Momentum Trading in Cryptocurrencies: A Comparative Study of Time-Series and Cross-Sectional Strategies - Gbadebo, Adedeji Daniel (Buhalterinės apskaitos teorija ir praktika, 2026)
Momentum-based trading strategies are widely employed in financial markets and have become increasingly relevant within the cryptocurrency ecosystem. This study examines the profitability of momentum-based trading strategies in cryptocurrency markets using a multi-horizon exponential moving average (EMA) framework. The analysis covers eight major cryptocurrencies, Bitcoin, Ethereum, Litecoin, Ripple, Binance Coin, Cardano, Dogecoin, and Solana over the period 1 January 2020 to 31 October 2025. Momentum signals are constructed using short- and long-term Exponential Moving Average (EMAs) combined with volatility normalization to ensure comparability across assets. Two portfolio structures are evaluated: time-series momentum, which adjusts exposure for each asset individually, and cross-sectional momentum, which ranks assets by relative strength. Empirical results show that momentum effects remain economically meaningful in digital assets. Time-series momentum delivers superior performance, achieving an annual return of 31.96% and outperforming cross-sectional momentum on a risk-adjusted basis. Cross-sectional momentum exhibits higher max drawdowns of 55.0% but lower overall profitability in terms of annual returns, partly due to high correlations among cryptocurrencies. The findings confirm that trend persistence and volatility remain key drivers of momentum profitability in crypto markets.