The linkage between Google search volume intensity and cryptocurrency trade volume: An analysis on bitcoin, ethereum, and cardano
Cryptocurrencies have grown significantly over the past years and have been seen by many investors as speculative assets that they can trade in order to generate returns. Analysts have always been interested in discovering indicators that can help them better predict cryptocurrency movements. The li...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2022
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etdb_econ/47 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1048&context=etdb_econ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Language: | English |
| Summary: | Cryptocurrencies have grown significantly over the past years and have been seen by many investors as speculative assets that they can trade in order to generate returns. Analysts have always been interested in discovering indicators that can help them better predict cryptocurrency movements. The literature has shown that investor attention has an effect on investors’ purchasing decisions. In more recent studies, Google search intensity has been used as a proxy for investor attention. With that being said, the researchers wanted to investigate if there is a dependence structure between Google search intensity and cryptocurrency trading volume for Bitcoin, Ethereum, and Cardano. The researchers employed Spearman’s Rank-order Correlation, a Vector Autoregression framework, and a Copula approach. For the Spearman’s Rank-order Correlation, all cryptocurrency trade volumes showed dependence with all Google search intensities. It was consistent for all three cryptocurrencies that Ethereum search intensity always has the highest correlation with all trade volumes. The VAR estimates show that Ethereum now has a stronger influence on other cryptocurrencies compared to Bitcoin as it is able to predict not only the trade volume of other altcoins but also Bitcoin’s as well. Furthermore, the positive effect of Google search intensity on trade volume is only short-term. For the copula approach, we determined that the best fitting copula type for the Bitcoin and Cardano model is the Gaussian copula, while the best fitting copula type for the Ethereum model is the Frank copula. Overall, the results of this paper support the notion that a dependence structure between Google search intensity and cryptocurrency trade volume exists for Bitcoin, Ethereum, and Cardano. |
|---|