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

IF 2.8 3区 经济学 Q2 BUSINESS, FINANCE
Mingzhe Wei, Ioannis Kyriakou, Georgios Sermpinis, Charalampos Stasinakis
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Abstract

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.

Abstract Image

加密货币与幸运因素:技术分析和基本面分析的价值
本研究探讨了技术分析和基本面分析在预测和交易 12 种加密货币(即比特币、以太坊、瑞波币、Dash、卡达诺、雪崩币、Binance Coin、Dogecoin、Polkadot、莱特币、Terra 和 Solana)收益方面的有效性。我们使用 7846 条技术规则、5 个基于对数移动平均线的比率和 59 个基本因素,通过幸运因素方法和卓越预测能力测试来检验可预测性和盈利能力。我们观察到一小部分技术和基本面规则具有可预测性,而只有基于对数移动平均线的短期比率和哈希率指数表现出真正的样本内和样本外盈利能力。我们的研究结果对加密货币技术分析和基本面分析的价值提出了质疑。
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来源期刊
CiteScore
5.70
自引率
6.90%
发文量
143
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