Affiliation:
1. Kent Business School University of Kent Kent UK
2. Bayes Business School City, University of London London UK
3. Adam Smith Business School University of Glasgow Glasgow UK
Abstract
AbstractThis study explores the effectiveness of technical and fundamental analysis in predicting and trading the returns of 12 cryptocurrencies, namely Bitcoin, Ethereum, Ripple, Dash, Cardano, Avalanche, Binance Coin, Dogecoin, Polkadot, Litecoin, Terra and Solana. A universe of 7846 technical rules, five log moving average‐based ratios and 59 fundamental factors are used to test predictability and profitability through the Lucky Factors methodology and Superior Predictive Ability test. We observe predictability for a small set of technical and fundamental rules, while only the short‐term log moving average‐based ratio and Hashrate Index demonstrate genuine in‐sample and out‐of‐sample profitability. Our findings question the value of both technical and fundamental analysis on cryptocurrencies.
Subject
Economics and Econometrics,Finance,Accounting
Cited by
1 articles.
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