The impact of the COVID-19 outbreak on the connectedness of the BRICS's term structure.

This study aims to examine the impact of the different waves of the COVID-19 pandemic on the connectedness of the BRICS (Brazil, Russia, India, China, and South Africa) term structure of interest rates and its components (level, slope and curvature). For that purpose, this research applies the time-varying parameter vector autoregression (TVP-VAR) approach in order to assess the direction of spillovers among countries and factors and measure their contribution to the connectedness system. Our results show that the total connectedness measure changes over time, and the level and curvature components show connectedness that persists longer than the slope component, both in the first wave of the COVID-19 pandemic. Brazil and South Africa would appear as net transmitters of shocks, whereas China and India are net receivers. Finally, the most significant differences in the net dynamic connectedness between transmitters and receivers were focused on before and during the first wave of the COVID-19 pandemic crisis. Some additional impacts were observed during the last waves of the coronavirus pandemic. To our best knowledge, this is the first study on the connectedness between the yield curves of the BRICS economies and the COVID-19 crisis uncertainty according to the coronavirus MCI, by decomposing the yield curve into its factors (level, slope, and curvature).

Connectedness between Defi assets and equity markets during COVID-19: A sector analysis.

This paper explores the dynamic connectedness between Defi assets and sector stock markets focused around the COVID-19 pandemic crisis. For that aim, this research applies the TVP-VAR model, and it also computes the optimal weights and hedge ratios for the Defi assets-sector equity portfolios using the DCC-GARCH model. Our main findings reveal that static connectedness is slightly economy- and sector-dependent. Regarding the dynamic connectedness, as expected, the total spillover index changes over time, showing a cruel impact of the global pandemic declaration. Net spillover indices show relevant differences between the Defi assets and certain sectors (net receivers) and sectors such as industrials, materials and information technology (time-varying net transmitters). Finally, the optimal hedge ratios reveal similar levels of coverage in all the periods analyzed, with slight upturns in the cost of such coverage in the crisis period caused by COVID-19.

Government Bonds and COVID-19. An International Evaluation Under Different Market States.

This study evaluates the sensitivity of government bond yields from the countries most affected by the COVID-19 pandemic to variations in some international risk factors during the period between January 2020 and April 2021. This sample period allows us to focus the study on the first, and the subsequent waves of the COVID-19 pandemic. Specifically, we propose an extended risk factor model estimated using the quantile regression approach. In addition, this study compares the COVID-19 pandemic period with a pre-pandemic and a post-vaccination period. Interesting differences among them are observed, remarking that gold is the key risk factor during the pandemic, whereas VIX and crude oil play that role in the pre-pandemic and the post-vaccination periods, respectively, mainly for bearish states. As expected, the explanatory power of the model is better at extreme quantiles, showing relevant differences between sensitivities, because the found effects are quantile-, country- and risk factor-dependent. The results during the pandemic are robust to the inclusion of a country-specific factor and a factor accounting for the mutual influence of the government bonds.

The impact of COVID-19-related media coverage on the return and volatility connectedness of cryptocurrencies and fiat currencies.

This research explores the impact of COVID-19-related media coverage on the dynamic return and volatility connectedness of the three dominant cryptocurrencies (Bitcoin (BTC), Ethereum (ETH) and Ripple (XRP)) and the fiat currencies of the euro, GBP and Chinese yuan. The sample period covers the first and second devasting waves of the COVID-19 pandemic crisis and ranges from January 1, 2020, to December 31, 2020. The dynamic return and volatility connectedness measures are estimated using the time varying parameter-VAR approach. Our return connectedness analysis shows that the media coverage index (only before the first wave) and the cryptocurrencies are the net transmitters of shocks while the fiat currencies are the net receivers of shocks. Similar results are obtained in terms of volatility, except for the euro, which shows a clear net receiver profile in January and February. This fiat currency (the euro) became a net transmitter in March and during the first wave of the COVID-19 crisis, which possibly shows the virulence of the pandemic on the European continent. Moreover, the most relevant differences between the net dynamic (return and volatility) connectedness of these two groups of currencies are focused on the beginning of the sample period, just before the first wave of the SARS-CoV-2 pandemic crisis, although some differences are observed during the first and second waves of the coronavirus outbreak.

Cryptocurrencies and oil price shocks: A NARDL analysis in the COVID-19 pandemic.

This study explores potential non-linear and asymmetric interdependencies between oil price shocks and leading cryptocurrency returns. In addition, this research splits changes in crude oil prices into three relevant components: risk, demand, and supply shocks. By applying the NARDL methodology, this paper examines the connection between oil and cryptocurrencies in the period between November 20, 2018 and June 30, 2020, conducting a study of the first wave of the COVID-19 pandemic. Our results confirm that demand shocks show the greatest connection with the returns of the cryptocurrencies analysed. In addition, both short-term and long-term results show a greater interdependence between oil and cryptocurrencies in periods of economic turbulence, such as the SARS-CoV-2 coronavirus crisis.

Alternative estimates of the well-known negative relationship between the US interest rate risk and the flow-through capability.

This paper estimates US industries' ability to transmit inflation shocks to the prices of their products and services (flow-through capability, FTC) and the stock duration (interest rate sensitivity) at the sector level. Then, considering the significant differences in ability among industries, we analyze the relationship between FTC and interest rate sensitivity using two alternative methodologies (in both cases). Finally, we find a significant negative relationship between FTC and stock duration, as suggested by previous literature. Thus, industries with high FTC, such as S7 (Finance and Real Estate), S9 (Manufacturing), S11 (Transportation and Warehousing) and S12 (Utilities), may be less sensitive (than expected) to changes in nominal interest rates. In contrast, sectors such as S4 (Retail Trade), S8 (Information) and S10 (Professional and Administrative Services) (with high IRS) may be more sensitive (than expected) to changes in nominal interest rates, indicating a weak ability to transmit inflation shocks to the prices of their products and services.

Investor Behavior and Flow-through Capability in the US Stock Market.

This paper analyzes investor behavior depending on the flow-through capability (FTC) in the US stock market, because investors seek protection from inflation rate changes, and the FTC (a firm's ability to transmit inflation shocks to the prices of its products and services) is a key factor in investment decisions. Our estimates of the FTC of firms listed on the US stock exchange at the sector level are significantly different among industries, and we demonstrate a direct relationship between changes in stock prices (at the sector level) and FTC. These results would be relevant because they have important implications on investor behavior.

Interest and Inflation Risk: Investor Behavior.

We examine investor behavior under interest and inflation risk in different scenarios. To that end, we analyze the relation between stock returns and unexpected changes in nominal and real interest rates and inflation for the US stock market. This relation is examined in detail by breaking the results down from the US stock market level to sector, sub-sector, and to individual industries as the ability of different industries to absorb unexpected changes in interest rates and inflation can vary by industry and by contraction and expansion sub-periods. While most significant relations are conventionally negative, some are consistently positive. This suggests some relevant implications on investor behavior. Thus, investments in industries with this positive relation can form a safe haven from unexpected changes in real and nominal interest rates. Gold has an insignificant beta during recessionary conditions hinting that Gold can be a safe haven during recessions. However, Gold also has a consistent negative relation to unexpected changes in inflation thereby damaging the claim that Gold is a hedge against inflation.