Price Transmission from Bitcoin to Altcoins: High-Frequency Evidence and Implications for Trading Strategy

This study investigates the lagged price transmission from Bitcoin (BTC) to altcoins (ALTs) using high-frequency data and empirically validates trading strategies that leverage these market inefficiencies. Our comprehensive analysis across multiple market regimes reveals that small-cap cryptocurrencies exhibit significant delayed responses to BTC price movements. To examine this behavior, we introduce a simple indicator of immediate price responsiveness and find that lower liquidity tends to be associated with slower reactions. Granger causality tests further demonstrate unidirectional Granger-causal relationships from BTC to ALTs. Based on these findings, we develop a lag trading strategy using BTC's preceding returns as a leading indicator. Through machine learning-based trading decisions, our strategy consistently outperforms traditional buy-and-hold approaches across diverse market conditions. This research provides evidence of information transmission frictions in cryptocurrency markets and demonstrates the viability of practical investment strategies that leverage short-term anomalies. Our findings offer value to high-frequency and arbitrage traders while contributing new academic insights to the literature on cryptocurrency market microstructure.