This study introduces volatility impulse response functions (VIRF) for dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) models. In addition, the ...implications with respect to network analysis—using the connectedness approach of Diebold and Y
ιlmaz (Journal of Econometrics, 2014, 182(1), 119–134)—is discussed. The main advantages of this framework are (i) that the time‐varying dynamics do not underlie a rolling‐window approach and (ii) that it allows us to test whether the propagation mechanism is time varying or not. An empirical analysis on the volatility transmission mechanism across foreign exchange rate returns is illustrated. The results indicate that the Swiss franc and the euro are net transmitters of shocks, whereas the British pound and the Japanese yen are net volatility receivers of shocks. Finally, the findings suggest a high degree of comovement across European currencies, which has important portfolio and risk management implications.
We investigate the internal and external categorical economic policy uncertainty (EPU) spillovers between the US and Japan using a novel extension of the TVP-VAR connectedness approach of Antonakakis ...and Gabauer (2017). The decomposition of our approach gives us insights about the dynamics with and without international spillovers which has essential policy implications. Our results suggest that monetary policy uncertainty is the main driver, followed by uncertainties associated with fiscal, currency market and trade policies. Furthermore, we find that the Fukushima Daiichi accident can be interpreted as a negative trade shock that spread internationally.
•A novel extension of the dynamic directional connectedness approach is introduced.•Decomposes time-varying spillovers into internal and external connectedness.•We examine categorical policy uncertainty spillovers between Japan and the US.•Monetary policy uncertainty spillovers are most dominant.
In this paper, we show evidence of a dramatic change in the structure and time-varying patterns of return connectedness across various assets (gold, crude oil, world equities, currencies, and bonds) ...around the COVID-19 outbreak. Using the TVP-VAR connectedness approach, the results show that the dynamic total connectedness across the five assets was moderate and quite stable until early 2020. After that, the total connectedness spikes and the structure of the network of connectedness alters, which concurs with the COVID-19 outbreak. The equity and USD indices are the primary transmitters of shocks before the outbreak, whereas the bond index becomes the main transmitters of shocks during the COVID-19 outbreak. However, the USD index is a net receiver of shocks to other assets during the outbreak period. Furthermore, using a recently developed newspaper-based index of uncertainty in financial markets due to infectious diseases to capture the recent impact of COVID-19, we find that connectedness is positively related to this index, and increases at higher levels (conditional quantiles) of connectedness. Overall, our results reflect the speedy disturbing effects of the COVID-19 outbreak, which matters to the formulations of policies seeking to achieve financial stability. The results also indicate a possibility to threaten investors’ portfolios and fade the benefits of diversification.
•Return connectedness across various assets around the COVID-19 outbreak are analyzed.•A TVP-VAR-based connectedness is stable until early 2020, and spikes with the COVID-19 outbreak.•Equity and USD indices are primary transmitters before the outbreak.•Bond index becomes the main transmitter and USD index net receiver after the COVID-19 outbreak.•Connectedness is positively related to an index of financial uncertainty from infectious diseases.
This study introduces a novel time-varying parameter vector autoregression (TVP-VAR) based extended joint connectedness approach in order to characterize connectedness of 11 agricultural commodity ...and Crude Oil futures prices spanning from July 1, 2005 to May 1, 2020. Our results reveal that the system-wide dynamic connectedness is heterogeneous over time and driven by economic events. Peaks have been reached during the Global Financial Crisis, European Governmental Debt Crisis, and the COVID-19 pandemic. Further findings show that commodities such as Crude Oil, Grains, Livestock, Sugar, and Soybean Oil tend to be the main net transmitters of shocks while Corn, Lean Hogs, Soybeans, Cattle, and Wheat are the main receivers of shocks. Pairwise connectedness on the other hand shows that Crude Oil not only affects other commodity markets, but is also equally responsive to innovations that take place in most of these markets explaining the high interconnectedness of the network. Finally, we illustrate the importance of the chosen normalization technique employed in the connectedness framework as the retrieved findings have important implications for investors to design strategies for optimization of portfolio and asset allocation, reduction in downside risk along with hedging strategies. The full implementation and replication code is available at: https://github.com/GabauerDavid/ConnectednessApproach.
•Introduce a novel TVP-VAR-based extended joint connectedness approach.•Return transmission mechanism across Crude Oil and 11 agricultural commodities is investigated.•Crude Oil, Grains, Livestock, Sugar, and Soybean Oil are the main net transmitters of shocks.•Corn, Lean Hogs, Soybeans, Cattle, and Wheat are the main receivers of shocks.•Crude Oil not only affects commodity assets but is also equally responsive to their innovations.
In this study, we enhance the dynamic connectedness measures originally introduced by Diebold and Yılmaz (2012, 2014) with a time-varying parameter vector autoregressive model (TVP-VAR) which ...predicates upon a time-varying variance-covariance structure. This framework allows to capture possible changes in the underlying structure of the data in a more flexible and robust manner. Specifically, there is neither a need to arbitrarily set the rolling-window size nor a loss of observations in the calculation of the dynamic measures of connectedness, as no rolling-window analysis is involved. Given that the proposed framework rests on multivariate Kalman filters, it is less sensitive to outliers. Furthermore, we emphasise the merits of this approach by conducting Monte Carlo simulations. We put our framework into practice by investigating dynamic connectedness measures of the four most traded foreign exchange rates, comparing the TVP-VAR results to those obtained from three different rolling-window settings. Finally, we propose uncertainty measures for both TVP-VAR-based and rolling-window VAR-based dynamic connectedness measures.
We investigate 1-year interest rate swaps on USD, EUR, JPY and GBP between 2005 and 2020 utilising a quantile connectedness model. This approach allows for a nuanced investigation of connectedness ...and adds to understanding the monetary policy transmission mechanism within a highly integrated international financial system. Substantial interest rate changes (in either direction) matter for connectedness in financial markets. The results also indicate which currency drives developments depending on the direction of the change in interest rates. The full implementation and replication code — based on R, is available at: https://github.com/GabauerDavid/ConnectednessApproach.
•We study connectedness in IRS markets and include a magnitude dimension.•Large positive or negative interest rate changes increase connectedness.•Substantial variations are observed across major markets and over time.•The results have implications for the monetary transmission mechanism.
Economic uncertainty has attracted a significant part of the modern research in economics, proving to be a significant factor for every economy. In this study, we focus on the transmission channel of ...uncertainty between developed economies, examining potential spillover effects between the U.S., the E.U., the U.K, Japan and Canada. Within a time-varying framework our empirical results indicate of a significant spillover of uncertainty from the E.U. to the U.S.
This study has been inspired by the emergence of socially responsible investment practices in mainstream investment activity as it examines the transmission of return patterns between green bonds, ...carbon prices, and renewable energy stocks, using daily data spanning from 4th January 2015 to 22nd September 2020. In this study, our dataset comprises the price indices of S&P Green Bond, Solactive Global Solar, Solactive Global Wind, S&P Global Clean Energy and Carbon. We employ the TVP-VAR approach to investigate the return spillovers and connectedness, and various portfolio techniques including minimum variance portfolio, minimum correlation portfolio and the recently developed minimum connectedness portfolio to test portfolio performance. Additionally, a LASSO dynamic connectedness model is used for robustness purposes. The empirical results from the TVP-VAR indicate that the dynamic total connectedness across the assets is heterogeneous over time and economic event dependent. Moreover, our findings suggest that clean energy dominates all other markets and is seen to be the main net transmitter of shocks in the entire network with Green Bonds and Solactive Global Wind, emerging to be the major recipients of shocks in the system. Based on the hedging effectiveness, we show that bivariate and multivariate portfolios significantly reduce the risk of investing in a single asset except for Green Bonds. Finally, the minimum connectedness portfolio reaches the highest Sharpe ratio implying that information concerning the return transmission process is helpful for portfolio creation. The same pattern has been observed during the COVID-19 pandemic period.
This paper investigates the volatility spillovers and co-movements among oil prices and stock prices of major oil and gas corporations over the period between 18th June 2001 and 1st February 2016. To ...do so, we use the spillover index approach by Diebold and Yilmaz (2009, 2012, 2014, 2015) and the dynamic correlation coefficient model of Engle (2002) so as to identify the transmission mechanisms of volatility shocks and the contagion of volatility among oil prices and stock prices of oil and gas companies, respectively. Given that volatility transmission across oil and major oil and gas corporations is important for portfolio diversification and risk management, we also examine optimal weights and hedge ratios among the aforementioned series. Our results point to the existence of significant volatility spillover effects among oil and oil and gas companies' stock volatility. However, the spillover is usually unidirectional from oil and gas companies' stock volatility to oil volatility, with BP, CHEVRON, EXXON, SHELL and TOTAL being the major net transmitters of volatility to oil markets. Conditional correlations are positive and time-varying, with those between each of the aforementioned companies and oil being the highest. Finally, the diversification benefits and hedging effectiveness based on our results are discussed.
•We examine the volatility correlations and spillover effects between WTI and oil & gas firms.•We employ a firm-level approach which is useful for portfolio investments and risk management.•Correlations are impacted by global economic events, as well as, firm-specific events.•WTI is a net receiver of spillover shocks to oil and gas firms' volatility.•Optimal portfolio weights strategy is more effective than the optimal hedge ratio strategy.
•Spillovers of financial, macroeconomic and real estate uncertainties analyzed.•TVP-VAR model is used.•Spillovers vary over time.•In general, financial uncertainty dominates the other two ...uncertainties.•Role of macroprudential policies are highlighted.
We investigate the spillover across real estate (REU), macroeconomic (MU) and financial uncertainties (FU) in the United States based on monthly data covering the period of July, 1970 to December, 2017. To estimate the propagation of uncertainties across the sectors, a time-varying parameter vector autoregression (TVP-VAR)-based connectedness procedure has been applied. In sum, we show that that since the 1970s, FU has been the main transmitter of shocks driving both, MU and REU, with MU dominating the REU. Our results support the need for better macroprudential policy decisions.
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