Summary:
Cryptocurrencies have become famous nowadays and more and more studies on all their aspects are being published.
In this thesis, two main studies are conducted with one sub-study to follow.
The first study refers to the examination of the interconnection of four popular cryptocurrencies namely Bitcoin, Ethereum, Litecoin and Cardano. The study employs the Ordinary Least Squares (OLS) Model and basic tests are conducted.
The second study is related to the examination of the volatility dynamics of the four cryptocurrencies namely Bitcoin, Ethereum, Litecoin and Cardano in relation to the nine popular indices namely S&P 500, Dow Jones, Gold Price, Crude Oil Price WTI, Dow Jones Conventional Electricity, Dow Jones Real Estate, Baltic Dry index (BDI), Barclays US Aggregate Bond Index, S&P Goldman Sachs Commodity Index. For this study the employment of a multivariate GARCH model is necessary. Thus, the Diagonal BEKK model has been selected to be used.
Furthermore, a sub-study is presented, which deals with the volatility dynamics of Bitcoin and the nine aforementioned indices for the pre-COVID-19 period and the COVID-19 period.
This thesis has shown not only that there is positive relationship between the Bitcoin and other cryptocurrencies returns but also that cryptocurrencies present the highest weekly loss, highest average return, and highest volatility among all the studied indices and that the most stable index is the Barclays US Aggregate Bond. It can also be determined that the influence of the past common information of the variables is less significant than the persistence of covariance between all cryptocurrencies and indices. Also, the results show that S&P 500 index previous information strongly affects the cryptocurrencies’ returns and vice versa, while for the Gold and cryptocurrencies case, previous information has the least impact on their returns comparing to the other indices. As for the comparison of the pre-COVID-19 and COVID-19 periods volatility spillover between Bitcoin and indices, the covariance ARCH coefficients seem to be different in each period, nevertheless, for both periods the greatest covariance GARCH coefficient is spotted between Bitcoin and S&P Goldman Sachs Commodity Index, while the lowest is observed for the Bitcoin and Baltic Dry Index for the pre-COVID-19 period, while for the Bitcoin and Dow Jones for the COVID-19 period. The effect of COVID-19 crisis seems to have changed the behavior of financial and cryptocurrency markets.
Keywords:
Cryptocurrency, Volatility, GARCH, COVID-19
