Data - Raw & Transformed - Cryptocurrencies & Macro-Financial Indices

Published: 4 November 2019| Version 1 | DOI: 10.17632/8xd54xzbf8.1
Oluwatobi Oyefeso


The empirical investigation of the connection between cryptocurrencies and macro-financial indices is accomplished by employing the US Dollar-dominated price time series of bitcoin, bitcoincash and monero types of cryptocurrencies; along with the following macro-financial indices, USA short-term interest rate, USA bank prime lending rate, USA tedrate and USA medium-term interest rate. Notably, considering the fact that all the available digital currencies are usually priced in US Dollar, this study considers it appropriate to use the US macro-financial variables for uniformity and simplicity. Principally, the objective of this study is to investigate the possible short-run impact of macro-financial indices on cryptocurrencies in the study sample, thereby, ascertaining if the performance of cryptocurrencies can be predicted from the trend of macro-financial variables. The choice of the macro-financial variables in this study is underpinned by the economic influence of those variables in the financial markets. The data for USA short-term interest rate, USA bank prime lending rate and tedrate is sourced from the Federal Reserve, and the Federal Reserve Statistical Release website. Additionally, the daily prices for the cryptocurrencies: bitcoin, monero and bitcoincash are sourced from an online investing company. All the daily data series in the sample covers the period 1st January 2015 through 1st October 2019. The price series for all variables in the sample are converted into continuously compounded percentage exchange rate return calculated thus, r_t=(p_t⁄p_(t-1) ), where r_t is the continuously compounded return at time t, p_t is the price at time t and p_(t-1) is the price at time t-1 (i.e. t minus one) period.



Finance, Macroeconomic Data