Exploration of the relationships between Google searches and Bitcoin’s volatility, traded volume and price
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School of Business |
Bachelor's thesis
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Authors
Date
2018
Department
Major/Subject
Mcode
Degree programme
(Mikkeli) Bachelor’s Program in International Business
Language
en
Pages
38 + 16
Series
Abstract
Bitcoin has gained more and more press coverage during the past few years.Bitcoin is also fairly new phenomena, and as such it has not been researched as much as other, more traditional financial assets. Bitcoin is also highly speculative asset. That is why information demand is important variable when looking at Bitcoin’s key figures, which are: price, volatility and traded volume. This paper uses Google Searches (Google Trend Index) as an independent variable whereas Bitcoin’s price, volatility and traded volume are dependent variables. The aim of the study is to find relationships between the independent variable and the dependent variables, through correlations and regression models. The data will be examined yearly from 2014 to 2017. The paper is exploratory in nature, meaning that it will not make specific hypothesizes, due to the lack of research conducted on Bitcoin, but will make more broad assumptions on the results. The aim of the paper is to create foundation for future research and gain more information on the matter and possibly gain new perspectives. The main findings of this study were upward trend and overall very high correlations across all years. However, the results for 2017 were significantly higher than the previous years. All the regression models showed positive coefficients meaning that as the Google Trend Index rises so does Bitcoin price, volatility and traded volume. However, the rise in volatility was fairly limited. Also, nearly all the regression model results were significant. The problem of internal validity existed in the study, which meant that no causal relationship could be found.Description
Thesis advisor
Stepanov, RomanKeywords
Bitcoin, volatility, volume, Google searches, information demand, regression, correlation, behavioral finance