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Wang, Lin (2020) Cryptocurrency Tokens: A Quantitative Study of Global Minimum Variance Portfolio and Naïve Allocation Strategies in Portfolio Diversification. [Dissertation (University of Nottingham only)]

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Abstract

Blockchain technology and cryptocurrencies have developed rapidly ever since Bitcoin was established. As this innovative and technological investment option transforms the current financial system, investors should ensure they explore a broad range of cryptocurrency investments and seize opportunities to diversify their portfolios. Considering the meteoric rise of cryptocurrencies and their enormous potential in portfolio management, investors should develop new investment strategies that closely track the evolution and expansion of the cryptocurrency market. This is increasingly crucial to achieving and maintaining long-term investment success. Multiple studies have examined the effect of portfolio diversification using cryptocurrencies, but the majority of them treat cryptocurrencies as a general asset type and only include a small number of cryptocurrency tokens. Therefore, this study focuses solely on cryptocurrency tokens and assesses the impact of adding such tokens into foreign exchange, commodity, and stock portfolios from 9 September 2019 to 30 April 2021. I investigate the impact of such diversification on both naïve allocation and Global Minimum Variance Portfolio (GMVP). The results show three key findings: (i) tokens have little correlation with conventional assets; (ii) tokens effectively achieve diversification in both naïve portfolios and GMVP in terms of enhancing risk-adjusted returns, but they do not necessarily reduce portfolio risk; and (iii) naïve allocation outperforms GMVP allocation in terms of rate of return and Sharpe ratio, but at the cost of higher risk level. Consequently, I conclude that risk- averse investors may prefer to adopt a GMVP allocation strategy when diversifying their original portfolios with tokens, as this results in less improvement in risk-adjusted return and lower additional risk.

Item Type:	Dissertation (University of Nottingham only)
Depositing User:	WANG, LIN
Date Deposited:	19 Apr 2023 15:04
Last Modified:	19 Apr 2023 15:04
URI:	https://eprints.nottingham.ac.uk/id/eprint/66246

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