ABSTRACT
The paper examines the dynamic spillover among traditional currencies and cryptocurrencies before and during the COVID-19 pandemic and investigates whether economic policy uncertainty (EPU) impacts this spillover. Based on the TVP-VAR approach, we find evidence of spillover effects among currencies, which increased widely during the pandemic. In addition, results suggest that almost all cryptocurrencies remain as "safe-haven" tools against market uncertainty during the COVID-19 period. Moreover, comparative analysis shows that the total connectedness for cryptocurrencies is lower than for traditional currencies during the crisis. Further analysis using quantile regression suggests that EPU exerts an impact on the total and the net spillovers with different degrees across currencies and this impact is affected by the health crisis. Our findings have important policy implications for policymakers, investors, and international traders.
ABSTRACT
Understanding the interactions among climate change, carbon emission allowance trading, crude oil and renewable energy stock markets, especially the role of climate change in this system is of great significance for policy makers, energy producers/consumers and relevant investors. The present paper aims to quantify the time-varying connectedness effects among the four factors by using the TVP-VAR based extensions of both time- and frequency-domain connectedness index measurements proposed by Antonakakis et al. (2020) and Ellington and Barunik (2021) [8,48]. The empirical results suggest that, firstly, the average total connectedness among climate change, carbon emission allowance trading, crude oil and renewable energy stock markets is not so strong for the heterogenous fundamentals underlying them. Nevertheless, the time-varying total connectedness fluctuates fiercely through May 2005 to September 2021, varying from about 8% to 30% and rocket to very high levels during the global subprime mortgage crisis and the COVID-19 pandemic. Furthermore, the total connectedness mainly centers on the short-term frequency, i.e., 1–3 months. Secondly, climate change is generally the leading information contributor among the four factors, although not particularly strong, and its leading role also performs mainly on the short-term frequency (1–3 months). Thirdly, renewable energy stock market and crude oil market show tight interactions between them and they are the two major bridges of information exchanges across various time frequencies (horizons) in this system. Finally, we confirm the evidence that the primary net connectedness contributor and receiver switch frequently across different time frequencies, implying that it is extremely essential for policy makers, energy producers/consumers and investors to make time-horizon-specific regulatory, production/purchasing or investment decisions when facing the uncertain effects of climate change on the interactions among carbon emission allowance, crude oil and renewable energy stock markets. © 2022 Elsevier Ltd
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Based on a Structural VAR approach, we estimated fiscal multipliers for social benefits in Brazil for 1997–2018. Our results suggest that social benefits have relatively large multiplier effects, even when compared to public investment. The multipliers are also larger in the full sample, which includes the country's 2014–16 economic crisis than in the period 1997–2014. In particular, our results show that spending one unit on social expenditures generates a final change in GDP of almost three after two years. The higher estimated multipliers in the full sample appear in the response of household consumption and private investment to shocks in total social expenditures and for different types of social benefits (e.g. cash transfers, unemployment insurance, and pensions). In a context in which the expansion of social protection became prominent as a response to structural changes in the labor market and the Covid-19 pandemic, our paper reinforces its potential role in the short-run economic recovery. © 2022 Informa UK Limited, trading as Taylor & Francis Group.
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PurposeThis paper examines the time-varying return connectedness between renewable energy, oil, precious metals, the Gulf Council Cooperation region and the United States stock markets during two successive crises: the pandemic Covid-19 and the 2022 Russo-Ukrainian war. The main objective is to investigate the effect of the Covid-19 pandemic and the Russo-Ukrainian war on the connectedness between the considered stock markets. Design/methodology/approachThis paper uses the time-varying parameter vector autoregression approach, which represents an extension of the Spillover approach (Diebold and Yilmaz, 2009, 2012, 2014), to examine the time-varying connectedness among stock markets. FindingsThis paper reflects the effect of the two crises on the stock markets in terms of shock transmission degree. We find that the United States and renewable energy stock markets are the main net emitters of shocks during the global period and not just during the two considered crises sub-periods. Oil stock market is both an emitter and a receiver of shocks against Gulf Council Cooperation region and United States markets during the full sample period, which may be due to price fluctuation especially during the two crises sub-periods, which suggests that the future is for renewable energy. Originality/valueThis paper examines the effect of the two recent and successive crises, the Covid-19 pandemic and the 2022 Russo-Ukrainian war, on the connectedness among traditional stock markets (the United States and Gulf Council Cooperation region) and commodities stock markets (renewable energy, oil and precious metals).
ABSTRACT
Amid the faster- and wider-than-expected spread of COVID-19, which has added new twists to the global economic outlook and profoundly impacted the performance of major currencies around the world, the RMB has been performing well, and thus, its market standing has improved. However, uncertainties about the future pose enormous challenges to the RMB internationalization. By processing 30-min high-frequency data, this paper aims to study changes in the characteristics of the relationship between the RMB and other non-USD currencies at five stages of the pandemic, first by means of auxiliary regression analysis, in which the pandemic is accounted for with a dummy variable, and then with a VAR-BEKK-GARCH model. The research shows that since the latter stages of the global pandemic, significant negative spillover effects among major non-USD currencies can be observed, while the independence of offshore RMB has increased gradually, and there have been weakening trends in the sustainability of the mean spillover and volatility spillover effects among other currencies. As the "regular pandemic prevention and control” begins to take hold in China and the geopolitical uncertainty increasingly outbreaks, the top priority in global currency market should be to resist the pressure of RMB independence with policy changes and increase caution in investing RMB assets. © 2022 Elsevier Inc.
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The paper investigates the volatility spillover across China's carbon emission trading (CET) markets using the connectedness method based on the quantile VAR framework. The non-linear result shows strong volatility spillover effects in upper quantiles, resulting from major economic and political events. This is in accordance with the risk contagion hypothesis that volatility of carbon price returns is affected by the shocks of economic fundamentals and spills over to other pilots. Guangdong and Shanghai are the most significant contributors to volatility transmission because of their high liquidity and active markets. Hubei CET pilot has shifted from transmitter to receiver since the COVID-19 pandemic. Regarding the pairwise directional connectedness, geographical location and similar market attribute also matter in volatility transmission. This provides implications for policymakers and investors to attach importance to risk management given the quantile-based method rather than the average shocks. © 2023 Elsevier B.V.
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This study investigates the impacts of crude oil-market-specific fundamental factors and financial indicators on the realized volatility of West Texas Intermediate (WTI) crude oil price. A time-varying parameter vector autoregression model with stochastic volatility (TVP-VAR-SV) is applied to weekly data series spanning January 2008 to October 2021. It is found that the WTI oil price volatility responds positively to a shock in oil production, oil inventories, the US dollar index, and VIX but negatively to a shock in the US economic activity. The response to the EPU index was initially positive and then turned slightly negative before fading away. The VIX index has the most significant effect. Furthermore, the time-varying nature of the response of the WTI realized oil price volatility is evident. Extreme effects materialize during economic recessions and crises, especially during the COVID-19 pandemic. The findings can improve our understanding of the time-varying nature and determinants of WTI oil price volatility. © 2022
ABSTRACT
Our article employs a quantile vector autoregression (QVAR) to identify the connectedness of seven variables from April 1, 2019, to June 13, 2022, in order to examine the relationships between crypto volatility and energy volatility. Our findings reveal that the dynamic connectedness is approximately 25% in the short term and approximately 9% in the long term. The 50% quantile equates to the overall average connectedness of the entire period, according to dynamic net total directional connectedness over a quantile, which also indicates that connectedness is very intense for both highly positive changes (above the 80% quantile) and crypto and energy volatility (below the 20% quantile). With the exception of the early 2022 period when the Crypto Volatility Index transmits a net of shocks because of the Ukraine-Russia Conflict, dynamic net total directional connectedness implies that in the short term, the Crypto Volatility Index acts as a net shock receiver across time. While this indicator is a net shock receiver for long-term dynamics, wind energy is a net shock transmitter during the short term. Green bonds are a short-term net shock receiver. This role is valid in the long term. Clean energy and solar energy are the long-term net transmitters of shocks;nevertheless, the series is always and only momentarily a net receiver of shocks because of the short-term dynamics. Natural gas and crude oil play roles in both two quantiles. Dynamic net pairwise directional connectedness over a quantile suggests that uncertain events like the COVID-19 epidemic or Ukraine-Russia Conflict influence cryptocurrency volatility and renewable energy volatility. © 2022 Elsevier Ltd
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Policymakers imposed constraints on public life to contain the Covid-19 pandemic. At the same time, fiscal, monetary and macroprudential policies implemented a large range of expansionary measures to limit the economic consequences of the pandemic and stimulate recovery. In this paper, we assess the response of the equity market as a high-frequency indicator of economic activity to containment and stabilization policies for 29 European economies. We construct indicators of containment and stabilization policies and estimate a range of panel VAR models. The main results are threefold. First, we find that stock markets are highly responsive to containment and stabilization policies. We show that domestic fiscal policy, macroprudential policy as well as monetary policy support the recovery as reflected in the stock market. Second, expansionary fiscal policy conducted at the European level reduces rather raises stock prices. Third, we estimate the model over subsamples and show that the counter-intuitive stock market response to EU policies is driven by the responses in medium- and high-debt countries. These countries' stock markets are also particularly susceptible to monetary policy announcements. © 2022 CEPII (Centre d'Etudes Prospectives et d'Informations Internationales), a center for research and expertise on the world economy
ABSTRACT
This paper examines the dynamic connectedness among the implied volatilities of oil prices (OVX) and fourteen other assets, which can be grouped into five different assets classes (i.e., energy commodities, stock markets, precious metals, exchange rates and bond markets). To do so we estimate a recently developed time-varying parameter vector autoregressive (TVP-VAR) connectedness approach using daily data spanning from March 16th, 2011 to March 3rd, 2021 — covering the first year of the COVID-19 pandemic. The empirical results suggest that connectedness across the different asset classes and oil price implied volatilities are varying over time and fluctuate at very high levels. The dynamic total connectedness ranges between 65% and 85% indicating a high degree of cross-market risk linkages. Furthermore, we find that the oil market is becoming more integrated with the financial markets, since it tends to be materially impacted by abrupt fluctuations of the global financial markets' volatilities. More specifically, the analysis shows that, throughout the period, OVX is a net receiver of shocks to the remaining implied volatilities. Finally, the net pairwise connectedness measures suggest that OVX is constantly at the net receiving end vis-a-vis the majority of the asset classes' implied volatilities. Those findings are of major importance for portfolio and risk management in terms of asset allocation and diversification. © 2022 The Author(s)
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We document the impact of COVID-19 on inflation modelling within a vector autoregression (VAR) model and provide guidance for forecasting euro area inflation during the pandemic. We show that estimated parameters are strongly affected, leading to different and sometimes implausible projections. As a solution, we propose to augment the VAR by allowing the residuals to have a fat-tailed distribution instead of a Gaussian one. This also outperforms with respect to unconditional forecasts. Yet, what brings sizeable forecast gains during the pandemic is adding meaningful off-model information, such as that entailed in the Survey of Professional Forecasters. The fat-tailed VAR loses part, but not all of its relative advantage compared to the Gaussian version when producing conditional inflation forecasts in a real-time setup. It is the joint fat-tailed errors and multi-equation modelling that manage to robustify models against extreme observations; in a single-equation model the same solution is less effective.
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This paper examines the static and dynamic return and volatility connectedness among Islamic equity indices and a Coronavirus coverage index over the ongoing COVID-19 pandemic crisis. We employ ten major sectoral equity indices covering main economic sectors and the Coronavirus media coverage index (MCI) and apply the time-varying parameter vector autoregressive methodology (TVP-VAR). The results show a high degree of connectedness between the return and volatility series of the different sectoral indices. Moreover, the information transmission between these indices and the media coverage index shows that Islamic equities are net receivers of shocks from the coronavirus MCI. Additionally, we investigate the causality between the different connectedness measures and the Economic Policy Uncertainty (EPU). Our results indicate that EPU has predictive power on the net connectedness between the Islamic sectoral equities and the Coronavirus MCI. © 2022 Elsevier B.V.
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This study aims to examine whether life insurance futures can serve as a hedge against the COVID-19 pandemic and whether they have the characteristics of a safe haven under the impact of the health shocks of the COVID-19 pandemic. We chose three life insurance stock futures in India and one in Taiwan as samples, including the market index of the two countries and the number of confirmed COVID-19 cases as sample variables. We used the growth rate of COVID-19 cases as the threshold variable, estimated the asymmetric threshold vector autoregression model, and found that insurance futures in the regime with a significant growth rate of confirmed COVID-19 cases can hedge against COVID-19 risks; therefore, insurance futures are a safe haven for the market. We further estimated the time-varying parameter vector autoregression model, and the impulse response results showed that insurance futures are a safe haven for COVID-19 pandemic risks.
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This article explores the impact of fuel price movements on the stock market return of 2020 during the COVID-19 disruptions. In doing so, a monthly data of seven selected stock market indices representing developed and emerging economies globally was used for analysis. The study used a time-varying parameter VAR model to examine a time-varying causal association between oil prices and stock market returns and a novel quantile-causality approach to capture the fluctuations of these markets under COVID-19's varying market conditions. The study further utilises the entropy transfer approach to capture the Granger-causal relationship in the presence of nonlinearities of the data series. The results indicate a high information flow from fuel prices to the FTSE-100, Pacific, and European stock indicies, but not the other way round. The results show that, for the FTSE-100 and the European region, there is a two-way information flow between equities and natural gas, and vice-versa. However, a one-way information flow was established from the stock market to the Pacific and emerging economies.