Forecasting cryptocurrency returns and volume using search engines

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.

Bitcoin pricing: impact of attractiveness variables

“…Buchholz et al (2012) concluded that Google searches had a causal effect on Bitcoin transactions; however, the opposite did not seem to be applicable. Nasir et al (2019), by using copulas and a nonparametric approach, confirmed that Google searches have a direct relationship with Bitcoin performance, particularly in the short run: the more often the investors look for information about the cryptocurrency, the higher the returns and trading volume that follow.…”

“…Searches on electronic media for information about what Bitcoin is and how it works may be a variable that explains demand increases for the coin and, consequently, its price. Some authors sought to estimate a relationship between the search history of the term Bitcoin on platforms such as Google (Kristoufek 2013;Buchholz et al 2012;Bouoiyour and Selmi et al 2015;Polasik et al 2015;Nasir et al 2019), Wikipedia (Kristoufek 2013), Twitter (Davies 2014) and online forums (Kim et al 2017). Polasik et al (2015) described popularity as a strong factor for Bitcoin price returns.…”

Discovering interlinkages between major cryptocurrencies using high-frequency data: new evidence from COVID-19 pandemic

“…Thecryptocurrency market, a new asset class, has attracted significant attention from researchers, investors, policymakers, and governments in recent years (Makarov and Schoar 2020 ; Nasir et al 2019 ). The size of the cryptocurrency market is continuously increasing due to (a) the decline in public trust toward the central banking system after the global financial crisis (Weber 2016 ), (b) the fourth industrial revolution and use of smart technologies, (c) its acceptance as legal currency in different countries, and (d) its acceptance by large companies like Facebook, Microsoft, Shopify, JPMorgan, and Tesla.…”

Spillover Risks on Cryptocurrency Markets: A Look from VAR-SVAR Granger Causality and Student’s-t Copulas

“…Also, Li and Wang (2017) pointed out the role of attention in Bitcoin returns. Nasir et al (2019) contributed to the existing literature stating that Google search engines could be used to forecast Bitcoin returns in one-week shock. However, this element failed to explain why Bitcoin is volatile.…”