Return Spillovers Research Articles

Portfolio balance effect of the U.S. QE between commodities and financial assets in commodity-exporting countries

This study analyses the portfolio balance channel of the U.S. quantitative easing (QE) by assessing the dynamic spillover effect between commodities and financial assets in commodity-exporting countries during QE. This study integrates the generalized spillover index initially proposed by Diebold and Yilmaz (2012) for the fractional integration VAR model. Then, we estimate the multivariate framework of the Westerlund and Narayan (2015) (WN)-based predictive model to quantify the effect of the portfolio balance channel on the net pairwise spillover index from the U.S. to other countries. Our results show: first, for bond yields, that Asian and Pacific bond yields are impacted by both commodity price indices returns and the U.S. bond yields across the sample periods. However, mixed evidence is found for both Latin America and Others; second, for equity, dynamic net return spillovers contribute mixed evidence across regional groups during QE. The diverse results are partly explained by the average percentage of commodity exports to total exports of the country and the degree of close interrelationship between countries. Additionally, dynamic return spillover analyses show that most foreign exchange returns are negative net spillovers during QE, supporting the behavior of “commodity currencies.” Last, the WN-based predictability models show pronounced differences in predictability across the selected commodity-exporting countries.

Analyzing fossil fuel commodities' return spillovers during the Russia and Ukraine crisis in the energy market

During the Russia and Ukraine crises, the energy market, including fossil fuel commodities, experienced significant global shocks. This research paper investigates the phenomenon of return spillover across the energy market amid the Russia and Ukraine conflict, utilizing the Diebold and Yilmaz Spillover Framework and EGRACH Model. The study examines daily frequency data from 24 February 2022 to 30 June 2023, focusing on the interconnectedness between various energy commodities: Brent Oil, Carbon Emissions, Crude Oil WTI, Gasoline, Heating Oil, and Natural Gas. The result of the study reports a total spillover index of 36%, indicating a significant spillover during the Russia and Ukraine conflict. Furthermore, the highest dynamic gross directional return spillovers have been reported in Brent Oil compared to the others. However, carbon emissions and natural gas have the lowest spillovers. The study significantly contributes to a deeper understanding of energy commodities by confirming the volatility persistence across the energy market based on the E-GARCH model.

The impact of US-Sino trade war on commodity-currency nexus

This study attempts to assess the impact of US-China bilateral trade tension on commodity-currency nexus. Eleven exported commodities and two foreign currencies are selected for this purpose. With the application of cross-correlation functions, our results provide two notable findings. First, the return spillovers from the foreign exchange markets to most metal commodity markets are much more striking since the trade war began in 2018 under the former US President Donald Trump. Second, China’s rubber and the US soybean markets during the trade war are found to be dominant sources of volatilities in the USDCNY and CNYUSD exchange markets, respectively. Besides, the effect of shocks in the US soybean return during the trade war seems more measurable for CNYUSD exchange rate risk. To this end, our findings provide insights into the national level of investment and trade policy.

Impact of climate policy uncertainty on return spillover among green assets and portfolio implications

Green assets play a crucial role in addressing climate change, encompassing sustainable development, public health improvement, and climate risk mitigation. This study investigates the return spillover among green assets and examines the impact of climate policy uncertainty (CPU) on their interrelationship, using a quantile connectedness approach. Empirical results show that return connectedness among green assets is particularly strong during extreme events, with a surge in total connectedness attributed to increased spillover between the green bond market and other green assets. Additionally, CPU reduces the connectedness among green assets, favouring the idiosyncratic channel over investors' uncertainty channel. Based on these findings, we propose a CPU-driven portfolio rebalancing strategy for green investors to enhance diversification across green stock, green bond, and renewable energy markets. Simulation results demonstrate that the CPU-based portfolios outperform the buy-and-hold portfolio in terms of average monthly returns, standard deviation, and risk-adjusted returns. The research highlights the need for policymakers to acknowledge and address climate policy uncertainty, as it influences the interconnectedness of green assets, offering an opportunity to refine policy frameworks to better support stable and resilient investment environments conducive to sustainable development goals.

Terms of trade or market power? Further evidence from dynamic spillovers in return and volatility between Malaysian crude palm oil and foreign exchange markets

This study examines whether the Malaysian ringgit (MYR) provides terms of trade or market power for crude palm oil (CPO). We consider MYR exchange rates against three currencies of major CPO-importing countries, including the Indian rupee (INR), euro (EUR) and Chinese yuan (CNY). Using daily data on Malaysian CPO prices (spot and futures) and foreign exchange rates (INRMYR, EURMYR and CNYMYR) from 2000 to 2018, our results provide three notable findings. First, volatility spillovers from EURMYR to CPO spot and futures are more significant during the global financial crisis of 2008–2009. Second, the return spillovers from CPO spot and futures to INRMYR and EURMYR exchange rates experience significant bursts after the crisis. Third, the volatility of CPO spot price changes shows the predictive ability of the volatility of INRMYR exchange rate changes at the end of 2018. Overall, our findings support that the terms of trade are a driver of the CPO market after the crisis.

Connectedness among Chinese climate policy uncertainty, exchange rate, Chinese and international crude oil markets: Insights from time and frequency domain analyses of high order moments

This paper investigates the connectedness among the Chinese climate policy uncertainty, CNYUSD exchange rate, the Chinese crude oil and the international crude oil futures markets in terms of average return, volatility and high order moments. Meanwhile, different timescales and frequencies are also studied using Diebold and Yilmaz (2012) and Baruník and Křehlík (2018) approaches. The empirical results show that the connectedness among climate policy uncertainty, exchange rate and crude oil futures markets are time-varying and can be intensified by extreme events. The strength of connectedness depends on the moment order of spillovers. Covid-19 intensified the return, volatility and kurtosis connectedness. However, the impact of Covid-19 on higher order connectedness is relatively weak. In addition, the return spillovers are mainly caused by the short-term effect while higher order moment spillovers are driven by the long-term effect. Brent oil is the largest net shock transmitter and the Chinese crude oil futures mostly is the largest net shock receiver. Exchange rate is a net receiver except for kurtosis spillovers. The role of Chinese climate policy uncertainty is uncertain. In terms of the net pairwise connectedness, Chinese crude oil futures receives most shocks from Brent oil. In oil-exchange rate nexus, Chinese crude oil futures transmits shocks to the exchange rate in high order moment spillovers. The correlation between climate policy uncertainty and Chinese crude oil futures is time-varying. These findings offer useful implications for investors, policymakers and market supervisors.

Navigating environmental concerns and geopolitical risks: A study on green sukuk and Islamic equities amid climate crisis and the Russia-Ukraine conflict

Investors seek safe haven assets for portfolio diversification and risk management because climate change and environmental markets have recently become the concern of many governments, companies, households, politicians and academics. Therefore, this study examines the dynamic connectedness between sukuk (Islamic bonds), green sukuk, Islamic equities, and Islamic green markets for equity by comparing both in the short and long terms spillover and examining the effects of uncertainty factors on dynamic connectedness at different spillover horizons. In the short run, green Islamic equities, green sukuk and sukuk are net transmitters, and Islamic equities are net receivers. However, in the medium and long term, the behavior of these markets is vice versa. We then find the determinants of connectivity levels using macroeconomic conditions. We find that some of the determinants that cause return spillover in the short and medium term are quite different from those that cause return spillover in the long term. The results of portfolio analysis show that green sukuk are effective in hedging the risks of Islamic equities, green Islamic equities and sukuk. The performance characteristics of these potential diversification and risk mitigation benefits have been robust and enduring during the Covid-19 pandemic and the Russia-Ukraine War. Finally, our findings are of great importance to investors interested in ethical investing and for policymakers to maintain a healthy and resilient financial system.

Dynamic spillover between crude oil, gold, and Chinese stock market sectors –analysis of spillovers during financial crisis data during the last two decades

The present study investigates the presence of asymmetric return spillovers among crude oil futures, gold futures, and ten Chinese stock sector markets. Time-varying asymmetric spillovers between commodities and the 10 sectors are shown by utilizing the spillover index developed by Diebold and Yilmaz (2012, 2014). Our findings indicate that the industrial and discretionary consumer sectors generate and benefit the most from spillovers. Furthermore, it has been established that the basic materials sector exhibits a net positive impact on spillovers. In contrast, oil futures, gold futures, and other sectors demonstrate a net negative impact as recipients of spillovers. Moreover, the negative return spillovers outweigh the positive return spillovers. Our analysis spans from 2000 to 2023 to include various financial crises. The spillover effects of asymmetry are impacted by various factors, including the global financial crisis (GFC), the European sovereign debt crisis (ESDC), the decline in oil prices, and the outbreak of the COVID-19 pandemic. Including gold and oil in individual equity markets can benefit equity investors. Furthermore, implementing hedging strategies is susceptible to the global financial crisis, economic slowdown, oil price decline, and the recent COVID-19 pandemic. The oil futures exhibit the greatest hedging effectiveness during the COVID-19 spread. The findings indicate that gold exhibits comparable outcomes solely in the presence of positive spillover effects. At the same time, its performance reaches its peak during the recovery phase in the context of negative spillover effects.

Extreme Return Spillover Between the WTI, the VIX, and Six Latin American Stock Markets: A Quantile Connectedness Approach

Abstract This study examined extreme return spillovers and connectedness between crude oil (West Texas Intermediate), the Volatility Uncertainty Index (VIX), S&P 500, and six Latin American stock markets, namely, Argentina, Brazil, Chile, Colombia, Mexico, and Peru, using quantile connectedness. This approach allowed for a nuanced investigation of connectedness and added to the understanding the integration between these markets. The results indicated that the S&P 500 market was a full sender of spillover in the whole sample of the quantiles, when, to the contrary, the oil market was the highest receiver. The total spillovers were more intense during extreme quantiles, with swings between transmission and reception for VIX, Colombia, Mexico, and Peru. In addition, when the market turned to operate during bullish conditions, the VIX became a strong sender of spillover. Furthermore, an intense spillover was observed only in the lower and upper quantiles, and the spillover was sharper for the extreme upper quantile.

A Study on the Spill Over Effects on Nifty 50 Returns: Evidence from Stock Market Performances of Major Asian Counterparts of India

This study investigates the spillover effects of major Asian stock market performances on the returns of the Nifty 50, India's benchmark index. Employing advanced econometric techniques, we analyze the dynamic relationships between the Nifty 50 and key Asian counterparts, considering both short-term and long-term horizons. Our research delves into return spillovers aiming to comprehensively assess the interconnectedness and transmission of market movements across the region. This study utilizes an extensive dataset covering Nifty 50 returns from April 1, 2013, to March 31, 2023, along with meticulously documented returns from stock market indexes linked to major strategic alliances in India. By applying advanced multivariate time series analysis techniques, encompassing Vector Autoregression (VAR), Granger causality tests, and impulse response functions, we model the intricate dynamics interweaving these indexes with the Nifty 50. The research endeavors to answer fundamental questions, including assessing short- term and long-term effects resulting from major Asian counterparts of India on Nifty returns, as well as exploring noticeable patterns that indicate the direction of causality between these counterparts and Nifty returns. The outcomes of this study carry substantial implications for decision-makers. Investors can make more informed decisions, businesses planning strategic partnerships can refine their strategies, and policymakers can formulate economic and financial regulations that accurately reflect the complexities of these dynamics. By unveiling the ripple effects of these counterparts on the Nifty 50, this research offers valuable insights into the evolving dynamics of India's financial markets and their integration into the global economy.

Asymmetric and frequency-domain spillover effects among industrial metals, precious metals, and energy futures markets

We analyze asymmetric return spillovers in time and frequency domains across industrial and precious metals and energy futures markets using daily data for 18/05/2011–23/09/2020. Using the frameworks of Diebold and Yilmaz (2012) and Baruník and Krehlík (2018), we find that positive and negative spillover returns are symmetrical across analyzed markets, while being more pronounced during periods of economic turmoil or geopolitical unrest. Notable contributors of positive net spillovers are natural gas, diesel, zinc, and lead, while the most prominent negative net spillover receiver is gold. Findings will be of interest to investors, and portfolio managers.

An inferential spatiotemporal approach for knowledge synthesis to identify trends in public health research

BackgroundDecisions follow patterns that are introduced by human perception. Research and development (R&D) are influenced by these patterns. Furthermore, R&D publications can represent repetitive attempts to solve similar, or the same problems. Literature reviews serve as an important tool for identifying these trends, but they are time consuming. The time commitment of a literature review can be reduced by using a sample of research. This will allow an infinite population of research to be generalized. Additionally, spatiotemporal analysis is most appropriate for fields that follow time and geographic trends, such as public health. Also, using research locations to perform this analysis potentially captures the social return of R&D, as knowledge gained. As a result, an inferential spatiotemporal methodological framework is introduced to quickly identify research trends using public health research. This was applied to a childhood Pb exposure case study. MethodsA body of more than 1000 childhood elevated blood lead (Pb) level (EBLL) research articles were used to extract publication years, research locations, and subtopics. These publications were grouped into research locations (i.e., U.S. states where research was conducted; not publication location) and averaged over years published (i.e., 29 years). Binary indicator variables were derived using the subtopics extracted and the periods identified in time trend analyses. Explanatory variables were used to conduct hypothesis testing. Significant variables were used to generalize the population of the annual average EBLL articles written per state. ResultsThe range of the annual average of EBLL research articles by state was 0–1.7 articles, with a mean of 0.3 articles. Thirty-eight explanatory variables suggested a significant effect on research article production. These included temporal, sociodemographic, education, structure age, environmental, and economic variables. The strongest effect on research production for U.S. states came from the number of structures built before 1950. A predictive model was selected to generalize the population of articles using time-periods 1990-95, environmental subtopic, and structures built before 1950. The locations with the most research production for this topic were California and New York. The locations with the least research production for this topic were Alaska, Hawaii, Nevada, Wyoming, North Dakota, South Dakota, Mississippi, Delaware, and New Hampshire. ConclusionIf the trend for R&D is to make fast decisions, more human bias will be introduced into the decision-making process. Analytical tools that enable researchers to identify trends and ask more questions about their field will mitigate these biases. This hypothesis testing and predictive modeling methodology provide researchers and other decision makers with analytical tools they can use to quickly identify research trends and narrow their field of research. Additionally, this analysis potentially captures the impact of discovered ideas, as a social return spillover, for this topic.

The interconnected carbon, fossil fuels, and clean energy markets: Exploring Europe and China's perspectives on climate change

Carbon allowances represent a crucial financial instrument for mitigating the consequences of global warming and climate change. However, the feedback mechanism for Carbon-Energy- Finance systems introduces complexity due to the incorporation of equity, bond, and non- energy commodity assets. This study examines the volatility dynamics between carbon markets in Europe and China and their interactions with fossil fuel energy and clean energy indices. To measure this connectivity, we use advanced methodologies, such as the Diebold and Yilmaz method, to shed light on the complex relationships between these markets. Our study highlights significant disparities between China and Europe in terms of return spillover. In the short term, our results indicate that the Chinese carbon market acts as a receiver of shocks from other markets, while the European carbon market acts as a transmitter of shocks to various energy sources. In the specific contexts of China and Europe, these results provide valuable insights for policymakers and investors interested in tailoring approaches to sustainable energy transitions and financial stability.

Volatility and return spillovers between private equity buyout, venture capital and major financial markets

ABSTRACT This study investigates the volatility and return spillovers between Private Equity Buyouts (PE) and Venture Capital (VC), the equity market, precious metals, real estate, and the Dollar index, which has been widely ignored in the literature. We analysed daily data from 2 January 2004 to 29 December 2022 using Diebold and Yılmaz's (2012) framework. Our data covers the global financial crisis and the COVID-19 period and is rich enough to examine the linkages between the mentioned financial markets thoroughly. PE's higher connectedness with the equity market than VC’s is the main finding of this research. Besides, PE and VC have low connectedness to precious metals, real estate, and the Dollar index. In the sample period, VC is a net receiver, while PE is a net transmitter of volatility and return spillover. An exciting finding is that during the COVID-19 pandemic, VC experienced lower volatility spillover than PE from the broad market proxied by S&P 500. Investors and portfolio managers can benefit from our results to better diversify their portfolios.

Oil, gold and international stock markets: Extreme spillovers, connectedness and its determinants

This study examines the lower and upper return spillovers and connectedness between important commodity (crude oil and gold) and main international stock markets using the quantile connectedness approach by Ando et al. (2018). The results show stronger return spillovers during bearish and bullish market conditions. Crude oil and gold are net receivers of return spillovers irrespective of quantiles. Furthermore, an intense spillover is observed during high stress periods including COVID-19 in March 2020, and global economic slowdown and the Brexit referendum of 2016, oil price crash in 2014–2016, Tapering Tantrum in 2013, and the subprime crisis of 2008. Moreover, the spillovers in lower quantiles are stronger than in upper quantiles. The volatility uncertainty index (VIX) has a negative impact on the connectedness index at low and median quantiles. Gold and economic policy uncertainty indexes have a positive impact on lower quantile spillovers. In contrast, oil uncertainty index has a negative impact on quantile spillovers. COVID-19 crisis has a positive impact on lower, medium, and upper spillovers.

Return and volatility spillovers between non-fungible tokens and conventional currencies: evidence from the TVP-VAR model

This study investigates the static and dynamic return and volatility spillovers between non-fungible tokens (NFTs) and conventional currencies using the time-varying parameter vector autoregressions approach. We reveal that the total connectedness between these markets is weak, implying that investors may increase the diversification benefits of their multicurrency portfolios by adding NFTs. We also find that NFTs are net transmitters of both return and volatility spillovers; however, in the case of return spillovers, the influence of NFTs on conventional currencies is more pronounced than that of volatility shock transmissions. The dynamic exercise reveals that the returns and volatility spillovers vary over time, largely increasing during the onset of the Covid-19 crisis, which deeply affected the relationship between NFTs and the conventional currencies markets. Our findings are useful for currency traders and NFT investors seeking to build effective cross-currency and cross-asset hedge strategies during systemic crises.

Return spillover across the carbon market and financial markets: A quantile-based approach

This study examines the dynamic risk contagion between carbon and financial markets in extreme market conditions using a freshly developed methodology for spillovers based on quantile VAR modeling. The empirical results suggest that risk spillovers between them are strengthened in extreme market states and reduce the ability of the carbon market to be used for risk hedging in portfolios. Second, there is heterogeneity in the direction and size of spillovers between carbon and financial markets under bull and bear market conditions. This study also reveals that financial and carbon market participants pay more attention to risk information gathered from left-tail events. Finally, the paper identifies the transmitters and receivers of risk spillovers separately. The stock market is an important source of risks, authorities should pay attention to it.

REVISITING THE DYNAMIC CONNECTEDNESS, SPILLOVER AND HEDGING OPPORTUNITIES AMONG CRYPTOCURRENCY, COMMODITIES, AND ISLAMIC STOCK MARKETS

The study investigates the dynamic interconnections and opportunities for hedging among cryptocurrency, commodity, and Islamic stock markets using DCC-GARCH and Spillover connectedness models. Using daily data covering the Russia-Ukraine war and COVID-19 outbreak from December 1, 2019 to April 15, 2022, we document weak and frequently negative correlation between Bitcoin and Islamic stock markets. Thus, Bitcoin could be viewed as a haven from Islamic stock market losses. The results also indicate that Bitcoin's diversification benefits are normally steady and increase considerably during turbulence. Furthermore, the net return spillovers from the Bitcoin market remain above zero during most of the study period. We also find that utilizing Bitcoin as a hedge during the COVID-19 pandemic phase leads to higher expenses. The outcomes of this investigation are expected to carry substantial ramifications for Indonesian investors and portfolio managers who adhere to Shariah law since they will enable them to comprehend the advantages of diversifying portfolios across various periods of stock holding or investment horizons.

Return spillovers between decentralized finance and centralized finance markets

Return spillovers between decentralized finance and centralized finance markets

Riding the waves: A study of return spillovers and inter-sector linkages in US equity markets during the COVID-19 pandemic

In times of crisis, stock markets experience a significant increase in return volatility, which leads to spillovers across equity sectors. The purpose of this study is to investigate the asymmetric spillovers across ten U.S. equity sectors, representing different industries. Daily prices of sector indices were collected from 02 January 2018 to 22 October 2021 for the analysis. In addition, the study applied Diebold and Yilmaz's (2012) dynamic spillover methodology, along with the static and rolling windows phenomena, to examine the daily returns spillovers across sector indices. The results indicate that 82 % of volatility forecast error variance in U.S sector indices is due to the spillover effect. Moreover, both industrials and financials exhibit the highest gross spillovers to other sectors, while they also receive the highest spillovers from other sectors. Furthermore, the oil and gas sector and utilities sector receive the highest net returns spillovers. These empirical findings provide crucial information regarding the interdependence of U.S. sector indices during the COVID-19 pandemic, which is relevant for investors and practitioners.