Dynamic linkages between shipping and commodity markets: Evidence from a novel asymmetric time-frequency method

This study extends the existing literature in this area by examining the connectedness and shock spillover between commodity and shipping markets using a new novel time-varying frequency and quantile connectedness method developed by Chatziantoniou et al (2022) based on B&K (2018) and Ando et al (2018). Connectedness and shock transmission between the markets were analysed with daily data covering July 4, 2012 to July 20, 2022. A major value added of this study to the existing literature is the examination of the asymmetric effect of commodity price changes (or return) on the connectedness of the markets. Mean-frequency total connectedness analysis indicates that, the overall shipping market (BDI) is both the transmitter (to) and receiver of the highest shock from the entire market connectedness system. In the short-term, the agricultural markets dominate as both the transmitters and receivers of the major shocks to and from the entire market system, while in the medium-term, the shipping markets dominate as both the transmitters and receivers of the largest shocks to the entire market system. However, in the long-term, connectedness and shock propagation were very low. The time-varying quantile analysis reveals that, connectedness was very strong before, during and after COVID-19 at the bearish and bullish market conditions. Further, the time-varying frequency connectedness analysis shows that, although total connectedness is relatively high overtime, it was propelled by short-term dynamics. Metal markets are connected among themselves, and with both agricultural and shipping markets. Agricultural markets are connected among themselves, and with shipping markets, which are only connected among themselves. There is evidence of the asymmetric effect of commodity return dynamics on the connectedness of the markets. Some important policy recommendations were drawn from the findings.

Time-varying effects of fuel prices on stock market returns during COVID-19 outbreak.

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.

The systemic risk in Thailand: the role of tourism industry

The study analyses the contribution of the tourism, banking, property fund and real estate, and finance and securities industries to the systemic risk of Thailand. Using quantile regression, the study estimates the measures of systemic risk (conditional Value-at-Risk (CoVaR) and delta conditional Value-at-Risk (∆CoVaR)) and examines the relevance of various industries in increasing the systemic risk of Thailand using Kolmogorov – Smirnov test. The findings support the relevance of the tourism industry in significantly contributing to the systemic risk in Thailand. The study also highlights the systemic relevance of the tourism industry during the COVID-19 period in Thailand, when the industry was severely impacted, which adversely affected its systemic risk. [ FROM AUTHOR]

Dynamic spillover effects among green bond, renewable energy stocks and carbon markets during COVID-19 pandemic: Implications for hedging and investments strategies☆

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.

Comparing asymmetric price efficiency in regional ESG markets before and during COVID-19.

The ever-emerging environmental, social, and governance (ESG) concerns have received significant attention of policymakers, governments, regulation bodies, and investors. Considering the markets volatilities due to economic and financial uncertainties that can drive the informational price inefficiencies across the markets, this study compares the asymmetric price efficiency of regional ESG markets by using an asymmetric multifractal detrended fluctuation analysis before and during COVID-19 crisis. We then examine whether global factors influence the asymmetric efficiency of regional ESG markets. Our findings reveal that COVID-19 outbreak reduced the efficiency of regional ESG markets, except for Europe, which sustained its efficiency even during the pandemic. Moreover, global factors drive the efficiency of regional ESG markets significantly before and during COVID-19. A major implication of our findings stems from the fact that a contagion reduces the efficiency of the markets while stable economic conditions make those markets informationally efficient.

Extreme Connectedness between Green Bonds, Government Bonds, Corporate Bonds and Other Asset Classes: Insights for Portfolio Investors

This paper aims to examine the connectedness between green and conventional assets, particularly during the period of economic downturn. Specifically, we examine quantile-based time-varying connectedness between the green bond market and other financial assets using quantile vector autoregression (QVAR) from 9 March 2018 to 10 March 2021. We use daily prices of S&P U.S. Treasury Bond Index, S&P US Aggregate Bond Index, S&P US Treasury Bond Current 10Y Index, S&P 500 Bond Index, S&P 500 Financials index, S&P 500 Energy Bond Index and S&P 500, giving a total of 784 observations, and using Composite Index as a representative of conventional assets classes and S&P Green Bond Index to denote the green bond market. Results shows the connectedness between green bonds and the conventional asset classes intensified during the outbreak of the Coronavirus pandemic (COVID-19) as investors shifted their investment towards fixed income assets due to the plunge in the prices of stocks and commodities. The results also shows that green bonds are strongly connected with treasury bonds, aggregate bonds and bond index, as they share similarities with respect to issuance, risk and governance. Connectedness is weak in the case of composite index and energy bond index, as their prices do not have substantial influence on the green bond market. The study highlights the hedging and diversification benefits of green bonds. We have several implications for portfolio managers, policy makers and researchers.

Are FinTech, Robotics, and Blockchain index funds providing diversification opportunities with emerging markets?Lessons from pre and postoutbreak of COVID-19

The study has been inspired by the emergence of technology-based assets, namely, FinTech, Robotics, and Blockchain in the 4th Industrial Revolution. We are examining diversification opportunities with nonconventional technology funds based on FinTech, Robotics, and Blockchain while investing in MSCI Emerging Markets Index, and finally gauging the most resilient fund during the pre-and post-outbreak of COVID-19. The five technology-driven funds considered are ARK FinTech Innovation Exchange Traded Funds (ARKF), Global X FinTech Exchange Traded Funds (FINX), First Trust NASDAQ Artificial Intelligence and Robotics Exchange Traded Funds (ROBT), Global X Robotics and Artificial Intelligence (BOTZ), and Ishares Robotics and Artificial Intelligence (IRBO) to investigate diversification opportunities with MSCI Emerging Markets Index. The time-varying dynamic spillover using the Vector Auto Regression Model for average, low, and high volatility quantiles and the network of volatility connectedness based on quantile VAR have been applied to capture diversification and identifying the most resilient fund. The study found that ARKF and FINX provide diversification opportunities. In each quantile, these two funds are evidence of diversification, and BOTZ, also shows diversification evidence. Moreover, FINX is the throughout resilient fund, and ARKF is the most resilient in extreme quantiles. Throughout the quantiles, it is perceived a significant impact of COVID-19 on the total connectedness of Funds with the emerging market index.

Role of perceived corporate social responsibility in the nexus of perceived cause-related marketing and repurchase intention in emerging markets

Purpose>This study aims to evaluate the impact of perceived cause- related marketing (perceived-CRM) on the repurchase intention (CRIN). Besides, brand image (BIMA) and customer satisfaction (CSAT) connect this relationship as mediating variables. Especially, the role of perceived corporate social responsibility (perceived-CSR) contributed to this nexus between perceived-CRM and BIMA, perceived-CRM and CSAT in emerging economies.Design/methodology/approach>The paper follows a quantitative approach. Based on a comprehensive literature review on perceived-CSR, perceived-CRM , BIMA, CSAT and repurchase intention, the authors evaluate the impact of those constructs on repurchase intention in an emerging market. The study sample was composed of 395 responses covering customers of consumer goods. The study uses the Smart PLS-SEM version 3.3.2 to analyze the data.Findings>The findings revealed significant contributions to the extant CRM literature in some ways. This study's outcomes contribute to extending the existing literature on CRM and CSR. Specifically, the extension focuses on the mediating and moderating effects of BIMA, CSAT and perceived-CSR, respectively, in the relationship between perceived-CRM and CRIN. Moreover, the novelty of this study lies in providing a new approach to the influence of perceived-CRM on CRIN, with the mediating of BIMA, CSAT and moderating effects perceived-CSR integrated into a conceptual model.Practical implications>From a management perspective, the contribution of this study plays a very important role in strategic planning to enhance competitive advantage and improve business performance on a sustainable basis. This sustainability is founded on an insight into how changes in contextual factors affect the perception and consumer behavior of millennials in fast-moving consumer goods (FMCG) market, especially in a context of Covid-19 global crisis. It is important to emphasize that genuineness and transparency in all activities and communications are a prerequisite in today's sensitive context. The application of acquired insight into practice will help businesses operating in the consumer sector improve brand reputation and CSAT. As a result, this leads to enhanced competitive advantage of the business in the market, improved market performance and ultimately to an improvement in the overall performance of the enterprise.Originality/value>This is the first study that explores the moderating role of perceived CSR on the nexus between perceived-CRM with brand image (BIMA) and CSAT to the best of our knowledge. Besides, the study also discovers the mediating role of BIMA and CSAT between perceived-CRM and repurchase-intention in an emerging economy. Findings in this study provided additional evidence to the increasingly important roles of perceived-CRM and perceived-CSR in creating win-win relationships with customers, aiming to solve specific social causes jointly. Further, the perceived-CRM and perceived-CSR mechanisms help businesses enhance their intangible assets and competitive advantages through enhanced BIMA and stronger CRIN. In the current context, the business environment is changing rapidly due to many factors that lead to increased competition at a global level. Therefore, improving competitive advantage is a mandatory condition for businesses to survive and develop sustainably.

Modelling systemic risk of energy and non-energy commodity markets during the COVID-19 pandemic

COVID-19 led restrictions make it imperative to study how pandemic affects the systemic risk profile of global commodities network. Therefore, we investigate the systemic risk profile of global commodities network as represented by energy and nonenergy commodity markets (precious metals, industrial metals, and agriculture) in pre- and post-crisis period. We use neural network quantile regression approach of Keilbar and Wang (Empir Econ 62:1–26, 2021) using daily data for the period 01 January 2018–27 October 2021. The findings suggest that at the onset of COVID-19, the two firm-specific risk measures namely value at risk and conditional value of risk explode pointing to increasing systemic risk in COVID-19 period. The risk spillover network analysis reveals moderate to high lower tail connectedness of commodities within each sector and low tail connectedness of energy commodities with the other sectors for both pre- and post-COVID-19 periods. The Systemic Network Risk Index reveals an abrupt increase in systemic risk at the start of pandemic, followed by gradual stabilization. We rank commodities in terms of systemic fragility index and observe that in post COVID-19 period, gold, silver, copper, and zinc are the most fragile commodities while wheat and sugar are the least fragile commodities. We use Systemic Hazard Index to rank commodities with respect to their risk contribution to global commodities network. During post COVID-19 period, the energy commodities (except natural gas) contribute most to the systemic risk. Our study has important implications for policymakers and the investment industry.

Quantile risk spillovers between energy and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak

The spillover effect is a significant factor impacting the volatility of commodity prices. Unlike earlier studies, this research uses the rolling window-based Quantile VAR (QVAR) model to describe the conditional volatility spillover between energy, biofuel and agricultural commodity markets. Since the magnitude of connectedness and spillover effects may switch between bearish and bullish market states over time, a QVAR model is a relatively realistic and appropriate approach to capture the connectedness as compared to the mean-based approaches of Diebold and Yilmaz (DY;2009, 2012, & 2014) which are mostly used in the literature. To this end, we employ volatility estimates by using the realized variance advanced by Parkinson (1980). Specifically, we investigate the time-varying volatility spillovers and connectedness among agricultural markets (wheat, corn, sugar, soyabean, coffee, and cotton), energy markets (gasoline, crude oil, natural gas) and biofuel (ethanol) markets from January 12, 2012 to May 10, 2021. By comparing our empirical analysis with results from the DY spillover model, we establish that connectedness is stronger in the left and right quantiles than those in the mean and median of the conditional distribution, emphasizing the importance of systematic risk spillovers during extreme market movements. Furthermore, results find that volatility spillovers and connectedness in the right tail is higher than in the left tail. In particular, we document significant volatility spillovers from agricultural markets to energy markets during extreme markets conditions and observe the dominance of agricultural markets over energy markets. To ascertain the impact of COVID-19 on the volatility of markets examined, we divide our sample into sub-samples and observe significant variation in the level of volatility spillovers and connectedness across the markets before and during the outbreak of COVID-19. Finally, some useful implications are summarized for investors' portfolios and risk avoidance.

Risk Connectedness Between Green and Conventional Assets with Portfolio Implications.

The increasing concerns of investors toward green bonds and their appealing nature of diversification has motivated the current research to study the risk connectedness between green and conventional assets spanning from August 2014 to December 2020. We first estimate the dynamic equi-correlations through DECO-GARCH. Next, we assess the dynamic and static risk connectedness in the median, extreme low, and extreme high quantiles arguing that spillovers vary across different time periods particularly during economically intense time periods. Finally, we analyzed the hedge ratio and hedge effectiveness between green bonds and other assets. We find that equi-correlations are intense during economic shocks such as the Shale oil crisis, Brexit, US interest rate hike, and COVID-19 pandemic. The volatility analysis at average, lower, and upper quantiles also validate time-varying attributes of green and conventional assets. Further, network figures of green and conventional assets identify potential diversification opportunities. Meanwhile, the hedge effectiveness indicates that green bonds are effective hedge for precious metals and cryptocurrencies. Our findings draw multiple implications for policymakers, green investors, financial market participants, and regulatory authorities regarding flight-to-safety during crisis times and maintaining a diverse portfolio to escape potential losses.

Tail risk dependence, co-movement and predictability between green bond and green stocks

This paper examines the coherence of extreme returns between green bonds and a unique set of green stocks. We use the novel quantile cross-spectral coherence methodology of quantile spectral coherency model, cross-quantilogram correlation approach, windowed time-lagged cross-correlation, and windowed scalogram difference models as estimation techniques. The study period spans from 28 November 2008 to 23 September 2020. Our measure of green stocks comprises the constituents of the MSCI Global Environment Price Index: Alternative Energy, Green Building, Pollution Prevention or Clean Technology while our green bond market is proxied by S&P Green Bond Index. We find the dependency between Green Bonds and green stocks to be weak, and this is high during market downturn periods in the short- to medium-term dynamics. This suggests that Green Bonds do act as a hedge, diversifier, or safe-haven instrument for environment portfolio in the short-term, medium-term and long-term dynamics during bearish market conditions. We conclude that green bonds and green stocks are two distinct asset classes with a distinct risk-return profile despite their common climate-friendly nature.

How COVID-19 pandemic, global risk factors, and oil prices affect Islamic bonds (Sukuk) prices? New insights from time-frequency analysis

This paper studies the time?frequency co-movement among Islamic bond (Sukuk) prices, the recent spread of COVID-19, oil prices, economic policy uncertainty, global financial uncertainty, and global financial distress. The Dow Jones Sukuk Index (hereafter DJSI) is used as a proxy of the global Sukuk market. The Malaysian Sovereign Sukuk index is also used for comparison purposes because Malaysia maintains a leading position as the strongest global player in Islamic finance. The effect of global risk and uncertainty factors on Sukuk prices is controlled for using partial wavelet coherency. The empirical results indicate that the co-movements between the Sukuk prices (both global and Malaysian Sukuk) and global economic and financial risk factors are time and frequency varying. We also find that global and Malaysian Sukuk markets behave differently with global risk factors throughout the COVID-19 pandemic period. Furthermore, we find that the co-movement between Sukuk prices (both global and Malaysian Sukuk) and COVID-19-infected cases is stronger only in the short term.

Comparing the asymmetric efficiency of dirty and clean energy markets pre and during COVID-19.

In the backdrop of the recent COVID-19 pandemic, the study examines the comparative asymmetric efficiency of dirty and clean energy markets pre and during the COVID-19 pandemic. For this purpose, we utilize an asymmetric multifractality detrended fluctuation analysis (A-MF-DFA). The study's findings uncover the presence of asymmetric multifractality in clean and dirty energy markets. In addition, multifractality in the energy markets is sensitive to trends, time horizon and major events. More importantly, the results suggest superior efficiency of clean-energy markets compared to conventional energies. We confirm the time-varying nature of market efficiency in the energy markets, and during the recent COVID-19 outbreak, market inefficiencies in the clean and dirty energy markets soared. In this way, the study holds meaningful insights for policymakers, energy policy practitioners, investors, and financial market participants to choose between clean (dirty) investments based on their asymmetric efficiency (inefficiency).

Dynamic connectedness and spillovers between Islamic and conventional stock markets: time- and frequency-domain approach in COVID-19 era.

This study investigates the dynamic connectedness and spillovers between Islamic and conventional stock markets to reveal the time- and frequency-domain dynamics of the two asset classes under various market conditions. Using the spillover index of Baruník and Krehlík (2018), supplemented by the time-varying parameter vector autoregressions (TVP-VAR) connectedness model, we employ daily stock market indices for Islamic and conventional (G7) markets from November 23, 2015, to September 8, 2021. The findings explicate that the volatility spillovers across and within Islamic and/or G7 markets are time-varying and frequency-dependent but during market turbulences, the conventional stocks are prone to more volatilities than the Islamic stocks. Our findings additionally divulge contagious spillovers among Islamic and conventional stocks during Brexit and the studied COVID-19 period. Relative to mid-and long-term spillovers, we underscore the supremacy of short-term spillovers between Islamic and G7 markets. In turbulent trading periods, investors should utilise knowledge about market patterns and volatility to hedge their positions against lower stock returns, when spillover is more intense. Regulators should pay close attention to spillovers since they undermine cross-market connections. Intriguing findings and their implications are further discussed.

Dependence structure and dynamic connectedness between green bonds and financial markets: Fresh insights from time-frequency analysis before and during COVID-19 pandemic

This paper examines the interdependence between green bonds and financial markets in the time-frequency domain by utilizing the multivariate wavelet approach and dynamic connectedness through combining Ensemble Empirical Mode Decomposition (EEMD) with Diebold and Yilmaz (2012) spillover framework. The findings of wavelet multiple correlations indicate that the benefits of diversification opportunities are more evident in the short run. The evidence of wavelet multiple cross-correlations reveals that green bonds and financial markets are highly integrated in the long run. The results of the static connectedness framework explain that the direction and magnitude of spillover behave differently across markets. The world stock market is the net spillover transmitter, while the corporate bond market is the net spillover receiver among the selected markets. The green bond market is receiving more but transmitted less volatility in the present study. The evidence on dynamic connectedness measured by the rolling window approach shows that the interconnection between green bonds and financial markets is volatile over time. These pieces of evidence provide implications to global investors having a strong position in the green bonds market in terms of risk management and portfolio decisions.

The Spillover of Inflation among the G7 Countries

Many global shocks, including the renegotiation of NAFTA, the United States–China trade war, the Brexit, and the COVID-19 pandemic, may have recently influenced the inflation spillover in the G7 countries. The current literature overlooks the influence of these important events on the inflation spillover of the G7 countries. This study fulfills this gap and investigates the nature of inflation spillover in the short, medium, and long term. Using the monthly data from 1956:6 to 2020:12, the study finds that Japan and the United States are the main transmitters of inflation. International trade, purchasing power parity, low-cost technology, and the Abenomics policy were found to be responsible for the inflation spillover. We suggest that the central banks of these countries collaborate to achieve the targeted inflation rate.

Dynamic Connectedness and Portfolio Diversification during the Coronavirus Disease 2019 Pandemic: Evidence from the Cryptocurrency Market

This paper examines interlinkages and hedging opportunities between nine major cryptocurrencies from 30 September 2015 to 4 June 2020, a period which notably includes the COVID-19 outbreak lasting from early 2020 to the end of the sample period. Estimated time-varying correlation coefficients that are based on a TVP-VAR show a high degree of interconnectedness among cryptocurrencies throughout the sample period. Notably, the correlations reach their joint minimum during the COVID-19 pandemic indicating that cryptocurrencies acted as a hedge or safe haven during the stressful period of the COVID-19 pandemic. The cryptocurrency weights of the minimum connectedness portfolio were significantly reduced and their hedging effectiveness varied greatly during the pandemic, implying that investors’ preferences changed during the COVID-19 period.

Revisiting the sustainable versus conventional investment dilemma in COVID-19 times.

Sustainable living has emerged as the need of the hour for mankind in present times. Practitioners, as well as scholarship in the area, are divided over the comparison of financial returns from sustainable indexes vis-à-vis conventional indexes, causing investors' dilemma. These questions loom larger during the times of global crises, such as COVID-19, which have brought sustainability concerns to the limelight. This dilemma of the investors leads us to approach the study on hand. We study the Thomson Reuters/S-Network global indexes (as a proxy for sustainability-based indexes), and their corresponding alternatives, using the daily closing prices from 1st January 2011 to 29th June 2020. We apply the time-frequency-based Granger-Causality test, and further attempt to understand the coherence between these indexes before and during the COVID-19 period by using the Wavelet Coherence and phase-difference mechanisms. Our results suggest short-run uni-directional causality from sustainable indexes to conventional indexes whereas bi-directional causality in medium and the long-runs. The coherence is particularly stronger at low frequencies, indicating the long-run coherence with sustainable indexes in the lead during COVID-19. The results and conclusions of the study have important implications for different audiences. The portfolio and fund managers can prefer to invest in such markets to avail of higher returns over a longer period.