Investor attention and cryptocurrency price crash risk: a quantile regression approach

Abstract

Purpose

Motivated by the lure of cryptocurrencies for retail investors, whose concentrated holdings are particularly exposed to price crash risk, this paper aims to study the relationship between investor attention and crash risk for a range of cryptocurrencies.

Design/methodology/approach

This study adopts a quantile regression approach to determine the effect of investor attention on crash risk. Crash risk is measured using the negative coefficient of skewness and down up volatility.

Findings

This study finds that the connection is concentrated in the tails of the crash risk distribution. Investor attention has a positive relationship with crash risk when crash risk is low (below-median quantiles) and negative when crash risk is high (above-median). The findings are consistent for different measures of crash risk, for alternate internet searches and for a panel of large cryptocurrencies in addition to Bitcoin. This study also notes seasonality in crash risk, with higher crash risk during the June–August period and lower crash risk in the Halloween period that runs from November to April.

Originality/value

The results provide insights that are not apparent in previous analyses of cryptocurrency price crash risk. The results are particularly important for retail investors, who constitute a large portion of the cryptocurrency market, as they tend to hold concentrated investments and so a price crash of a single asset may have a large bearing on their wealth.

Citation

Smales, L.A. (2022), "Investor attention and cryptocurrency price crash risk: a quantile regression approach", Studies in Economics and Finance, Vol. 39 No. 3, pp. 490-505. https://doi.org/10.1108/SEF-09-2021-0371