Forecasting cryptocurrency returns and volume using search engines

Muhammad Ali Nasir, Toan Luu Duc Huynh, Sang Phu Nguyen, Duy Duong

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

In the context of the debate on the role of cryptocurrencies in the economy as well as their dynamics and forecasting, this brief study analyzes the predictability of Bitcoin volume and returns using Google search values. We employed a rich set of established empirical approaches, including a VAR framework, a copulas approach, and non-parametric drawings, to capture a dependence structure. Using a weekly dataset from 2013 to 2017, our key results suggest that the frequency of Google searches leads to positive returns and a surge in Bitcoin trading volume. Shocks to search values have a positive effect, which persisted for at least a week. Our findings contribute to the debate on cryptocurrencies/Bitcoins and have profound implications in terms of understanding their dynamics, which are of special interest to investors and economic policymakers.

Original languageEnglish
Article number2
Number of pages13
JournalFinancial Innovation
Volume5
Issue number1
Early online date10 Jan 2019
DOIs
Publication statusPublished - 1 Dec 2019
Externally publishedYes

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