Volatility Transmission Mechanism Research Articles

Agricultural commodities market reaction to COVID-19

This study examines the volatility transmission mechanism in agricultural futures returns during crisis periods, with a specific focus on the COVID-19 pandemic. The research employs the Markov Switching model to analyze the market dynamics of key agricultural commodities—cotton, sugar, rice, wheat, and corn. The study period is divided into three phases: Pre-COVID, COVID, and Post-COVID, allowing for a comprehensive analysis of market trends and shifts in response to the pandemic. Key findings reveal significant disruptions and heightened volatility in these markets during the COVID-19 period, with notable deviations from traditional market behaviors. The research reveals how various macroeconomic factors, such as the S&P 500, US 10-year Treasury bills, Brent crude oil prices, and the US Dollar Index, distinctly affect these commodity markets. Crucially, it sheds light on the dual nature of these markets, demonstrating both their resilience and susceptibility to worldwide disruptions, along with their recovery patterns following the pandemic. The policy implications of these findings are crucial for investors and policymakers. The study provides insights into managing and mitigating the impacts of global crises on essential commodities, emphasizing the need for robust strategies to navigate future market uncertainties. Additionally, the research contributes to the broader discourse on the interplay between macroeconomic conditions and agricultural market dynamics, offering valuable perspectives for informed decision-making in these sectors.

Volatility and Spillover Effects between Central–Eastern European Stock Markets and Energy Markets: An Emphasis on Crisis Periods

The objective of this paper is to study the spillover effects between energy markets and stock markets with emphasis on the significant crisis periods of the last 15 years, the period of the financial crisis that officially started in 2008, the pandemic period, generically called COVID-19, and the recent confrontation in Eastern Europe. Understanding the volatility transmission mechanisms between the energy and capital markets and also from the energy markets back and the spillover effects that result is very important. We use multivariate GARCH models to highlight a spillover effect between energy commodities and equities in Central and Eastern Europe. The highest correlations are recorded for CEE stock markets with electricity and Brent, and the lowest for CEE stock markets with gas. The biggest symmetric shocks between energy and CEE stock markets occurred during the COVID-19 pandemic. In contrast, the biggest asymmetric shocks occurred during the financial crisis (for gas) and the Ukrainian invasion (for Brent). We also find that volatility is more sensitive to its lagged values in the marketplace than it is to new information. The impact and contagion of shocks caused by the oil market are greater than those of other energy markets.

시간가변 전이효과를 고려한 글로벌 대체투자 자산들의 변동성 파급경로에 관한 연구

In this study, volatility spillover was analyzed based on the Time Varying Parameter VAR(Vector Autoregressive) model to identify the volatility transmission mechanism of alternative assets for the S&P Global Infrastructure Index, S&P Merger Arbitrage Index, and S&P U.S. SPAC Index.
 The results of the empirical analysis over the sample period are as follows: First, the total connectedness of the indices to be analyzed was estimated to be 27.22%, and the volatility spillover between the S&P500 and the Global Infrastructure Index was found to be quite high, whereas the index with the least connectedness to the S&P500 index was found to be the U.S. SPAC Index. Second, according to the net bidirectional connectedness estimation results, the most affected index was reported as the Merger Arbitrage Index, and the most affected index was reported as the Global Infrastructure Index. In addition, the U.S. SPAC Index was relatively neutral, confirming the possibility of contributing greatly to the portfolio diversification effect. Third, the total connectedness of the indices showed a behavior of rapidly increasing and then decreasing again at the time of the global spread of the coronavirus, but different movements were observed for each index, and the SPAC Index reacted more sensitively than other indexes.

The economic cost of environmental laws: Volatility transmission mechanism and remedies

Since the last three decades, the world has faced many changes that exhibit significant influence on natural resources, environmental laws, and the economic performance of various countries and regions. As the most developed country in the World, any policy adaptation of implementation in the US could influence the policies of other countries and regions. However, several factors could affect the country's economic performance, yet unexplored empirically, but are important from policy perspectives, which motivates this study. Therefore, the current study investigates the US's environmental laws, natural resource volatility, and economic performance from 1990 to 2020. The study used a novel wavelet methodology that considers wavelet power spectrum and wavelet coherence and provides short- and long-run estimates. The empirical results of the wavelet power spectrum reveal that environmental policy stringency and natural resource rents (total natural resource rents, natural gas rents, oil rents) are vulnerable in the selected time period. Additionally, the wavelet coherence empirically reports that there is a bidirectional causal association between environmental policy stringency, total natural resource rents, oil rents, and economic performance. In the short-run, the causality has been observed from these variables to economic performance, while from economic performance to these variables in the long run. Moreover, a unidirectional causal association runs from economic performance to natural gas rents. This study recommends strengthening environmental policy stringency and natural resources hedging to encourage economic performance and environmental sustainability.

Volatility spillovers across financial markets: the role of oil price uncertainty

ABSTRACT This paper analyzes the state-dependent volatility transmission mechanism between oil, stock, dollar, and bond prices to further examine the role of oil price uncertainty in financial markets. To this end, we extend the Diebold and Yilmaz (2014) spillover framework by incorporating a Markov-switching model and a Bayesian MCMC algorithm. We find that oil prices spills the highest degree of volatility to other markets during crises. The interdependence between the stock and oil markets is solid and stable, regardless of the regime shift. In contrast, the effect of oil price uncertainty on the foreign exchange or bond market during crises is double that during non-crisis periods. This suggests that oil price is closely related to other asset classes and reinforces its role as a risk transmitter during a crisis.

Volatility spillovers among G7, E7 stock markets and cryptocurrencies

PurposeThe existence of long memory and persistent volatility characteristics of cryptocurrencies justifies the investigation of return and volatility/shock spillovers between traditional financial market asset classes and cryptocurrencies. The purpose of this paper is to investigate the dynamic relationship between the cryptocurrencies, namely Bitcoin and Ethereum, and stock market indices of G7 and E7 countries to analyze the return and volatility spillover patterns among these markets by means of multivariate (MGARCH) approach.Design/methodology/approachApplying the newly developed VAR-GARCH-in mean framework with the BEKK representation, the empirical results reveal that there exists an evidence of mean and volatility spillover effects among Bitcoin and Ethereum as the proxies for the cryptocurrencies, and stock markets reviewed.FindingsInterestingly, the direction of the return and volatility spillover effects is unidirectional in most E7 countries, but bidirectional relationship was found in most G7 countries. This can be explained as the presence of a strong return and volatility interaction among G7 stock markets and crypto market.Originality/valueOverall, the results of this study are of particular interest for portfolio management since it provides insights for financial market participants to make better portfolio allocation decisions. It is also increasingly important to understand the volatility transmission mechanism across these markets to provide policymakers and regulatory bodies with guidance to eliminate the negative impact of cryptocurrency's volatility on the stability of financial markets.

The effects from the international crude oil returns to Asian frontier oil and gas company stock returns

Asian frontier markets present compelling investment opportunities for investors seeking higher returns and low correlation with traditional assets. As such, it is important for financial market participants to understand the volatility transmission mechanism across these markets in order to make better portfolio allocation decisions. This study investigates the magnitude of return and volatility spillovers from the international crude oil markets on the Asian frontier oil and gas stock markets. In particular, we construct mean return and volatility spillover models to discuss whether regional (DSE, CSE, HNX, HOSE) and global (ICE) market impacts are crucial for the determination of oil & gas stock returns in Bangladesh, Sri Lanka, and Vietnam by employing ARMA(1,1)-GARCH(1,1) model. Using daily returns from January 4, 2010 to December 31, 2019, the findings of this paper show that the Brent oil and WTI crude oil markets influence the Sri Lanka and Vietnamese oil and gas stock markets. WTI price changes, however, have a relatively minor impact on Sri Lanka companies. For Bangladesh, it is noticeable that none of the spillover effects is statically significant. The results are explained by different levels of the reform process in the energy sector as well as by the importance of oil in these markets. In general, these frontier markets, especially the Bangladesh and Sri Lanka may offer promising diversification benefits due to low correlations with developed equity markets. These results are important for economic policymakers and investors in understanding the magnitude of volatility spillover effects of the international crude oil on these markets. Investors can use this information to make better portfolio allocation decisions to reduce risks and enhance returns.

Realized volatility spillovers between US spot and futures during ECB news: Evidence from the European sovereign debt crisis

We study the simultaneity impact of the European Central Bank news on the daily realized volatility transmission mechanism (spillovers) among various US spot and futures markets. To this end, we apply a bias-corrected vector autoregressive model via Wild bootstrap simulation. We use minute-by-minute intraday data to construct daily realized volatility. We consider 429 news form the ECB as important events employing two major classifications, namely, a country classification with the highest total number of days related ECB news and a type of ECB news classification. We find that investors in futures markets react more vigorously and mainly for the ECB news that is associated with the group of EMU member states applied structural reforms. Yet, more importantly, we show that the US stock markets response heterogeneously to the ECB news, as we find key disagreements in the reactions both across the US markets and the types of ECB news studied. Such evidence is consistent with the explanation of the differential interpretation of information among market participants. From a practical point of view, we suggest that investors in the US spot market can effectively use two or more futures contracts to minimize their exposure to volatility risk associated with that news.

Risk Dynamics of Sectoral Stocks in BRICS Countries

This study attempts to contribute to the literature on risk exposures by investigating the dynamic volatility spillover transmissions and volatility co-movements between oil-risk factors and sectoral stocks in BRICS countries. A spillover index and DCC-GARCH estimation techniques are applied to identify the volatility transmission mechanism and co-movement among the series using daily data from 5th May 2007 to December 31st, 2016. To provide practical implications of the volatility transmissions, the estimated results are in turn used to compute and analyze the optimal weights and hedge ratios for oil-stock portfolio holdings. Our findings indicate the existence of significant volatility spillover interdependences and a time-varying volatility co-movement between oil-risk factors and sectoral stocks. However, the direction of spillover is shown to be somewhat unidirectional mainly from some selected sectors to oil-risk factors. Thus, we show that although volatility spillovers from oil-risk factors to sectors exist, the effect is at best, marginal. Finally, the optimal weights and hedge ratios show that oil-risk factors would be better suited as instruments for portfolio diversification rather than hedging to minimize oil price and portfolio risks which is important for risk management and diversification benefits.

Investigating the price volatility transmission mechanisms of selected fresh vegetable chains in Greece

PurposeThis paper attempts to model the transmission of volatility between producer and consumer prices in the fresh potato, tomato, and cucumber markets in Greece.Design/methodology/approachThe transmission mechanism of the price volatility is modeled using the most popular multivariate GARCH models while taking into consideration possible asymmetries in the transmission process. The models utilized are the DVECH and the BEKK models from the VECH family, as well as the CCC model and the DCC model from the family of conditional correlation models. The possible asymmetric effects are evaluated using asymmetric GARCH models, as well as estimating volatility impulse responses for independent shocks.FindingsThe results reveal that, in the tomato and cucumber markets, which are regulated by the Common Market Organization of fruits and vegetables, producers are less vulnerable to volatility shocks transmitted from consumers. In contrast, in the non-regulated potato market, producers are affected by spillover effects from consumers.Research limitations/implicationsThis study is limited to a few commodities (i.e. potatoes, tomatoes, and cucumbers); however, it could be extended to additional commodities.Practical implicationsThe results of this study show that, if producers are organized on a cooperative basis within the regulative framework of the CAP, like the tomato and cucumber producers, their place in the food supply chain is strengthened, although the CAP targets more market-oriented agricultural markets that are more exposed to world prices.Originality/valueThe present study attempts to understand the transmission of volatility between producer and consumer prices in the fresh potato, tomato, and cucumber markets in Greece, which is not apparent from previous studies. Furthermore, the volatility clusters that are identified in the present study are associated with certain CAP reforms.

Volatility impulse response analysis for DCC‐GARCH models: The role of volatility transmission mechanisms

AbstractThis study introduces volatility impulse response functions (VIRF) for dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) models. In addition, the implications with respect to network analysis—using the connectedness approach of Diebold and Y lmaz (Journal of Econometrics, 2014, 182(1), 119–134)—is discussed. The main advantages of this framework are (i) that the time‐varying dynamics do not underlie a rolling‐window approach and (ii) that it allows us to test whether the propagation mechanism is time varying or not. An empirical analysis on the volatility transmission mechanism across foreign exchange rate returns is illustrated. The results indicate that the Swiss franc and the euro are net transmitters of shocks, whereas the British pound and the Japanese yen are net volatility receivers of shocks. Finally, the findings suggest a high degree of comovement across European currencies, which has important portfolio and risk management implications.

The volatility transmission between crude oil market and tanker freight market

International crude oil and tanker shipping markets interrelate closely. Crude oil prices and tanker freight rates always fluctuate drastically, however the volatility transmission mechanism between the two markets have been ignored. The purpose of this study is to examine volatility transmission effects between the two markets by applying the BEKK-GARCH model on analysing Brent oil prices and Baltic Dirty Tanker Index. The index range was set from 18th January 2007 to 9th November 2015 covering the periods of financial crisis and oil price fall. Results show that volatility is mainly transmitted from crude oil market to tanker freight market from a long-term perspective, but not vice versa. Some bi-directional effects were found in tanker freight market that lagged variances and could affect the current variance in a counterpart market, regardless of the volatility transmission for some certain periods. The findings could help the practitioners better understand the market dynamics.

Dynamic transmission mechanisms in global crude oil prices: Estimation and implications

This study examines the dynamic behavior and spillover effects in global crude oil markets by introducing a connectedness measure based on the vector autoregressive model. Seven major crude oil prices are selected for the analysis on return and volatility connectedness and used to investigate information spillover and their dynamic linkages. Our empirical results suggest that the degree of market integration in global crude oil markets remains high over time although the total connectedness of the whole system varies substantially. In the international crude oil market, each price has shown to made distinctive contributions to the information flow of return and volatility networks. Specifically, the Brent and Bonny prices have played leading roles in explaining return dynamics over the whole sample, whereas the Dubai price has the highest hierarchy in the volatility transmission mechanism. In both the return and volatility networks, Asian oil prices are net receivers in the international oil market. Our findings shed light on global imbalance in the crude oil market pricing system, such as understanding the Asian Premium, and have important implications for forming portfolios to hedge oil market risks.

Volatility Impulse Responses for DCC-GARCH: The Role of Volatility Transmission Mechanisms

This study introduces volatility impulse response functions (VIRF) for DCC-GARCH models. In addition, the implications with respect to network analysis is illustrated by using the connectedness approach of Diebold and Yilmaz (2014) which rests on VIRFs. The advantage of this framework is that it does not underlie a rolling-window approach. An empirical analysis on the volatility trans- mission mechanism across foreign exchange rate returns is discussed. The findings point out that the CHF and the EUR are net volatility transmitters of shocks whereas the GBP and JPY are net volatility receivers of shocks.

On the risk spillover across the oil market, stock market, and the oil related CDS sectors: A volatility impulse response approach

Compared to Credit Default Swap (CDS) literature, this study focuses on the magnitude of volatility transmission and the risk spillover mechanism across the oil market, financial market risks, and the oil-related CDS sectors. Our dataset includes futures prices of West Texas Intermediate (WTI) and seven different measures of markets and credit risks. Four of the vast risk measures are the oil-related CDSs for auto, chemicals, natural gas, and utility sectors. In addition, three measures of the financial market risk, the one-month expected equity volatility measured by VIX, MOVE and SMOVE are included. The daily dataset covers the period from 6 January 2004 to 2 February 2016. The volatility transmission mechanism across the oil and financial markets and CDS sectors is examined using the volatility impulse response model. We evaluate the risk transmission due to several recent crisis shocks around the world and the results show complicated transmission mechanisms that spread over long periods. Among these events, the Lehman Brothers bankruptcy has destabilizing effects on all oil-related sectors. Findings also show that all oil market related shocks have significant risk transmission effects.

China–Africa financial markets linkages: Volatility and interdependence

The China–Africa relationship has blossomed in recent years and the scale and scope of Chinese engagement and investment in the latter have expanded enormously in the last decade. The purpose of this paper is to analyse the dynamic linkages and volatility transmission mechanisms between Chinese and African stock markets in recent years while highlighting the relative importance of Chinese capital flows and investments. We utilise dynamic forecasting models including Bayesian VAR and BEKK GARCH to estimate both price and volatility behaviours of Chinese and 15 selected African stock markets. Our empirical results indicate strong evidence of spillover effects in terms of both price movement and volatility behaviour, implying that Chinese and African stock markets are showing signs of integration. For price movement, bidirectional feedback relationships between Chinese and most of the African stock markets are observed, suggesting that both Chinese and African stock markets could influence each other. China has been building a strong African partnership and, therefore, increasing its trade and investment influences in the region. Examining volatility transmissions, at least one spillover effect (shock and/or volatility) from China to most of the African stock markets is reported. This suggests that the Chinese stock market now plays an influential role across African stock markets given that it has major investments in 46 out of 54 countries. Our findings show important portfolio management implications as a surge in Chinese investments provide new portfolio diversification opportunities for international investors. Policy-wise, we believe further market-oriented reforms and carefully designed and long-term development policies are required to boost capacity for development and achieve sustainable trade and growth.

A complex network for studying the transmission mechanisms in stock market

This paper introduces a new complex network to describe the volatility transmission mechanisms in stock market. The network can not only endogenize stock market’s volatility but also figure out the direction of volatility spillover. In this model, we first use BEKK-GARCH to estimate the volatility spillover effects among Chinese 18 industry sectors. Then, based on the ARCH coefficients and GARCH coefficients, the directional shock networks and variance networks in different stages are constructed separately. We find that the spillover effects and network structures changes in different stages. The results of the topological stability test demonstrate that the connectivity of networks becomes more fragile to selective attacks than stochastic attacks.

On Volatility Transmission from Crude Oil to Agricultural Commodities

The paper examines volatility transmission from crude oil market to agricultural commodities like wheat, corn, cotton and soybeans. We find that the volatility transmission from crude oil to agricultural commodities exhibits sudden changes over a study period. We also examine whether the sudden changes in volatility influence the observed sudden changes in volatility transmission from crude oil to agricultural commodities. Our results indicate the observed sudden change in volatility transmission mechanism is not influenced by sudden changes in volatility series.

Volatility Spillover and Time-Varying Conditional Correlation Between DDGS, Corn, and Soybean Meal Markets

In this paper, we seek to identify the price and volatility transmission mechanisms between DDGS, corn, and soybean meal markets to better inform market participants who wish to manage price risks in these three markets. Using weekly data from January 2000 to May 2016, we find important interplays between the three markets in both price and volatility dynamics. We uncover a stable long-run equilibrium between the three prices, and find that in the long-run, DDGS prices are positively correlated with both corn and soybean meal prices. However, corn and soybean meals are weakly exogenous — neither markets respond to deviations from this long-run relationship. We also find strong time-varying dynamic conditional correlations between the three markets, with the correlation between DDGS and corn strengthening between 2006 and 2012, the period when ethanol production in the US underwent massive expansion. Additionally, we identify significant volatility spillovers from both the corn and soybean meal markets to the DDGS market, with the impact from corn shocks much larger compared to soybean meal shocks. Corn appears to be the primary channel through which exogenous shocks are transmitted to the DDGS market. Our results also suggest that neither DDGS prices nor volatility significantly impact the corn and soybean meal markets.

Analysis of the Correlation Structure between Stock and Exchange Rate Markets: An Example of China on Asian emerging Markets

This study investigates the dynamic correlation between stock and exchange rate markets to examine the influences of China stock and exchange rate movements on other Asian emerging countries. We employ the GARCH model, which allows for the conditional correlation structure to be time-varying, to explore the return and volatility transmission mechanism between stock and exchange rate markets among these countries. Our results demonstrate that the China stock market has a greater positive impact on other Asian stock markets. We also find that the exchange rate movements of China have a positive effect upon the exchange rate markets of Singapore, South Korea, and Taiwan, but have no significant influence on the other countries. The test of volatility spillover shows that stock market movements do not affect exchange rate markets, which is a result that does not support Phylaktis and Ravazzolo (2005)’s evidence that stock market movements influence the exchange rate dynamics.