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Herding and feedback trading in cryptocurrency markets
Timothy King1, Dimitrios Koutmos2
1University of Kent, Canterbury, Kent, CT2 7NZ UK.
Annals of Operations Research
|January 19, 2021
Summary
Investor behavior in cryptocurrency markets varies, with some showing trend-chasing (herding) and others contrarian tendencies. These trading patterns significantly impact price dynamics and risk-return tradeoffs for major digital assets.
Area of Science:
- Quantitative Finance
- Behavioral Finance
- Cryptocurrency Market Analysis
Background:
- Cryptocurrency markets exhibit unique price dynamics influenced by investor behavior.
- Understanding herding and feedback trading is crucial for market analysis.
Purpose of the Study:
- To investigate the prevalence of herding and feedback trading in major cryptocurrencies.
- To analyze how these behaviors affect cryptocurrency price dynamics and autocorrelation.
- To examine the risk-return tradeoffs within an intertemporal asset pricing model.
Main Methods:
- Analysis of price data for nine major cryptocurrencies (Bitcoin, Ethereum, XRP, Bitcoin Cash, EOS, Litecoin, Stellar, Cardano, IOTA).
- Identification and differentiation of herding (trend-chasing) and contrarian trading behaviors.
- Application of an intertemporal asset pricing model.
Main Results:
- Heterogeneity observed in investor feedback trading strategies across different cryptocurrency markets.
- Evidence of herding behavior in some markets and contrarian behavior in others.
- Trading behaviors impact autocorrelation patterns in cryptocurrency prices.
Conclusions:
- Investor behavior, specifically herding and feedback trading, significantly drives cryptocurrency price dynamics.
- The findings provide insights into the forces shaping cryptocurrency markets.
- The study clarifies the relationship between trading behaviors, autocorrelation, and risk-return tradeoffs.
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