1,721,004 research outputs found
“Ubiquitous uncertainties”: spillovers across economic policy uncertainty and cryptocurrency uncertainty indices
No full textPurpose The purpose of this paper is to extend the literature on the spillovers across economic policy uncertainty (EPU) and cryptocurrency uncertainty indices. Design/methodology/approach This paper uses cross-country economic policy uncertainty indices and the novel data measuring the cryptocurrency price uncertainties over the period 2013-2021 to construct a sample of 946 observations and applies the time-varying parameter vector autoregression (TVP-VAR) model to do an empirical study. Findings The findings suggest that there are cross-country spillovers of economic policy uncertainty. In addition, the total uncertainty spillover between economic policies and cryptocurrency peaked in 2015 before gradually decreasing in the following periods. Concomitantly, the cryptocurrency uncertainty has acted as the "receiver." More importantly, the authors found the predictive power of economic policy uncertainty to predict the cryptocurrency uncertainty index. This paper's results hold robust when using alternative measurement of cryptocurrency policy uncertainty. Originality/value This study is the first research that deeply investigates the association between two uncertainty indicators, namely economic policy uncertainty and the cryptocurrency uncertainty index. We provide fresh evidence about the dynamic connectedness between country-level economic policy uncertainty and the cryptocurrency index. Our work contributes a new channel driving the variants of uncertainties in the cryptocurrency market
The impact of biodiversity score on the European firm’s performance
No full textThis study aims to contribute to the corporate-environment nexus by investigating the impact of biodiversity scores on firms’ financial performance. Employing a panel model applied to 36 European firms, we find a positive and statistically significant relationship between the Biodiversity Impact Reduction Score and financial performance and firm value. These findings highlight the financial advantages of effective biodiversity management, improving operational efficiency and strengthening investor confidence. Our results offer useful insights for both corporate decision-makers and the academic community, shedding light on the economic implications of biodiversity-related risk
The Time-Spatial Dimension of Eurozone Banking Systemic Risk
No full textIn this paper, we measure the systemic risk with a novel methodology, based on a “spatial-temporal” approach. We propose a new bank systemic risk measure to consider the two components of systemic risk: cross-sectional and time dimension. The aim is to highlight the “time-space dynamics” of contagion, i.e., if the CDS spread of bank i depends on the CDS spread of other banks. To do this, we use an advanced spatial econometrics design with a time-varying spatial dependence that can be interpreted as an index of the degree of cross-sectional spillovers. The findings highlight that the Eurozone banks have strong spatial dependence in the evolution of CDS spread, namely the contagion effect is present and persistent. Moreover, we analyse the role of the European Central Bank in managing contagion risk. We find that monetary policy has been effective in reducing systemic risk. However, the results show that systemic risk does not imply a policy intervention, highlighting how financial stability policy is not yet an objective
Tail risk connectedness in clean energy and oil financial market
No full textThis research investigates the connectedness and the tail risk spillover between clean energy and oil firms, from January 2011 to October 2021. To this, we use the Tail-Event driven NETworks (TENET) risk model. This approach allows for a measurement of the dynamics of tail-risk spillover for each sector and firm. Hence, we can provide a detailed picture of the existing extreme relationships within these markets. We find that the total connection between the markets varies during the period analysed, showing how the uncertainty in oil price plays a critical role in the risk dynamics for oil companies. Also, we find that relationships between energy firms tend to be intrasectoral; that is, each sector receives (emits) risk from (to) itself. These results can have important practical implications for risk management and policymakers
Tail Risk and Extreme Events: Connections between Oil and Clean Energy
Full text linkDo tail events in the oil market trigger extreme responses by the clean-energy financial market (and vice versa)? This paper investigates the relationship between oil price and clean-energy stock with a novel methodology, namely extreme events study. The aim is to investigate an asymmetry effect between the response to good versus bad days. The results show how the two markets influence each other more negatively, i.e., extreme negative events significantly impact the other market. Furthermore, we document how the impact of the shock transmitted by oil prices to clean-energy stocks is less than the amount of shock transmitted oppositely. These findings have important implications for investor and renewable energy policies
Smart Beta Allocation and Macroeconomic Variables: The Impact of COVID-19
Full text linkSmart beta strategies across economic regimes seek to address inefficiencies created by market-based indices, thereby enhancing portfolio returns above traditional benchmarks. Our goal is to develop a strategy for re-hedging smart beta portfolios that shows the connection between multi-factor strategies and macroeconomic variables. This is done, first, by analyzing finite correlations between the portfolio weights and macroeconomic variables and, more remarkably, by defining an investment tilting variable. The latter is analyzed with a discriminant analysis approach with a twofold application. The first is the selection of the crucial re-hedging thresholds which generate a strong connection between factors and macroeconomic variables. The second is forecasting portfolio dynamics (gain and loss). The capability of forecasting is even more evident in the COVID-19 period. Analysis is carried out on the iShares US exchange traded fund (ETF) market using monthly data in the period December 2013–May 2020, thereby highlighting the impact of COVID-19
European bank credit risk transmission during the credit Suisse collapse
No full textThe effect of Credit Suisse collapse on the credit risk spillover across banks is understudied and unclear. Using the tail-event and network dynamics framework on weekly data covering 15 large European banks from March 11, 2020 to March 28, 2023, we show that the credit risk has a strong spillover effect on major banks, increasing systemic risk significantly after the collapse of Credit Suisse. This is notable for non-EU (Swiss and UK) banks in the post-collapse era. The findings are useful for policymakers and regulators concerned with contagious credit risk and the stability of the banking sector under extreme events
Tail risk connectedness in clean energy and oil financial market
No full textThis research investigates the connectedness and the tail risk spillover between clean energy and oil firms, from January 2011 to October 2021. To this, we use the Tail-Event driven NETworks (TENET) risk model. This approach allows for a measurement of the dynamics of tail-risk spillover for each sector and firm. Hence, we can provide a detailed picture of the existing extreme relationships within these markets. We find that the total connection between the markets varies during the period analysed, showing how the uncertainty in oil price plays a critical role in the risk dynamics for oil companies. Also, we find that relationships between energy firms tend to be intrasectoral; that is, each sector receives (emits) risk from (to) itself. These results can have important practical implications for risk management and policymakers
Clean energy indices and brown assets: an analysis of tail risk spillovers through the VAR for VaR model
No full textThis paper studies the dependence between the clean energy markets and brown assets (oil and Bitcoin) over the years 2011–2019. For this purpose, we use the VAR for VaR framework to capture the extreme dependence (tail risk). Moreover, we compute the Granger-causality in risk to study the impact of the Paris Agreement on these markets. We provide novel evidence of the relationship between the clean and oil markets. Notably, the results suggest that they are highly integrated in terms of risk spillover: their lagged returns, risks and extreme events influence both the VaRs of the clean energy sector and oil prices. Additionally, there is a symmetrical and an asymmetrical effect between returns and risks depending on market condition (downside/upside). The focus on the Paris Agreement demonstrates that this event is not neutral concerning the risk transmission. The effects of spillover from oil to clean energy are present before the agreement, while afterwards, we do not find evidence. Finally, the findings provide fresh insights into the relationship between clean energy and Bitcoin. The empirical analysis shows a significant spillover effect of extreme events between the two markets, suggesting a possible substitution effect
The “Donald” and the market: Is there a cointegration?
No full textThis paper analyses the relationship between post-election main sentiment on Donald Trump and financial markets. The sample period, spans from 8 November (the election Day) and 28 February. Our study intends to verify if there exist a co-implication between Trump's Favorable (TF), namely the percentage of favorable opinions on Trump, and some financial variables (i.e. stock and Treasury returns, currency and commodities). The results of cointegration analysis show that Trump's Favorable has explanatory power for stock market returns, 10 long term Treasury bond and decrease of gold. Furthermore, we found no evidence of the opposite relation
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