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Cryptocurrencies and Lucky Factors: The value of technical and fundamental analysis

Wei, M., Kyriakou, I. ORCID: 0000-0001-9592-596X, Sermpinis, G. & Stasinakis, C. (2023). Cryptocurrencies and Lucky Factors: The value of technical and fundamental analysis. International Journal of Finance and Economics, doi: 10.1002/ijfe.2863


This 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.

Publication Type: Article
Additional Information: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2023 The Authors. International Journal of Finance & Economics published by John Wiley & Sons Ltd.
Publisher Keywords: cryptocurrencies, fundamental analysis, multiple hypothesis testing, technical analysis
Subjects: H Social Sciences > HG Finance
H Social Sciences > HN Social history and conditions. Social problems. Social reform
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Bayes Business School > Actuarial Science & Insurance
SWORD Depositor:
[thumbnail of Int  J Fin Econ - 2023 - Wei - Cryptocurrencies and Lucky Factors  The value of technical and fundamental analysis.pdf]
Text - Published Version
Available under License Creative Commons: Attribution International Public License 4.0.

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