The transition of the global financial markets' connectedness during the COVID-19 pandemic

This study contributes to the literature on financial research under the presence of the COVID-19 pandemic. Fresh evidence emerges from using two novel approaches, namely network analysis and wavelet coherence, to examine the connectedness and comovement of financial markets consisting of stock, commodity, gold, real estate investment trust, US exchange, oil, and Cryptocurrency before and during the COVID-19 onset. Moreover, unlike the previous studies, we seek to fill a gap in the literature regarding the ex-post detection of COVID-19 crises and propose the Markov-switching autoregressive model to detect structural breaks in financial market returns. The first result shows that most financial markets entered the downtrend after January 30, 2020, coinciding with the date the World Health Organization (WHO) declared the COVID-19 pandemic as a Public Health Emergency of International Concern. Thus, it is reasonable to use this date as the break date due to COVID-19. The empirical result from network analysis indicates a similar connectedness, or the network structure, in other words, among global financial markets in both the pre-and during COVID-19 pandemic periods. Moreover, we find evidence of market differences as the MSCI stock market plays a central role while Cryptocurrency presents a weak role in the global financial markets. The findings from the wavelet coherence analysis are quite mixed and illustrate that the comovement of the financial markets varies over time across different frequencies. We also find the main and most significant period of coherence and comovement among financial markets to be between December 2019 and August 2020 at the low-frequency scale (>32 days) (middle and long terms). Among all market pairs, the oil and commodity market pair has the strongest comovement in both pre-and during the COVID-19 pandemic phases at all investment horizons.     

Spillover and connectedness among G7 real estate investment trusts: The effects of investor sentiment and global factors

This paper examines the dynamic spillover interconnectedness of G7 Real Estate Investment Trusts (REITs) markets. We use the spillover index of Diebold and Yilmaz (2012), the time-varying parameters vector-autoregression (TVP-VAR) model, and the quantile regression approach. The result show that REITs network connectedness is dynamic and experiences an abrupt increase in the first wave of COVID-19 outbreak (2020Q1). We also observe a substantial abrupt decrease in connectedness during the success of vaccination programs (end 2021). The connectedness among assets is much stronger during COVID-19 than before. The REITs of Japan and Italy are net receivers of spillover and those of US and UK are net transmitters of spillovers before and during COVID-19. Conversely, the REIT of Canada and Germany (France) switches from net receivers (contributors) of spillovers before the pandemic to net contributors (receivers) during the COVID-19. Finally, we show that News Sentiment index, Geopolitical Risk index, Economic Policy Uncertainty index, US Treasury yield, and Stock Volatility index influence the spillover magnitude across quantiles.     

Monetary policy regimes and the term structure of interest rates

US monetary policy is investigated using a regime-switching no-arbitrage term structure model that relies on inflation, output, and the short interest rate as factors. The model is complemented with a set of assumptions that allow the dynamics of the private sector to be separated from monetary policy. The monetary policy regimes cannot be estimated if the yield curve is ignored during estimation. Counterfactual analysis evaluates importance of regimes in policy and shocks for the great moderation. The low-volatility regime of exogenous shocks plays an important role. Monetary policy contributes by trading off asymmetric responses of output and inflation under different regimes.     

The impact of COVID-19 on the G7 stock markets: A time-frequency analysis

We examine the co-movement of the G7 stock returns with the numbers of confirmed COVID-19 cases and causalities based on daily data from December 31, 2019 to November 13, 2020. We employ the wavelet coherence approach to measure the impact of the numbers of confirmed cases and deaths on the G7 stock markets. Our findings reveal that both the number of confirmed COVID-19 cases and the number of deaths exhibit strong coherence with the G7 equity markets, although we find heterogeneous results for the Canadian and Japanese equity markets, in which the numbers of COVID-19 cases and the deaths exhibit only a weak relationship. This evidence is more pronounced in the long-term horizon rather than the short-term horizon. Moreover, the lead-lag relationship entails a mix of lead-lag relations across different countries. We present the implications of these findings for both policymakers and the international investment community.     

Analysis of the impact of COVID-19 pandemic on G20 stock markets

We examine the impact of the COVID-19 pandemic on G20 stock markets from multiple perspectives. To measure the impact of COVID-19 on cross-market linkages and deeply explore the dynamic evolution of risk transmission relations and paths among G20 stock markets, we statically and dynamically measure total, net, and pairwise volatility connectedness among G20 stock markets based on the DY approach by Diebold and Yilmaz (2012, 2014). The results indicate that the total volatility connectedness among G20 stock markets increases significantly during the COVID-19 crisis, moreover, the volatility connectedness display dynamic evolution characteristics during different periods of the COVID-19 pandemic. Besides, we also find that the developed markets are the main spillover transmitters while the emerging markets are the main spillover receivers. Furthermore, to capture the impact of COVID-19 on the volatility spillovers of G20 stock markets, we individually apply the spatial econometrics methods to analyze both the direct and indirect effects of COVID-19 on the stock markets’ volatility spillovers based on the “volatility spillover network matrix” innovatively constructed in this paper. The empirical results suggest that stock markets react more strongly to the COVID-19 confirmed cases and cured cases than the death cases. In general, our study offers some reference for both the investors and policymakers to understand the impact of COVID-19 on global stock markets.     

Animal Behavior in Capital markets: Herding formation dynamics,trading volume,and the role of COVID-19 pandemic

This paper provides new evidence on herding behavior. Using daily frequency data for 336 US listed firms over a five-year period, we investigate three important elements of financial herding behavior. First, trading volume, representing market interest, as a significant variable in capital markets apart from stock prices. Second, herding dynamics since herding formation is a dynamic process. Third, the reaction of possible financial herding to exogenous events-threats, as we use the pandemic event in order to investigate a market under stress. Even though the benchmark herding model used does not provide evidence of herding behavior, our results verify the significance of the above herding elements. We also find that trading volume and positive changes in trading volume result in increased cross-sectional absolute deviation (CSAD). Most importantly, we find that herding behavior is evident during the COVID-19 pandemic confirming that investors tend to herd during major crisis periods.     

Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic

This research empirically evaluates the potential diversification benefits of Gold during the COVID-19 pandemic period, when including it in equity-based asset allocation strategies. This study proposes minimum VaR portfolios, with monthly rebalance and different wavelet scales (short-run, mid-run and long-run), doing both an in-sample and out-of-sample analysis. We find much more unstable weights as the frequency of the decomposition becomes lower, and strong evidence of the outperformance of the mid-run decompositions over the rest of active management strategies and the passive management of buy and hold the variety of single equity indices. Thus, we may shed some light on the role of Gold as a safe haven when properly filtering aggregated data.