Positive Co-movement Research Articles

Comovements and hedging effectiveness between conventional and Islamic cryptocurrencies: evidence from the COVID-19 pandemic

PurposeThis study examines the dynamics of the comovement and causal relationship between conventional (Bitcoin, Ethereum and Binance coin) and Islamic (OneGram, X8X token and HelloGold) cryptocurrencies.Design/methodology/approachThis study uses wavelet coherence approach to examine the time-varying lead-lag relationship between conventional and Islamic cryptocurrencies. Furthermore, the authors use BEKK-GARCH model to estimate the optimal weights, hedge ratio and hedging effectiveness in pre-COVID-19 and during the COVID-19 period.FindingsThe authors find no significant comovement in pre-COVID-19. However, the authors find significant positive comovement in conventional and Islamic cryptocurrencies at the beginning of the pandemic, and in most cases, conventional cryptocurrencies are leading. X8X and HelloGold have no/weak correlation with conventional cryptocurrencies, implying that investors can diversify the risk by making an Islamic and conventional cryptocurrencies portfolio. The authors also calculate the optimal weights, hedge ratio and hedging effectiveness using the BEKK-GARCH model. Based on the optimal weights, for the portfolios of conventional–Islamic cryptocurrencies, investors are suggested to increase their investment in Islamic cryptocurrencies during the COVID-19 than normal period. The results of hedge ratios show that hedging costs are higher during COVID-19 than before.Practical implicationsThe findings of the paper offer several practical policy implications for investors, portfolio manager, Shariah advisors and policymakers pertaining to asset allocation, risk management, forecasting and diversification. Specifically, investors can maximize the risk adjusted returns of their conventional cryptocurrencies portfolio by adding some portions of Islamic cryptocurrencies. Considering the comovement is time-varying, investors/manager should adjust their investment strategies frequently. For the entrepreneurs in crypto-industry, it is advised to introduce new Islamic cryptocurrencies, as it has a huge growth potential because of their distinct features and performance.Originality/valueThis is the first study that explores the linkages between conventional and Islamic cryptocurrencies, therefore this study extends the literature of Islamic finance, stablecoins and cryptocurrencies in pre-COVID-19 and during COVID-19 period. The study results provide insights to conventional crypto investor on how to manage their portfolio during normal and turbulent period.

Stock Market Co-Movements between CPEC Economies: A Wavelet based Approach

This research investigates the co-movement of Stock Market Returns between China and Pakistan in the prospective of China Pakistan Economic Corridor. In this study, individual power spectrum, cross and wavelet coherence are used for analyzing co-movement of stock returns between Pakistan and Shanghai at the aggregate level. Wavelet methodology enables the simultaneous examination of the behavior of a time-series in both frequency and time spaces. The daily data for this study is retrieved from the data stream that ranges from January 1, 2007 until May 30, 2022. The wavelet coherence technique reveals that there is strong positive co-movement at the aggregate level in different times, which is a good sign for the investors and policy makers to diversify their investment for getting maximum benefits. The results have an important implication for the fund managers, policy makers, investors and that encourages the portfolio diversification.

Role of hydroelectricity and natural gas consumption on environmental sustainability in the United States: Evidence from novel time-frequency approaches

This study analyzes time- and frequency-varying impacts of hydroelectricity energy consumption, natural gas energy consumption, and economic growth on environmental sustainability proxied by carbon dioxide (CO2) emissions in the United States of America (the US) for the period 1965/Q1 to 2020/Q4. This study is the first of its kind to contribute to the current literature by analyzing dynamic relationships among these variables in the short-, medium-, and long-term at different time frequencies in the framework of a multivariate correlation, hence providing a more comprehensive picture about the impacts of these effective factors on CO2 emissions. To meet the objectives of the study, Wavelet local multiple local (WLMC), which is a recent novel methodology developed by Polanco-Martínez et al. (2020), is applied. Moreover, the Wavelet coherence (WTC) approach is used for robustness check. The outcomes provide fresh insights into the long-term dynamic correlations among hydroelectricity energy consumption, natural gas energy consumption, economic growth, and CO2 emissions. The study discovers a robust positive co-movement between natural gas energy consumption and CO2 emissions and a negative correlation between hydro energy consumption and CO2 emissions that is the most intense on the long-term frequencies. Furthermore, economic growth causes CO2 emissions, which is evidenced by a positive relationship between both factors at short- and long-term time-frequencies. Supported by the outcomes of the study, the authors urge to suggest crucial insights and policy points for the US policymakers to shift from fossil energy to renewable energy sources to meet Sustainable Development Goals (SDGs), especially SDG-7 and SDG-13, since they induce lower emissions.

Time‐frequency comovement among green financial assets and cryptocurrency uncertainties

AbstractThe high energy consumption and carbon footprints have raised environmental and sustainable concerns of green investors and policymakers. This study explores comovements between three green and socially responsible financial assets, S&P global clean energy index (GCEI), S&P green bonds index (GB), DJ sustainability world index (DJSWI) and four cryptocurrency uncertainty/attention indices cryptocurrency policy uncertainty index, Central Bank Digital Currencies Uncertainty Index, Central Bank Digital Currencies Attentions Index and Index of Cryptocurrency Environmental Attention using the bivariate wavelet coherence approach. The findings show that GCEI, GB, DJSWI returns have consistent positive comovement with all cryptocurrency uncertainty/attention indices in the medium‐term, suggesting their time‐varying leading role. Evidence of negative coherences shows that higher cryptocurrency uncertainties/attentions lead to lower green financial asset returns, reflecting the adverse impact of higher uncertainties/attention on the trust of green and sustainable investors. The above empirical findings offer up‐to‐date insights for guiding policymakers, and regulators, enabling them in environmental policy development. Furthermore, socially responsible investors can make better investment judgments by considering the environmental concerns in the cryptocurrency marketplaces.

Return and risk spillovers between the ESG global index and stock markets: Evidence from time and frequency analysis

In this paper, we examine comovements between stock market returns and investments that take into account Environmental, Social, and Governance (ESG) factors by studying the interconnections between the two returns in time and frequency space. We study interdependencies between the conventional stock market and ESG stocks using daily data from 2007 to 2021 for 19 developing and 19 developed countries. Our results show significant comovement patterns between ESG returns and stock returns at various frequencies, time scales, and sample episodes in all countries, particularly during periods of financial turmoil. For the most part, we document positive (in-phase) comovements between the stock returns and ESG returns in developing countries and negative (out-of-phase) comovements in developed countries. This implies limited portfolio gains from adding ESG stocks to portfolio diversification in developing countries but significant gains in developed countries.

Time–frequency contained co-movement of renewable electricity production, globalization, and co2 emissions: A wavelet-based analysis in Asia

This study examined the time–frequency relationship between renewable energy, globalization, economic growth, trade openness, urbanization, and CO2 emissions in Asia. The wavelet-based causality framework was utilized to quantify the causal associations in time–frequency space among the variables. The method is favorable as a scaling tool and it unveils the time–frequency dependence among variables with more reliability and it accounts for the seasonality, cycles, or trends extracted from the transformation change over time. The empirical data demonstrated that within the sample period, the substantial causal relationships between the employed variables are primarily focused on the short and medium runs at different frequency scales. The wavelet coherence results provided evidence of a strong association among the variables in the long-run estimation, which is supported by the Trace analysis and the Toda–Yamamoto causality. The findings also revealed that renewable energy and CO2 are out of phase and have an anti-cyclic impact, with CO2 emissions driving the cycle. A positive co-movement between globalization and CO2 emissions was observed with no lag relationship, while the association between trade openness and CO2 emissions was seen to be insignificant in the long run. These results have significant policy implications for Asian economies’ long-run sustainable policies. Environmental researchers should take into account lead–lag channels of transmission and the time–frequency nexus between series.

Dynamic connectedness of China’s green bonds and asset classes

This paper quantifies the co-movement and time-varying integration between China's green bonds and other asset classes across different time domains using the wavelet coherence and time-frequency connectedness model based on the time-varying parameter VAR (TVP-VAR). First, we predominantly detect a strong positive co-movement of green and conventional bonds, especially in the medium and long term. Second, strong bidirectional spillovers exist between green bonds and treasury, corporate, and financial bonds regardless of the time horizon. Lastly, cross-market spillovers between the green bonds and the stock, energy, low-carbon stock market were quite limited in the short-run but strengthened towards the long-term except during the 2015 China stock market crash and the COVID-19 recession when short-term integration rose sharply. The results document some practical enlightenment for investors and policymakers with various time horizons.

Socio-economic and technological drivers of sustainability and resources management: Demonstrating the role of information and communications technology and financial development using advanced wavelet coherence approach

Inclusive and sustainable growth can only be ensured through socio-economic and technological transformation. In this regard, this study offers a new perspective on the dynamic interrelationship between financial development (FD), economic growth (GDP), information and communication technologies (ICT), education (EDU), and CO2 emissions (CO2) in the United Kingdom. The paper employs the Breitung and candelon (2006) causality and wavelet approaches to assess these connections using data from 1990Q1 to 2019Q4. The wavelet coherence is employed to explore the coherence and lead/lag interrelationship between CO2 and the independent variables over dissimilar time scales. Finally, the Breitung and candelon (2006) causality test is used as a robustness check for the wavelet coherence approach. The wavelet coherence (WTC) revealed: (a) negative coherence between CO2 and GDP with GDP leading; (b) negative co-movement between CO2 and financial development with financial development leading; (c) positive co-movement between CO2 and energy use with energy use leading; (d) negative co-movement between ICT and CO2 with ICT leading; and (e) negative co-movement between education and CO2 with education leading. The outcomes of the multiple wavelet and partial wavelet as well as the Breitung and candelon (2006) causality comply with those of the wavelet coherence. Since a connection between CO2 and financial development and ICT is found in the short-medium term, our findings imply that policymakers should focus on investing in technologies and financial markets. In addition, the report recommends that emphasis be placed on green energy policies, as growing pollution levels from fossil fuels impede long-term productivity.

Time-frequency comovements between sovereign CDS and exchange rates: The role of sentiments

This study introduces various bivariate, multiple, and partial wavelet methods to explore the role of inclusive market sentiments in comovements between sovereign credit default swap (CDS) spreads and exchange rates from a time-frequency perspective. The empirical results show that the sovereign CDS spread and exchange rate nexus varies across countries and time-frequency domains. Further, the strong and positive comovements between sovereign CDS spreads and exchange rates are uncovered, concentered at medium- and long-term frequencies, especially in commodity-dependent countries. Among the various market sentiments, Volatility Index and Chicago Board Options Exchange Crude Oil Volatility are revealed as the most critical factors driving the comovements in commodity-dependent countries. The findings provide important recommendations for investors, regulatory authorities, and policymakers to understand the pivotal roles of market sentiments in inducing comovement between sovereign CDS spreads and exchange rates.

Quantiles dependence and dynamic connectedness between distributed ledger technology andsectoral stocks: enhancing the supply chain and investment decisions with digital platforms.

Distributed Ledger Technology (DLT) is highly applicable in various fields, especially the supply chain in many sectors. Against limited empirical evidence, this paper analyzes the relations between the Kensho Distributed Ledger Technology Index and stock indices of 12 sectors, including communication services, consumer discretionary, consumer staples, energy, health care, financials, industrials, information technology, materials, utilities, and real estate, and ESG by employing the quantile coherency and dynamic connectedness techniques. Our results reveal that the quantile coherency between the DLT stock index and the sectoral stock indices in almost all cases is significant and positive. The positive co-movement tends to be stronger in the longer terms and as we move from the lower to the higher quantiles, implying that they are more strongly connected in the long term and during the bearish market condition. Moreover, the dynamic connectedness indicates that the DLT stocks and the sectoral stocks are highly connected, with the former being a net transmitter of spillover shocks. The spillovers are also time-varying, and the results significantly corroborate those of the quantiles coherency methods. Among other relevant implications, DLT can be an important factor in the development and enhancement of these sectors.

Financial shocks and the relative dynamics of tangible and intangible investment: Evidence from the euro area

Abstract We develop an extended real business cycle model with financially constrained firms and non-pledgeable intangible capital. Based on a model-consistent series for firms’ borrowing conditions, we find, within a structural vector autoregression framework, that, in response to an adverse financial shock, tangible investment falls more than intangible investment. This positive co-movement between tangible and intangible investment as well as the relative resilience of intangible investment pose a challenge for the theoretical model. We show that investment-specific adjustment costs help in reconciling the model with the observed empirical evidence. The estimation of the theoretical model using a Bayesian limited information approach yields support for the presence of much larger adjustment costs for intangible investment than for tangible investment.

Is Bitcoin a Safe Haven for Indian Investors? A GARCH Volatility Analysis

This paper attempts to understand the dynamic interrelationships and financial asset capabilities of Bitcoin by analysing several aspects of its volatility vis-a-vis other asset classes. This study aims to analyse the volatility dynamics of the returns of Bitcoin. An asymmetric GARCH model (EGARCH) is used to investigate whether Bitcoin may be useful in risk management and ideal for risk-averse investors in anticipation of negative shocks to the market (leverage effect). This paper also examines Bitcoin as an investment and hedge alternative to gold as well as NSE NIFTY using a multivariate DCC GARCH model. DCC GARCH models are also used to check whether correlation (co-movement) between the markets is time-varying, examine returns and volatility spillovers between markets and the effect of the outbreak of COVID-19 in India on the investigated markets. The results show that given the supply of Bitcoin is fixed, low returns realisation is equivalent to excess supply over demand wherein investors are selling off Bitcoin during bad times. The positive co-movement between Bitcoin and gold during the COVID-19 outbreak shows that investors perceived Bitcoin as a relatively safe investment. However, overall analysis shows that Bitcoin was not considered a safe hedge and an investment option by Indian investors during the study period.

Rare Earth Market, Electric Vehicles and Future Mobility Index: A Time-Frequency Analysis with Portfolio Implications

This study investigates the co-movements between the Solactive Electric Vehicle and Future Mobility Index (EVFMI) and multiple rare earth elements (REEs). We applied a TVP-VAR model and bivariate wavelet coherence approach to capture co-movements both in the time and frequency domain considering short-, medium- and long-term investment horizons. Using daily returns from 1 June 2012 to 4 June 2021, the results of the TVP-VAR model show that individual REEs and the EVFMI have strong return connectedness and are heterogenous over time. The bivariate wavelet coherence approach reveals that Dysprosium, Neodymium, Praseodymium and Terbium returns have positive co-movement (in-phase) with the EVFMI in the medium-term and long-term. In contrast, Cerium, Europium, Lanthanum and Yttrium returns have negative co-movements (out-phase) with the EVFMI in the medium-term and long-term. We find strong positive co-movements between the MVIS Global Rare Earth/Strategic Metals Index (MVREMX) and EVFMI at multiple wavelet scales. Following the lead/lag relationship, Cerium, Europium and Lanthanum, Yttrium returns are leading the EVFMI, and Neodymium, Dysprosium, Praseodymium, Terbium and MVREMX returns are lagging to the EVFMI. This study, therefore, suggests heterogenous hedging and diversification properties of REEs over time and investment horizons. Specifically, Cerium, Europium, Lanthanum and Yttrium act as strong hedges in long-term investment horizons and Neodymium, Dysprosium, Praseodymium and Terbium are weak hedges or diversifiers in short-term investment horizons. These results may be of particular interest to investors and relevant to policymakers considering multiple investment horizons.

Time-frequency moment interdependence of equity, oil, and gold markets during the COVID-19 pandemic

Like no other calamitous event in recent memory, the COVID-19 pandemic has plunged the world’s financial system into disarray, triggering systemic risk spillovers across markets. In this study, we use 5-minute index futures price data to examine the multiscale interdependence structure of global equity, gold, and oil markets prior to and following the COVID-19 outbreak, in terms of the first four realized moments of their respective return distributions (i.e., mean, variance, skewness, and kurtosis). With respect to the equity-gold nexus, we find that stock (gold) returns and volatility negatively (positively) lead their gold (stock) counterparts at medium- and long-term scales in the pandemic period, while asymmetry risk in stock markets positively leads its counterpart in gold markets at the same scales before and during the early months of the health crisis. Concerning the oil-equity nexus, our results reveal a positive (negative) co-movement between asymmetry risks at short- and medium-term scales in January-April (May-July) 2020, whereas heavy tail risks are positively synchronized at low frequencies in the turbulent period of March-April 2020. Some policy implications are derived from the analysis.

Current Account Imbalances, Real Exchange Rates, and Nominal Exchange Rate Variability

AbstractThis paper globally analyzes the bivariate relation between large current account imbalances and the real exchange rate over different degrees of nominal exchange rate variability. Employing both linear and nonlinear panel estimation procedures, we typically find an inverse long-run link between large imbalances and the real exchange rate at lower nominal exchange rate rigidity levels. This is in contrast to the often non-existent or positive comovement that materializes under lower nominal exchange rate variation. Our results thus suggest that greater nominal exchange rate adjustment can induce a stabilizing “current account”-“real exchange rate” relation. Meanwhile, current account adjustment speeds up with more flexible nominal exchange rates. Along the cross-section, the most salient findings are i) the striking positive relation between current account persistence and real exchange rate persistence based on country-specific estimates and ii) the inverse correlation between persistence in either the current account or real exchange rate and nominal exchange rate volatility.

Do stock market fear and economic policy uncertainty co-move with COVID-19 fear? Evidence from the US and UK

PurposeThe purpose of the paper is to investigate co-movement of major implied volatility indices and economic policy uncertainty (EPU) indices with both the health-based fear index and market-based fear index of COVID-19 for the USA and the UK to help investors and portfolio managers in their informed investment decisions during times of infectious disease spread.Design/methodology/approachThis study uses wavelet coherence approach because it allows to observe lead–lag nonlinear relationship between two time-series variables and captures the heterogeneous perceptions of investors across time and frequency. The daily data used in this study about the USA and the UK covers major implied volatility indices, EPU, health-based fear index and market-based fear index of COVID-19 for both the first and second waves of COVID-19 pandemic over the period from March 3, 2020 to February 12, 2021.FindingsThe results document a strong positive co-movement between implied volatility indices and two proxies of the COVID-19 fear. However, in all the cases, the infectious disease equity market volatility index (IDEMVI), the COVID-19 proxy, is more representative of the stock market and exhibits a stronger positive co-movement with volatility indices than the COVID-19 fear index (C19FI). This study also finds that the UK’s implied volatility index weakly co-moves with the C19FI compared to the USA. The results show that EPU indices of both the USA and the UK exhibit a weak or no correlation with the C19FI. However, this study finds a significant and positive co-movement of EPU indices with IDEMVI over the short horizon and most of the sampling period with the leading effect of IDEMVI. This study’s robustness analysis using partial wavelet coherence provides further strengths to the findings.Research limitations/implicationsThe investment decisions and risk management of investors and portfolio managers in financial markets are affected by the new information on volatility and EPU. The findings provide insights to equity investors and portfolio managers to improve their risk management practices by incorporating how health-related risks such as COVID-19 pandemic can contribute to the market volatility and economic risks. The results are beneficial for long-term equity investors, as their investments are affected by contributing factors to the volatility in US and UK’s stock markets.Originality/valueThis study adds following promising values to the existing literature. First, the results complement the existing literature (Rubbaniy et al., 2021c) in documenting that type of COVID-19 proxy matters in explaining the volatility (EPU) relationships in financial markets, where market perceived fear of COVID-19 is appeared to be more pronounced than health-based fear of COVID-19. Second, the use of wavelet coherence approach allows us to observe lead–lag relationship between the selected variables, which captures the heterogeneous perceptions of investors across time and frequency and have important insights for the investors and portfolio managers. Finally, this study uses the improved data of COVID-19, stock market volatility and EPU compared to the existing studies (Sharif et al., 2020), which are too early to capture the effects of exponential spread of COVID-19 in the USA and the UK after March 2020.

The international real business cycle when demand matters

This study explores the demand side of an international real business cycle model adopting additive intratemporal preferences over differentiated final goods and monopolistic competition. It shows that the structure of the demand system matters for macroeconomic dynamics by affecting firms’ pricing over time and across countries. The endogenous variability of markups and profits amplifies the propagation of shocks through novel substitution effects, generating positive comovements of output, labor and investment, and reducing consumption correlation between countries. In particular, a positive shock in the Home country improves its terms of trade, promotes consumption in the Home country and also production in the Foreign country.

A static and dynamic copula-based ARIMA-fGARCH approach to determinants of carbon dioxide emissions in Argentina.

This paper attempts to model both static and dynamic dependence structures and measure impacts of energy consumptions (both renewable (EC) and non-renewable (REN) energies), economic globalization (GLO), and economic growth (GDP) on carbon dioxide (CO2) emissions in Argentina over the period 1970-2020. For analyses purpose, the current research deploys the novel static and dynamic copula-based ARIMA-fGARCH with different submodels. The static bivariate copula results show that the growth rates of the pairs EC-CO2 and GDP-CO2 are asymmetrically positive co-movements and have high left tail (extreme) dependencies, implying that the increase in non-renewable energy and economic growth can critically contribute to the environmental degradation, and the decrease in the consumption of non-renewable energy at a high level will consequently reduce the CO2 emissions at the same level. Based on several copula-based dependence measures, we document that between the two factors, the non-renewable energy has a stronger impact than the economic growth regarding the CO2 emissions. On the other hand, the growth rates of both economic globalization and renewable energy symmetrically negatively co-move with the growth rates of the CO2 emissions, but they have no extreme dependencies, indicating that these factors contribute to Argentina's environmental quality, in which the factor of renewable energy has a greater impact. Furthermore, the dynamic copula outcomes show that the (tail) dependencies of CO2 emissions on the non-renewable energy and economic growth are time-varying, while the pairs REN-CO2 and GLO-CO2 possess only dynamic dependencies, but no dynamic tail dependencies. Moreover, through the dynamic copula-based dependence, the environmental Kuznets curve (EKC) hypothesis can be estimated and illustrated explicitly. In addition, we leverage multivariate vine copulas for modelling dependence structures of the five variables simultaneously, which can reveal rich information regarding conditional associations among the relevant variables. Some policy implications are also provided to mitigate CO2 emissions.

Are green bonds and sustainable cryptocurrencies truly sustainable? Evidence from a wavelet coherence analysis

This article aims to explore the co-movement of daily returns among S&P green bonds (GB/GBs), the top five sustainable cryptocurrencies, Bitcoin, the Dow Jones Sustainability World Index (DJSWI) and the Dow Jones Sustainability Emerging Market Index (DJSEMI) to determine whether GBs, Bitcoin and sustainable cryptocurrencies are truly sustainable; in addition, it investigates hedging and diversification opportunities. Using a partial wavelet coherence framework to capture the bivariate co-movement, our findings show strong (weak) positive co-movements among GB (sustainable cryptocurrencies) and DJSWI returns, where GBs (sustainable cryptocurrencies) have a heterogeneous leading role in the short-term and long-term horizons. Results indicate moderate positive (negative) co-movement among GBs and sustainable cryptocurrencies (Bitcoin) and DJSWI in the short run (long run). Overall, the results show GB (sustainable cryptocurrencies) acts as a diversifier for Bitcoin and sustainable cryptocurrencies in most cases (DJSWI). However, increasing Bitcoin returns adversely impacts the DJSWI in the long run. Findings are equally imperative for green investors, crypto traders and policymakers, where investors and traders can earn financial and social returns, and policy-makers can deploy suitable policies for the development of sustainable cryptocurrency mining processes. The role of Bitcoin is alarming for the United Nations Sustainable Development Goals and global greener economy.

Sentiments and real business cycles

We introduce sentiments under incomplete information in an otherwise standard real business cycle model. Individual firms receive signals about their idiosyncratic demand shocks, which are confounded by sentiments. Sentiments coordinate the optimal decisions of individual firms through their extraction of aggregate economic conditions from the signals. We show that there exists a sentiment-driven rational expectations equilibrium, in addition to a fundamental equilibrium. Optimism stimulates the aggregate economy, leading to positive comovements between output, consumption, investment, and hours worked. We calibrate a full-fledged dynamic stochastic general equilibrium model based on U.S. aggregate data and find that sentiment shocks substantially amplify aggregate fluctuations and contribute to real business cycles.