Could Cryptocurrency Policy Uncertainty Facilitate US Carbon Neutrality?

Investigating the essential impact of the cryptocurrency market on carbon emissions is significant for the U.S. to realize carbon neutrality. This exploration employs low-frequency vector auto-regression (LF-VAR) and mixed-frequency VAR (MF-VAR) models to capture the complicated interrelationship between cryptocurrency policy uncertainty (CPU) and carbon emission (CE) and to answer the question of whether cryptocurrency policy uncertainty could facilitate U.S. carbon neutrality. By comparison, the MF-VAR model possesses a higher explanatory power than the LF-VAR model;the former's impulse response indicates a negative CPU effect on CE, suggesting that cryptocurrency policy uncertainty is a promoter for the U.S. to realize the goal of carbon neutrality. In turn, CE positively impacts CPU, revealing that mass carbon emissions would raise public and national concerns about the environmental damages caused by cryptocurrency transactions and mining. Furthermore, CPU also has a mediation effect on CE;that is, CPU could affect CE through the oil price (OP). In the context of a more uncertain cryptocurrency market, valuable insights for the U.S. could be offered to realize carbon neutrality by reducing the traditional energy consumption and carbon emissions of cryptocurrency trading and mining.

Bitcoin and money supply relationship: An analysis of selected country economies

Bitcoin has become quite known after the 2008 economic crisis and the COVID-19 health crisis. For some, these cryptocurrencies constitute rebellion against the existing system as governments encourage uncontrolled expansions in the money supply;for some others, it is a quick source of income. Undeniably, the volume of the crypto money market has grown considerably in recent years, regardless of the reasoning of the people who invest and trade in this field. At this point, one of the most important questions to be investigated is "what variables have caused the tremendous growth in the crypto money quantities in recent years?" This study tests the assumption that changes in cryptocurrencies are affected by changes in national currencies. Thus, the Bitcoin price is the dependent variable, and M1 monetary supply changes in the USA, European Union and Japanese economies are considered independent variables. The variables in this study were tested using the time-varying Granger causality method. The results obtained from this study confirm the philosophy of Bitcoin's emergence and the possibility that it can be a hedge against the inflationary effects of money, especially after the COVID-19 pandemic.

Íkiz Açık Hipotezi Türkiye'de Geçerliliği: Zamanla Değişen Nedensellik Analizi

Finansal ve ekonomik istikrarın sürdürülebilirliği açısından iç ve dış dengenin birlikte sağlandığı maliye politikalarının uygulanması son derece önem arz etmektedir. Bu nedenle, cari işlemler ile bütçe açıkları arasındaki ilişkinin incelenmesi politika yapıcılar, araştırmacılar ve ekonomistler arasında tartışılan önemli konulardan biri haline gelmiştir. Bu kapsamda, çalışmada Türkiye için Ocak 1998 – Aralık 2021 döneminde ikiz açık hipotezi, Granger nedenselliğin geçici istikrarını yeniden değerlendirmek amacıyla kullanılan yinelemeli algoritmalar kullanılarak araştırılmaktadır. Zamanla değişen Granger nedensellik analizden elde edilen bulgular, Türkiye'de ele alınan dönemde cari işlemler dengesi ve bütçe açığı arasında çift yönlü bir nedensellik ilişkisi olduğunu ortaya koymaktadır. Bu sonuç, Türkiye'de ikiz açık hipotezinin geçerli olduğunu ifade etmektedir. Aynı zamanda, nedensellik ilişkisinde anlamlı geçici değişimlerin olduğu gözlenmektedir. Seçim ve kriz dönemlerinde ikiz açık hipotezinin varlığı mevcut iken, 2002-2008 ve 2015-2021 dönemlerinde cari işlemler hedeflemesi politikası uygulanmaktadır. COVID-19 pandemisi döneminde ise, cari işlemler dengesi ve bütçe açığı arasında çift yönlü asimetrik aktarım mekanizmasının işlediği ifade edilebilir.Alternate :Implementing fiscal policies to ensure domestic and foreign balances together is of vital importance to sustain financial and economic stability. Therefore, investigating the relationship between budget deficit and current account deficit is one of the issues debated by popolicymakersnd economists. In this context, the existence of the win deficit hypothesis in Turkey is researched through recursive algorithms used to revaluate the temporal stability of Granger causality for the periods of January 1998-December 2021. The findings from time-varying Granger causality analysis reveal the existence of a bidirectional causality relationship between budget deficit and current account deficit. This result means the validity of the twin deficit hypothesis in Turkey. Also, the temporal changes in the so-called casualty relationships are observed significantly. During the electoral and crisis periods there is the existence of the twin deficit hypothesis wthe hileaccountnt acount targeting policy is implemented during the periods of 2002-2008 and 2015-2021. In the COVID-19 period, a bidirectional asymmetric transmission mechanism between budget deficit andcurrentt account deficit is worked can be stated.

The Granger Causality of Bahrain Stocks, Bitcoin, and Other Commodity Asset Returns: Evidence of Short-Term Return Spillover before and during the COVID-19 Pandemic

This study examines the tendency of short-term return spillover across Bahrain stocks, bitcoin, and other commodity assets factoring in the dynamic effect of the COVID-19 pandemic. The study employed vector autoregression (VAR) model using the daily returns of Bahrain All Shares Index, bitcoin, crude oil, and gold futures from January 2018 to March 2022. The results showed a persistent unidirectional short-term spillover of return from the Bahrain stock market to the futures gold market for both the period before and during the pandemic. Moreover, the results also showed that the significant positive shock in the bitcoin returns as granger-caused by the returns of the Bahrain stock market is only during the period before the pandemic. Finally, a significant negative contemporaneous short-term effect on the crude oil market returns can be statistically explained by the shocks in the Bahrain stock market only during the COVID-19 period. © 2023 IGI Global. All rights reserved.

Sánchez Arévalo, J. L., Moreira de Sousa, G., & Malta Meurer, R. (2022). Causal effect between the Ibovespa stock market and Shanghai, S&P500, Merval and Nikkei indicators. Cuadernos de Economía

This paper analyzes the causal relationship between the Brazilian stock market indicator and other stock exchange indicators. Specifically, the study time incorporates the world crisis caused by the covid-19 and the war over the price of oil. Were used the differentiated series considering the existence of a unit root, the VAR and Granger Causality models were subsequently estimated. The results show that the causality between the Ibovespa with the S&P500 and Nikkei is bidirectional. These results are consistent when relating the degree of commercial exchange and the origin of foreign investment in Brazil. © 2023, Cuadernos de Economia (Colombia). All Rights Reserved.

Global Systemic Risk Dynamic Network Connectedness during the Covid-19: Evidence from Nonlinear Granger Causality

This study examined the global systemic risk network connectedness during the COVID-19 pandemic by focusing on the stock, bond, and foreign exchange markets of 14 countries (2000–2021). We found that the commonality among multiple markets was high, while the systemic risk of COVID-19 was smaller than that of the 2007–2008 financial crisis. Additionally, the exposure of bond markets to systemic risk was larger than the exchange rate and stock markets. Although the stock and bond markets were the main sources of risk during the pandemic, the foreign exchange market had the strongest connection with the global financial network.

Stock Market Response to Covid-19 Pandemic Period In Asian Equity Markets: An Event Study

The purpose of the study was to evaluate the relationshi ps between factors and the variability of Asian Emerging Stock Markets for the time before, during, and following the COVID 19 Outbreak. Descriptive, ADF Test, GARCH (1.1) Model, and Pair-wise Granger Causality Test were used in the research. From the outcomes of empirical analysis, the study found that the information about the COVID 19 Pandemic played a major role in the movement of Asian emerging countries, stock markets. But the fear of a COVID 19 pandemi c exerci sed mi xed i mpact on t he count ry' s market performance. As a result, while investing in the stock markets, the i nvest or shoul d keep a keen wat ch on market movements. International stock market investors in particular, should watch numerous worldwide events, for a sound investment in the global stock markets. © Indian Institute of Finance.

Reinvestigating the Co-Movements between Stock Market and Exchange Rates: An Augmented Vector Autoregression Analysis

Empirical works on the stock market exchange rate nexus remain scanty in the managed floating exchange rate environment like Nigeria. Thus, our paper contributes to the scanty literature by analyzing how the COVID19 pandemic shapes the existing link in the oil-rich countries like Nigeria using a time series approach based on daily data spanning between 2017 and 2021. The paper investigates a Granger causality relationship in the specified VAR model by implementing the Toda and Yamamoto procedures while determining the direction of the causality through our impulse response analysis. Our findings show unidirectional causality from exchange rates to the stock market in the pandemic but no causality before the pandemic. This suggests that the exchange rate affects the performance of the Nigerian stock market in the pandemic period. Therefore, the Nigerian stock market and the exchange rate should not be considered as alternative strategies to mitigate risk during the crisis periods.

The interconnectedness across risk appetite of distinct investor types in Borsa Istanbul

PurposeThis study aims to investigate the interconnectedness across the risk appetite of distinct investor types in Borsa Istanbul. This study also examines the causal impact of global implied volatility indices on the risk appetite of these investor groups.Design/methodology/approachThe authors use a novel time-varying frequency connectedness framework of Chatziantoniou et al. and a new time-varying Granger causality test with a recursive evolving procedure by Shi et al. over June 2008 and July 2022.FindingsThe results show a high level of interconnectedness across the risk appetite of different investor types. The sizable spillovers to domestic types of investors either occur from professional or foreign investors, indicating the long-term dominant effect of foreign and more qualified investors on the domestic investors in Borsa Istanbul. The authors provide significant evidence of causality from the global implied volatility to the Borsa Istanbul risk appetite indices, which are getting stronger after the COVID-19 outbreak.Originality/valueUnlike the previous studies, the authors analyze the risk appetite sub-indices of various types of investors to reveal behavioral distinctions and interconnectedness across them. The authors use a novel econometric framework to assess investors' risk appetite in different investment horizons in a time-varying system. Together with volatility index (VIX), the authors also use volatilities of oil (OVX), gold (GVZ) and currency (EVZ), considering the information transmission not only from stock markets but also energy, metals and currency markets. The present data set covers significant financial crises, socioeconomic events and the COVID-19 outbreak.

The role of the COVID-19 pandemic in time-frequency connectedness between oil market shocks and green bond markets: Evidence from the wavelet-based quantile approaches.

This study contributes to the existing literature on the relationship between oil market shocks and the green bond market by investigating the impact of the COVID-19 pandemic on their dynamic correlation. We first decompose the oil market shocks into components using a time-frequency framework. Then, we combine wavelet decomposition and quantile coherence and causality methods to discuss changes during the COVID-19 era. We observe positive effects of both supply-driven and demand-driven oil shocks on the green bond market at most quantile levels. However, supply-driven oil price changes play a major role. The results also indicate that long-term changes have a greater impact than short-term changes on the connection between oil and green bond markets. Nevertheless, the COVID-19 pandemic changed the nature of the causal relationship, as we observed no relationship under extreme market conditions during the pandemic era. We argue that the economic and social impacts of the COVID-19 pandemic have left investors focusing on the short-term substitution between oil and green bond markets.

Quantile Dependence between Crude Oil Returns and Implied Volatility: Evidence from Parametric and Nonparametric Tests

We examine the daily dependence and directional predictability between the returns of crude oil and the Crude Oil Volatility Index (OVX). Unlike previous studies, we apply a battery of quantile-based techniques, namely the quantile unit root test, the causality-in-quantiles test, and the cross-quantilogram approach. Our main results show evidence of significant bi-directional predictability that is quantile-dependent and asymmetric. A significant positive Granger causality runs from oil (OVX) returns to OVX (oil) returns when both series are in similar lower (upper) quantiles, as well as in opposite quantiles. The Granger causality from OVX returns to oil returns is only significant during periods of high volatility, although it is not always positive. The findings imply that the forward-looking estimate of oil volatility, reflecting the sentiment of oil market participants, should be considered when studying price variations in the oil market, and that crude oil returns can be used to predict oil implied volatility during bearish market conditions. Therefore, the findings have implications regarding predictability under various conditions for oil market participants.

Directional predictability and volatility spillover effect from stock market indexes to Bitcoin: evidence from developed and emerging markets

PurposeThis paper aims to quantify the volatility spillover impact and the directional predictability from stock market indexes to Bitcoin.Design/methodology/approachDaily data of 15 developed and 15 emerging stock markets are used for the period March 2017–December 2021.;The author uses vector autoregressive (VAR) model, Granger causality test and impulse response function (IRF) to estimate the results of the study.FindingsEmpirical results show a significant unidirectional volatility spillover impact from emerging markets to Bitcoin and only six stock markets are powerful predictors of Bitcoin return in the short term. Additionally, there is no a difference between developed and developing markets regarding the directional predictability however there is difference in the reaction of Bitcoin return to shocks in the emerging markets compared to developed ones.Originality/valueThe paper proposes different econometric techniques from prior research and presents a comparative analysis between developed and emerging markets.

Price Transmission and Asymmetry in the Colorado Potato Supply Chain

We conduct a time-series analysis of Colorado, Idaho, and national potato markets to examine price transmission and asymmetry (relative likelihood and magnitude of upward versus downward price shocks). Prices are typically driven by supply-side shocks. Colorado potato producers' prices are influenced by Idaho and experience unfavorable asymmetry relative to downstream parties. We apply findings to the COVID-19 lockdown period as a case study to explore market behavior during that time. Identifying and noting potentially harmful price dynamics in commodity markets could help producers effectively respond to similar shocks in the future. © 2022, Food Distribution Research Society. All rights reserved.

Asymmetric dynamic risk transmission between financial stress and monetary policy uncertainty: thinking in the post-covid-19 world

Considering the dramatically increasing impact of the COVID-19 outbreak on monetary policy and the uncertainty in the financial system, we aim to examine the dynamic asymmetric risk transmission between financial stress and monetary policy uncertainty. Our sample covers 30 years of data. We first employ the conventional Granger causality test to examine the average relationship between financial stress and monetary policy uncertainty, and the results cannot provide evidence of causality between them. However, from an asymmetric perspective, we further detect the strongly apparent existence of the asymmetric structure of causality between them. Finally, we conduct further research on the asymmetric impacts from a time-varying perspective. The time-varying test finds that this relationship can be influenced by major events, especially the dot-com bubble, the 2009 financial crisis, and the current COVID-19 pandemic. Thus, one can learn more information about the influencing mechanism between financial stress and monetary policy with our work, which may be beneficial for making better decisions in the future. © 2023, The Author(s).

Dependence Analysis for the Energy Sector Based on Energy ETFs

This study investigates the effects of crude oil and natural gas future returns on energy stock portfolios. We consider returns of portfolios of energy companies approximated by energy ETFs and returns of Brent crude oil and natural gas contracts listed on the US market from January 2015 to September 2022. To study the relationship between Brent crude oil, natural gas, and ETFs, we apply Granger causality in mean and variance, Dynamic Conditional Correlation and the tail dependence-focused copula approach. The research hypothesis regarding the dependence between energy ETFs and the underlying energy risk factors—crude oil and natural gas, and therefore, the existence of hedging or diversification opportunities, was verified. Our empirical findings indicate that crude oil has a medium effect on energy ETFs, and for natural gas it is even lower in the analyzed period, so hedging opportunities are weak, but opportunities for diversification arise.

Dynamic causality between oil prices and stock market indexes in Russia and China: does US financial instability matter?

Purpose: This study aims to examine the dynamic bidirectional causality between oil price (OIL) and stock market indexes in net oil-exporting (Russia) and net oil-importing (China) countries. Design/methodology/approach: The authors use monthly data for the period starting from October 1995 to October 2021. In this study, the bootstrap rolling-window Granger causality approach introduced by Balcilar et al. (2010) and the probit regression model are performed in order to identify the bidirectional causality. Findings: The results show that the causal periods mainly occur during economic, financial and health crises. For oil-exporting country, the results suggest that any increase (decrease) in the OIL leads to an appreciation (depreciation) in the stock market index. The effect of the stock market on OIL is more relevant for the oil-importing country than that for the oil-exporting one. The COVID-19 consequences are demonstrated in the impact of oil on the Russian stock market. The probit regression shows that the US financial instabilities increase the probability of causality between OIL and stock market indexes in Russia and China. Practical implications: The dynamic relationship between the variables must be taken into account in investment decisions. As financial instabilities in the USA drive the relationship between oil and stocks, investors should consider geopolitical, economic and financial elements when constructing their portfolios. Shareholders are required to include other assets in their portfolios since oil–stock relationship is highly risky. Originality/value: This study provides further evidence of the bidirectional oil–stock causal link. Additionally, it examines the impact of financial instabilities on the probability that the OIL and the stock market index cause each other through the Granger effect. © 2023, Emerald Publishing Limited.

Explaining the Gamestop Short Squeeze using Ιntraday Data and Google Searches

This article examines the recent short squeeze of the GameStop (GME) stock in early 2021. This event, although not the only case of short squeeze, has some idiosyncratic features that makes it extremely interesting, mainly because it was organized by non-institutional investors through social media like Reddit. Using intraday data during the period 4/1/2021-26/3/2021, we conclude that volume and Google searches provide useful information which enable us to explain the GME performance. Moreover, we show that information on volume and Google searches can provide investors with valuable data, but the faster investors have access to this information, the greater the advantages. This analysis could be very useful for scholars and practitioners who examine profitable investment strategies when such conditions emerge in the markets, and it also provides some thoughts for regulators regarding the impact of networks, social or not, on the stability of the financial markets.

Association Between Weather Parameters and SARS-CoV-2 Confirmed Cases in Two South African Cities.

Several approaches have been used in the race against time to mitigate the spread and impact of COVID-19. In this study, we investigated the role of temperature, relative humidity, and particulate matter in the spread of COVID-19 cases within two densely populated cities of South Africa-Pretoria and Cape Town. The role of different levels of COVID-19 restrictions in the air pollution levels, obtained from the Purple Air Network, of the two cities were also considered. Our results suggest that 26.73% and 43.66% reduction in PM2.5 levels were observed in Cape Town and Pretoria respectively for no lockdown (Level 0) to the strictest lockdown level (Level 5). Furthermore, our results showed a significant relationship between particulate matter and COVID-19 in the two cities. Particulate matter was found to be a good predictor, based on the significance of causality test, of COVID-19 cases in Pretoria with a lag of 7 days and more. This suggests that the effect of particulate matter on the number of cases can be felt after 7 days and beyond in Pretoria.

A study on the changes in the ICT industry after the COVID-19 pandemic

Purpose: The aim of this paper is to explore the changes in the ICT and global value chains (GVCs) after the COVID-19 pandemic. Design/methodology/approach: This study compared the difference between Korea' domestic ICT industries, ICT imports and ICT exports before and after the COVID-19 outbreak by using trade data of ICT products and national economic indicators, and presents growth strategy for the ICT industry in the post-COVID 19 era. For this purpose, this study determined the causalities between Korea's imports/exports of ICT products and composite Indexes before and after COVID-19, and derived implications in the ICT industry environment after the COVID-19 pandemic. Findings: Analysis results showed the following changes in Korea's ICT industry in the post-COVID-19 world. (1) Non-face-to-face and contact-free technologies related sectors in the ICT industry, such as the semiconductor sector, have grown exponentially;(2) as the USA has grown as the new key player, the causal relationship with China, a key player of the GVC in the pre-COVID-19 era, disappeared;and (3) the GVC of the ICT industry is not a rigid one-way vertical structure, but is changing to a flexible structure influenced by cooperation and competition between countries. Originality/value: The results indicate that it is essential to constantly develop new ICT sectors that make use of non-face-to-face and contact-free technologies in the post-COVID-19 era, and the main strategies in response to the changed GVC would be taking the initiative by securing source technologies and expanding through cooperation with other GVCs and resource sharing. © 2022, Emerald Publishing Limited.

Which is leading: Renewable or brown energy assets?

This study examines the relationship between crude oil, a proxy for brown energy, and several renewable energy stock sector indices (e.g., solar energy, wind energy, bioenergy, and geothermal energy) over various investment horizons. Using daily data from October 15, 2010, to February 23, 2022, we apply a combination of methods involving co-integration, wavelet coherency, and wavelet-based Granger causality. The results show that the relationship between crude oil and renewable energy indices is non-linear and somewhat multifaceted. Firstly, there are sectorial differences in the intensity of the relationships. Notably, the relationship intensity between the wind and crude oil is lower than that involving geothermal energy or bioenergy. Secondly, the relationship evolves with time. For example, the COVID-19 outbreak seems to have increased the relationship between crude oil and renewable energy markets, notably for solar, bioenergy, and geothermal. Thirdly, the relationship varies across scales. When controlling for the VIX (volatility index), a proxy of the sentiment of market participants, and EPU (economic policy uncertainty index), the relationship seems strong in the long term but weak in the short term. This result is confirmed using a Granger causality test on the wavelet-decomposed series. These findings have important implications for long-term investors, short-term speculators, and policymakers regarding the co-movement between brown and renewable energy markets. © 2022 Elsevier B.V.