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9/1/20: Herding and Anchoring in Cryptocurrency Markets

Summary:
Our new paper, with Daniel O'Loughlin, titled "Herding and Anchoring in Cryptocurrency Markets: Investor Reaction to Fear and Uncertainty" has been accepted to the Journal of Behavioral and Experimental Finance, forthcoming February 2020. The working paper version is available here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3517006.Abstract:Cryptocurrencies have emerged as an innovative alternative investment asset class, traded in data-rich markets by globally distributed investors. Although significant attention has been devoted to their pricing properties, to-date, academic literature on behavioral drivers remains less developed. We explore the question of how price dynamics of cryptocurrencies are influenced by the interaction between behavioral factors behind investor

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Our new paper, with Daniel O'Loughlin, titled "Herding and Anchoring in Cryptocurrency Markets: Investor Reaction to Fear and Uncertainty" has been accepted to the Journal of Behavioral and Experimental Finance, forthcoming February 2020.

The working paper version is available here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3517006.

Abstract:
Cryptocurrencies have emerged as an innovative alternative investment asset class, traded in data-rich markets by globally distributed investors. Although significant attention has been devoted to their pricing properties, to-date, academic literature on behavioral drivers remains less developed. We explore the question of how price dynamics of cryptocurrencies are influenced by the interaction between behavioral factors behind investor decisions and publicly accessible data flows. We use sentiment analysis to model the effects of public sentiment toward investment markets in general, and cryptocurrencies in particular on crypto-assets’ valuations. Our results show that investor sentiment can predict the price direction of cryptocurrencies, indicating direct impact of herding and anchoring biases. We also discuss a new direction for analyzing behavioral drivers of the crypto assets based on the use of natural language AI to extract better quality data on investor sentiment.

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