The role of technical chart patterns in the early Bitcoin market: intraday evidence from the Mt.Gox transaction dataset

Abstract

Abstract We use transaction-level data from the Bitcoin exchange Mt.Gox, including over 1.4 million transactions from more than 45,000 traders, to investigate the role of technical chart patterns in the early Bitcoin market from April 2011 to September 2013. Employing a pattern recognition algorithm, we identify hourly trading signals for five major chart patterns. Buy signals of these patterns are associated with an average increase in abnormal trading volume of more than 53%. Trades executed during buy signal periods yield significantly higher average returns than those made during non-signal periods. Traders who use chart patterns more frequently are more likely to generate right-skewed return distributions, engage in more active trading, and achieve higher average roundtrip returns. Our research suggests that chart pattern trading was a crucial tool for Mt.Gox clients, highlighting the importance of technical heuristics in shaping the dynamics in a less efficient and unregulated market environment. By leveraging a comprehensive transaction dataset from a major cryptocurrency exchange, we provide unique insights into the actual trading behavior of the first Bitcoin adopters. This sets our work apart from previous studies that mainly rely on backtesting technical strategies using publicly available price data.

Keywords

• Technical analysis
• Bitcoin
• Cryptocurrencies
• Chart pattern recognition
• Trading volume
• Skewness preference