Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19

Dealing with structural breaks is an essential step in most empirical economic research. This is particularly true in panel data comprised of many cross-sectional units, which are all affected by major events. The COVID-19 pandemic has affected most sectors of the global economy;however, its impact on stock markets is still unclear. Most markets seem to have recovered while the pandemic is ongoing, suggesting that the relationship between stock returns and COVID-19 has been subject to structural break. It is therefore important to know if a structural break has occurred and, if it has, to infer the date of the break. Motivated by this last observation, the present article develops a new break detection toolbox that is applicable to different sized panels, easy to implement and robust to general forms of unobserved heterogeneity. The toolbox, which is the first of its kind, includes a structural change test, a break date estimator, and a break date confidence interval. Application to a panel covering 61 countries from January 3 to September 25, 2020, leads to the detection of a structural break that is dated to the first week of April. The effect of COVID-19 is negative before the break and zero thereafter, implying that while markets did react, the reaction was short-lived. A possible explanation is the quantitative easing programs announced by central banks all over the world in the second half of March.

Did green debt instruments aid diversification during the COVID-19 pandemic?

Faced with a persistent pandemic, investors are concerned about portfolio diversification. While the literature on COVID-19 has evolved impressively, limited work remains on diversification opportunities. We contribute to the literature by exploring the volatility and co-movement of different sovereign debt instruments, including green sukuk, sukuk, bond and Islamic and conventional equity indices for Indonesia. Our results consistently point towards increased asset co-movement and weak profitability during the pandemic. Interestingly, sukuk and green sukuk have a 14% correlation with stocks, suggesting potential diversification prospects in times of extreme shocks.

Understanding exchange rate shocks during COVID-19

Using a dynamic VAR model fitted to hourly data, we evaluate the evolution of spillover shocks from exchange rates returns of EURO, Yen, CAD and GBP. We find that over the COVID-19 sample: (a) total exchange rate shock spillovers explain around 37.7% of the forecast error variance in the exchange rate market compared to only 26.1% in the pre-COVID-19 period;and (b) exchange rate own shocks explain between 56% to 75% of own exchange rate movements. These results hold in multiple robustness tests. The implication is that exchange rates predict most of their own changes. We confirm this through an economic significance test where we show that the shock spillovers predict exchange rate returns and these predicted exchange rates can be useful in extracting buy and sell trading signals.

Evidence of oil market price clustering during the COVID-19 pandemic.

We use hourly data on opening price, closing price, opening ask price, opening bid price, closing ask price and closing bid price to show that while oil prices are characterized by price clustering behavior, prices tend to cluster on numbers closer to zero than to one. Comparing the pre-COVID-19 sample with the COVID-19 sample, we find that evidence of price clustering is 8% more in the COVID-19 sample. We test the determinants of price clustering and find that as much as 30% of the price clustering behavior can be attributed to the COVID-19 pandemic. Finally, using a simple technical trading strategy, we do not find any evidence that the oil market is profitable in the COVID-19 period.

Has COVID-19 changed the stock return-oil price predictability pattern?

In this paper, we examine if COVID-19 has impacted the relationship between oil prices and stock returns predictions using daily Japanese stock market data from 01/04/2020 to 03/17/2021. We make a novel contribution to the literature by testing whether the COVID-19 pandemic has changed this predictability relationship. Employing an empirical model that controls for seasonal effects, return-related control variables, heteroskedasticity, persistency, and endogeneity, we demonstrate that the influence of oil prices on stock returns declined by around 89.5% due to COVID-19. This implies that when COVID-19 reduced economic activity and destabilized financial markets, the influence of oil prices on stock returns declined. This finding could have implications for trading strategies that rely on oil prices.

COVID-19 research outcomes: An agenda for future research

This paper undertakes a survey of the COVID-19 pandemic literature. I find that stock market performance, COVID-19 policies and energy markets are most researched. I reason that this is because of availability of relatively high-frequency time-series data supported by appropriate econometric tools. I discuss a range of socioeconomic- and finance-related subjects of significant policy importance. In so doing, I identify specific and broad areas in need of immediate research. These future research topics have strong policy importance.

Understanding exchange rate shocks during COVID-19.

Using a dynamic VAR model fitted to hourly data, we evaluate the evolution of spillover shocks from exchange rates returns of EURO, Yen, CAD and GBP. We find that over the COVID-19 sample: (a) total exchange rate shock spillovers explain around 37.7% of the forecast error variance in the exchange rate market compared to only 26.1% in the pre-COVID-19 period; and (b) exchange rate own shocks explain between 56% to 75% of own exchange rate movements. These results hold in multiple robustness tests. The implication is that exchange rates predict most of their own changes. We confirm this through an economic significance test where we show that the shock spillovers predict exchange rate returns and these predicted exchange rates can be useful in extracting buy and sell trading signals.

How stock markets reacted to COVID-19? Evidence from 25 countries.

The objective of this paper is to analyse how COVID-19 related government policies influenced stock markets. Of the 25 countries we consider, stock returns did not react to any of the three policies - the stimulus package, lockdown, and travel ban in 20% of countries. For around 48% of countries, the effect on returns was negative, due largely to the stimulus package and lockdown policies. Of the 13 countries that experienced a change in the cash rate, returns were negative for 46% of the markets. The travel ban had the least effect on stock returns.

Commentary on a method for testing resistance to shocks.

This note tours the Narayan (2020a: Has COVID-19 Changed Exchange Rate Resistance to Shocks?) approach to testing for resistance of a time-series variable to shocks. We take a step-by-step account of this approach and demonstrate its applicability with respect to the crude oil price.•The approach entails steps (1) to (8), as outline in the paper.•Future researchers will find this method useful in evaluating the resistance of variables to not only COVID-19 shocks but to any shock which has had a sufficiently long life.

Japanese currency and stock market-What happened during the COVID-19 pandemic?

This paper examines the relationship between the Japanese Yen and the country's stock returns. Using several variants of econometric models and empirical specifications, we unravel that the depreciation of the Yen vis-à-vis the US dollar led to gains in Japanese stock returns. A one standard deviation depreciation of the Yen during the COVID-19 period (equivalent to 0.588%) improved stock market returns by 71% of average returns We see that this relationship was stronger over the COVID-19 period (January 2020 to August 2020) compared to the pre-crisis period.

COVID-19 lockdowns, stimulus packages, travel bans, and stock returns.

This paper examines the effect of government responses of G7 countries to the coronavirus pandemic (COVID-19) on stock market returns. Using time-series data, we show that lockdowns, travel bans, and economic stimulus packages all had a positive effect on the G7 stock markets. However, lockdowns were most effective in cushioning the effects of COVID-19. Our results are robust to different measures of returns and controls for other factors of returns.