The witching week of herding on bitcoin exchanges

Abstract

This paper analyses the herding behaviour among exchanges around the expiration of bitcoin futures traded on the Chicago Mercantile Exchange (CME). The database extends from December 2017 to October 2020, taking as a reference the main exchanges that trade bitcoin (Binance, Bitfinex, Bitstamp, Coinbase, itBit, Kraken, and Gemini) and using hourly closing prices and trading volumes in bitcoin and US dollars. Adapting the proposal of Chang, Cheng and Khorana (2000) (CCK) to test conditional herding, we obtain results that indicate that the herding effect is significant during the week before expiration. After expiration, the herding effect lasts for a few hours and disappears. Information overload originating, among other causes, from sophisticated investors’ strategies may generate this mimetic behaviour. The results show the relevance of intraday data applied to specific events such as expiration since the unconditional analysis shows, in general, anti-herding behaviour throughout the period of study.

Behavioural finance and cryptocurrencies

“…Panel A: Herding behaviour Ballis and Drakos (2020) The results provide evidence that the up-events market dispersion follows market movements at a faster pace compared to the down events Blasco et al (2022) The presence of herding behaviour amongst exchanges around the expiration of Bitcoin futures traded on the Chicago Mercantile Exchange (CME) appears to be significant during the week before expiration Bouri et al (2019a, b) The findings indicate that there is considerable herding behaviour that fluctuates over time and that herding tends to occur as uncertainty increases Choi et al (2022) Findings reveal anti-herding behaviour at shorter time intervals and herding during longer periods, with the phenomenon being even stronger in the latter during down markets Da Gama Silva et al (2019) The results revealed herding behaviour, demonstrating extreme periods of adverse herd behaviour Gurdgiev and O'Loughlin (2020) Results show that investor sentiment can predict the price direction of cryptocurrencies, indicating direct impact of herding and anchoring biases Haryanto et al (2020) Findings show that the cryptocurrency market exhibits a reverse disposition effect in bullish periods and the usual positive disposition effect in bearish periods Jalal et al (2020) The presence of herding is confirmed in cryptocurrencies in the upper quantiles during bullish and high volatility times due to investor overexcitement, which leads to large volume trading J unior et al (2022) Results demonstrate that regardless of market conditions, herding towards the market exhibits substantial movement and persistence Kaiser and St€ ockl (2020) The study shows experimentally that herding measures focused on a transfer currency give a more exact depiction of dispersion in investors' opinions on the cryptocurrency market Kallinterakis and Wang (2019) The results suggest that, besides herding and asymmetry (stronger during up-markets), the cryptocurrency market entails strong destabilising potential King and Koutmos (2021) Study documents heterogeneity in the types of feedback trading strategies investors utilise across markets Kumar (2020) Herding is pronounced when the market is either passing through stress or has become highly volatile Kyriazis (2020) The empirical estimations of the study reveal that herding behaviour is evident only in bull markets Manahov (2021) The results of the study demonstrate that cryptocurrency traders facilitate EPMs and demand liquidity even during the utmost EPMs, observing the presence of herding behaviour during up markets across the entire dataset Omane-Adjepong et al (2021) Results reference significant symmetric crowd and imitation trading, which are dependent on time, along with asymmetric herd behaviour in the cryptocurrency and stock markets Raimundo J unior et al (2022) Findings showcase that herding towards the market shows significant movement and persis...…”

“…In their study Raimundo J unior et al (2022) reveal that herding towards the market shows significant movement, and persistence regardless of the market condition. Finally, Blasco et al (2022) analyse herding behaviour amongst exchanges around the expiration of Bitcoin futures traded on the Chicago Mercantile Exchange (CME), finding that herding appears to be significant during the week before expiration.…”

Blockchain and digital finance

“…The second sub-theme is mainly about investor behavior and market phenomena in cryptocurrency markets. Blasco et al ( 2022 ) study the herding effect among exchanges before the Bitcoin futures expiration date. Haykir and Yagli ( 2022 ) investigate financial bubbles in the cryptocurrency market during the COVID-19 pandemic.…”

Behavioural Finance and Cryptocurrencies

“…In their study Raimundo Júnior et al (2022) reveal that herding toward the market shows significant movement, and persistence regardless of the market condition. Finally, Blasco et al (2022) analyse herding behaviour among exchanges around the expiration of Bitcoin futures traded on the Chicago Mercantile Exchange (CME), finding that herding appears to be significant during the week before expiration.…”

“…Panel A: Herding Behaviour Ballis and Drakos (2020) The results provide evidence that the up-events market dispersion follows market movements at a faster pace compared to the down events. Blasco et al (2022) The presence of herding behaviour among exchanges around the expiration of Bitcoin futures traded on the Chicago Mercantile Exchange (CME), appears to be significant during the week before expiration.…”