This paper analyzes the Bitcoin price discovery process. We collect data on futures and spot prices for the period December 2017 to May 2018 and compute Hasbrouck's information share and Gonzalo and Granger's common factor component to quantify the contribution of each market to the price discovery process. Both measures coincide in suggesting that the Bitcoin futures market dominates the price discovery process. We also find that both prices are driven by a common factor that is given by a weighted combination of the futures and spot market. Finally, we observe that deviations from the equilibrium condition equating the futures and spot log-price have predictive ability for the return on the Bitcoin spot price but not on the futures price.

No abstract

No abstract

The shock to the global economy from the coronavirus (COVID-19) pandemic has been unprecedented in terms of its speed and severity. Global GDP shrank 3.9% in 2020. This is by far the biggest drop in the past eight decades (IMF, 2020; World Bank, 2020). Shocks to the real economy have led to extreme volatility in global stock markets that is unparalleled in recent decades. In the first quarter of 2020, the FTSE and Dow Jones indices witnessed the largest fall when compared with previous crises since 1987 (BBC, 2020). Baker et al. (2020) show that the early period of COVID-19 stands out for an exceptionally high frequency of stock market swings that is over 20 times the average since 1900. Estimates suggest that COVID-19 costs global stock markets $16 trillion in less than a month due to heightened uncertainty (Gandel, 2020). COVID-19 has also severely impacted other financial asset classes such as sovereign bonds, commodities, and exchange rates. In their study of the correlation within the major asset classes between the COVID-19 pandemic and the 2008 Global Financial Crisis (GFC), Kinateder et al. ( 2021) observe a considerable degradation of co-relationship within the asset classes in COVID-19 compared with GFC.Although the coronavirus is not substantially more lethal than past viral outbreaks, the transmission rate is considerably higher (O'Donnell et al., 2021;Sanche et al., 2020). This rapid transmission and the accompanying containment measures led to more severe impact on stock markets compared with preceding outbreaks. For instance, S&P 500 experienced peak-to-trough losses during COVID-19 that are nearly twofold as compared to SARS; fourfold as compared to MERS; and sixfold as compared to Swine flu and Ebola virus (O'Donnell et al., 2021). Similarly, Baker et al. (2020) conclude that no previous pandemic, including the Spanish flu, has impacted the stock market as strongly as COVID-19. Their evidence suggests that government restrictions on commercial activities and social distancing measures are the main factors affecting stock market volatility. While assessing the relative fallouts from COVID-19 and SARS, Avalos

This paper examines the integration of financial markets using data from the Dubai Financial Market Stock Exchange, Abu Dhabi Stock Exchange and the FTSE Nasdaq Dubai UAE 20 index. To do this, we apply a vector error correction model and a permanent-transitory decomposition of the series of prices. Our results reveal the existence of a long-run equilibrium relationship between the three financial indices suggesting that UAE stock markets are integrated. Shocks to any of these markets affect the other markets in the long and the short run through the equilibrium condition. We uncover a major role of the FTSE Nasdaq Dubai UAE 20 index in this equilibrium relationship. Our analysis of market integration also allows us to obtain a permanent-transitory decomposition given by two common factors that drive the three financial indices. Whereas the first factor is defined as a weighted combination of the two major financial indices the second factor is mainly determined by the FTSE Nasdaq Dubai. As a byproduct of our analysis, we find empirical evidence of short-run and long-run predictability running from the Dubai financial indices to the Abu Dhabi index.