How Cryptocurrencies diversify macroeconomic risk: Investigating US macroeconomic impacts on cryptocurrency markets from a monetarism and credit creation perspective.

Afreh, Kwame (2021) How Cryptocurrencies diversify macroeconomic risk: Investigating US macroeconomic impacts on cryptocurrency markets from a monetarism and credit creation perspective. [Dissertation (University of Nottingham only)]

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Abstract

This paper studies the hedging capabilities of unsystematic risk that cryptocurrencies provide to a portfolio, using arch or garch time series analysis. My passion for blockchain innovation and the combination of finance and technology was my main driver for the development of the thesis.

By following a monetarism approach, the paper is also able to conclude whether cryptocurrencies have features to which liken to the fisher equation, and the effects of credit creation from the banking sector on the asset class. Research is conflicted on the dynamics behind Bitcoin price drivers, to which some researches go as far as to call it a purely speculative asset class. By incorporating analysis on XRP and Litecoin, the paper is able to expand on current literature by broadening macroeconomic analysis to multiple cryptocurrencies rather than its current sole focus on Bitcoin.

I find that Bitcoin and Litecoin have similar properties to that of a currency proposed by monetarism underpinned by the fisher equation, whilst XRP does not. XRP’s model is sensitive to the efficiency of the markets, to which improve post 2017. In addition to this, Bitcoin and Litecoin can categorically be used as safe haven assets against bearish stock market outlooks. Bitcoin has the least correlation to macroeconomic indicators, whilst XRP has the most correlation. Finally, the credit creation in the banking sector has significantly positive impacts on all three assets, showing that cryptocurrencies increase in value as the dollar debases.

These results have implications for investors as the hedging and price drivers of cryptocurrencies are made clear, impacting the efficient allocation of a portfolio to achieve minimum variance.

Item Type: Dissertation (University of Nottingham only)
Depositing User: Afreh, Kwame
Date Deposited: 19 Apr 2023 15:21
Last Modified: 19 Apr 2023 15:21
URI: https://eprints.nottingham.ac.uk/id/eprint/66330

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