rolling MF-DFA approach. For an in-depth analysis, this study uses the quantile regression approach to examine the determinants of efficient markets. The results show that all markets present evidence of long-memory property and multifractality. Furthermore, the inefficiency of cryptocurrency markets is time-varying, and Dash is the least inefficient market while Litecoin is the most inefficient. Finally, we find that higher liquidity improves but higher volatility weakens the efficiency of cryptocurrencies, depending on the quantiles. Therefore, we conclude that high liquidity with low volatility helps active traders to arbitrage away opportunities, resulting in market efficiency.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/ade23ce8788e22f3f800866a4926e25f3127c232
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Citations in the corpus
- Cryptocurrency trading: a comprehensive survey (2020, methodology): “[102] examined multiple fractals, long memory processes and efficiency assumptions of major cryptocurrencies using Hurst exponents, time-rolling MF-DFA and quantile regression methods.”