Forecasting Returns & Volume of Cryptocurrencies by Using Search Engines

Muhammad Ali Nasir (), Toan Luu Duc Huynh, Sang Phu Nguyen and Duy Duong
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Muhammad Ali Nasir: Leeds Beckett University
Toan Luu Duc Huynh: University of Economics Ho Chi Minh City
Sang Phu Nguyen: Banking University of Ho Chi Minh City
Duy Duong: Banking University of Ho Chi Minh City

A chapter in Blockchain, Crypto Assets, and Financial Innovation, 2025, pp 219-233 from Springer

Abstract: Abstract In the context of the debate on blockchain technology and associated Cryptocurrencies, their role in the economy as well their dynamics and forecasting, this brief study has analysed the predictability of cryptocurrencies (Bitcoin) volume and returns using Google Search Values. We employed a rich set of established empirical approaches including a VAR framework, Copulas approach and non-parametric drawings for calculating dependence structure. Using weekly dataset from 2013 to 2017, our key results suggest that the frequency of Google search leads to positive returns and surge in the trading volume. The shocks to the searching value have a positive effect which persisted for at least a week. Our findings contribute to the debate on Cryptocurrencies and have profound implications in terms understanding their dynamics which are of special interest to investors and economic policymakers.

Keywords: Financial innovation; Forecasting; Blockchain; Google search values; Bitcoin; Cryptocurrencies (search for similar items in EconPapers)
JEL-codes: C58 G10 G14 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-96-6839-7_8

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DOI: 10.1007/978-981-96-6839-7_8

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