Abstract:
In the context of the great turmoil in the financial markets caused by the COVID-19 outbreak, we examine the predictability of the US Treasury securities (Chapter 2), international stocks (Chapter 3), foreign exchange rates and Bitcoin (Chapter 4) and agricultural commodity futures (Chapter 5) given daily infectious diseases-related uncertainties (EMVID) using the heterogonous autoregressive volatility (HAV-RV) model. On stationary intraday data computed from a 5-minute interval, we conduct a recursive out-of-sample forecast. Through the RMSFE metric, our results provide evidence that these financial assets remain attractive to investors within the pandemic episode, with Bitcoin obtaining significantly high forecast gains among all the other assets in the medium and long forecast horizons. The US Treasury securities remain risk-free and the worldwide recognition of gold as a “safe haven” asset is emphasised. Among the agricultural traded commodities, cocoa and oats futures had significant forecast gains. The international stocks in Pakistan and Singapore appeared to be the most volatile. It is also evident that an econometrician can acquire the highest forecast gain in the Swiss Franc futures in the foreign exchange market.
In Chapter 6, we use annual data on real gold returns and the probability of fatality due to contagious diseases over the period 1258 to 2020, we detect nonlinearity and regime changes in the relationship between the two variables of concern. We rely on a quantile regression model to show that real gold returns can hedge against the risks associated with such rare disasters (COVID-19), primarily when the market is in its bullish state, with it being negatively impacted in its bearish state.
By assessing the role of contagious diseases on these financial assets’ returns we find strong evidence that contagious diseases play an important role in forecasting their RV. Understandably, our results have important portfolio implications for investors, speculators and portfolio managers during periods of high levels of uncertainty associated with infectious diseases.
