Abstract
The aim of this study is to examine the volatility spillover between bitcoin and Turkish financial markets for the pre-COVID-19 and COVID-19 periods. Using GARCH-based volatility spillover indices, the authors find that BTC-USD was a volatility transmitter in the pre-COVID-19 period but has become the main volatility receiver in the COVID-19 period, and its net volatility transmission fell from 0.7% to -10.84%. Moreover, they concluded that the total spillover index increased from 12.49% to 15.25% indicates a low connectedness between the markets in both periods and the error variance in markets is on average 15.25% originated from other markets in the COVID-19 period.
TopIntroduction
Subsequent to the high inflation, sharp drops and volatility in national currency and Istanbul Stock Exchange that are more apparent with the period of pandemic in which economic activities in Turkey has been significantly restricted, search for a safe harbor in the financial markets has directed investors to the cryptocurrencies, especially Bitcoin. The results of Statista Global Consumer Survey indicate that Turkey ranks 4th in the worldwide and first in Europe with the 16 percentages within the world’s biggest 74 economies that use mostly cryptocurrencies compared to the population (Buchholz, 2021). However, while Turkey ranks high in the world in the investment of cryptocurrencies, the Central Bank of the Turkish Republic publicly declared a regulation effective stating that direct or indirect use of cryptocurrencies in payments will not be allowed (OG, 2021). In addition to the heavy demand for cryptocurrencies that significantly impact the background of these legal regulations, it is also crucial to investigate the effect of the pandemic process and alternative investment instruments.
In the financial economics literature, there has been a growing interest to analyze the investment benefits of cryptocurrencies. Especially in an unprecedented crisis period such as Covid-19 pandemic, the effect of cryptocurrencies on international financial markets has no longer to be ignored. There are various studies examining the counter return of the cryptocurrency market against other investment instruments before and during the Covid-19 pandemic. We can list these studies briefly as follows.
Baur and Dimpfi (2021) found in their study that the volatility in Bitcoin prices is extreme and almost 10 times higher than the volatility of the main exchange rates (against the US Dollar, Euro and Yen). Goodell and Goutte (2021) found a strong co-movement between Bitcoin prices and Covid-19. Caferra and Vidal-Tomas (2021) pointed out that cryptocurrencies recovered rapidly during the Covid-19 pandemic, but the stock markets failed to show the same recovery. Zhang et al. (2021) pointed out a downside risk spillover that seems to be time dependent between Bitcoin and four assets (stocks, bonds, currencies and commodities). Ghorbel and Jeribi (2021) analyzed the volatility relationships between five cryptocurrencies, American indexes (S&P 500, Nasdaq and VIX), oil, and gold. This study showed that Bitcoin and gold were accepted as hedges for the US investors before the coronavirus crisis. Unlike gold, it was concluded that cryptocurrencies were not a safe haven for the US investors during the coronavirus crisis. Umar et al. (2021) stated that in the case of the first shock experienced in the crypto market from January 2018 to March 2020, the spillover effect was felt by all financial markets. Moreover, they continued to point out that the stock and bond markets created a great persistence in the volatility of cryptocurrencies, showing that mostly cryptocurrencies are the receiver, not the source of the volatility.
The results of Cebrian-Hernandez and Jimenez-Rodriguez’s study (2021) examining the relationship between Bitcoin volatility and the variables of basic financial environment (several commodities linked to cryptocurrencies, exchange rates, stock market indexes and company stocks) indicate a certain heterogeneity in the adaptation of different variables and also highlight the lack of correlations with traditional safe harbors such as gold and oil. It has been found out that in each multivariate model they examined, Bitcoin volatility was inversely proportional to USD/EUR. In the commodities taken into account in this study, gold and oil showed an insignificant correlation. The volatility of stocks of companies associated with Blockchain technology- RIOT, NVDA and KBR- and the volatility of payment methods- VISA and MASTERCARD- presented a clear and significant correlation with that of cryptocurrencies.
Key Terms in this Chapter
Volatility Spillover: Volatility spillover is a transmission of instability or a contagion of risk from market to market.
Connectedness: Connectedness is a statistical measure of the relationship between variables that allows asymmetries in bilateral connections between markets, instead of inherently symmetrical (hence non-directional) measures such as correlation. Hence, the connectedness index estimates the directional measure of volatility spillover.
Leverage Effects: The leverage effect which is defined as a measure of the effect of negative shocks on volatility helps to describe those unexpected negative shocks have a greater influence on volatility than positive shocks.
Correlation: Correlation measures the direction and strength of linear dependence between two variables. The correlation function is symmetric and undirected, so it is only a bilateral measure of the relationship.
Volatility Clusters: The volatility clusters which are the characteristic of financial returns mirror the leptokurtic shape (fat tails) of the return of the financial assets. The source of the volatility clusters is the direction and magnitude of the price changes. Volatility clustering takes place to large/small price changes being followed by large/small changes in either direction.
Volatility Persistence: Volatility persistence is the strength of the volatility feedback effect High persistence means that volatility shocks will be felt further in the future, albeit to a lesser extent. The persistence of volatility affects the predictability of future economic variables and the predictability of changes in the risk-return balance over business cycles.
Conditional Volatility: The conditional volatility can be defined as a measure of risk or a statistical measure of the change in the values of a financial asset over time. In other words, it is an estimated standard deviation of financial time series under the specified probability distribution.