Abstract

This article focuses on the returns of four major cryptocurrencies. It covers a complete study of the dynamics of cryptocurrencies with traditional financial markets, including stocks, gold and oil prices and the technology proxied by hashrates and social sentiments gauged by Twitter data. The article fits the time series model using the Autoregressive Distributed Lag framework and selects the fitted model using penalized least-square estimates. The study also encompasses a set of control variables to improve the model’s accuracy. The findings confirm the existence of a dynamic relationship between the cryptocurrency market and the traditional financial markets. Our results imply that cryptocurrencies can be used as a tool for portfolio diversification. This study is a unique attempt at identifying the major drivers of the cryptocurrency market at large, by disentangling and modelling the dynamic relationships shared by the leading four cryptocurrencies with the relevant components of the financial markets. This article is a significant contribution to the emerging literature on cryptocurrencies and has implications for practitioners.

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