Эмпирическое исследование "стадного поведения" на рынках криптовалют

This dissertation investigates herd behaviour in the cryptocurrency market, following Avery & Zemsky’s (1998) information-based model of herd behaviour. More specifically, the relationship between event uncertainty and herding is considered as well as the interaction between information uncertainty, herding and price movements. The entire Bitcoin trade history of Poland’s leading cryptocurrency exchange was downloaded and used to measure the daily convergence of investment decisions. In order to assess the arrival of new information into the market, daily rising Bitcoin-related search terms from Google Trends were retrieved and then processed to compute a measure of event uncertainty. Evidence supporting Avery & Zemsky’s information-based model is uncovered –namely a significant positive relation between herding and event uncertainty. Furthermore, large price movements are observed when the market appears to behave like a well informed market, despite high event uncertainty.