Significant Volatility Spillover Effects Research Articles

Can carbon emission trading markets reduce the risks in traditional energy markets?

As the largest energy consumer in the world, China maintains a tightly interconnected energy market in the international arena. Therefore, it is necessary to explore the interdependence and spillover effects between the carbon emissions trading markets, traditional energy markets in China, and International markets. We explore changes in risk in the Chinese energy market with the introduction of the Chinese carbon market by employing the Vine Copula function to construct a vine structure and analyse the complex interdependence among markets. Moreover, we utilise the Time-Varying Parameter Vector Auto Regression and Diebold-Yilmaz Spillover Index (TVP-VAR-DY) method to examine the dynamic spillover effects of risk across various markets. Empirical analyses reveal a strong interdependence between the carbon emissions trading market and the traditional energy market. The Brent crude oil market occupies a central position within the system and significantly influences other markets. The carbon emissions trading market on the periphery has little impact on the system. Additionally, significant volatility spillover effects—observed between the carbon emissions trading market and traditional energy market systems—are closely correlated with economic conditions and extreme events, demonstrating time-varying characteristics. Furthermore, the Chinese carbon emissions trading market effectively reduces risk spillover in traditional Chinese energy markets from international markets during periods of risk contagion, particularly during times of high volatility, which can offer policymakers a novel path for risk management and provide investors with new avenues for investment hedging strategies.

Is China’s hog futures market effective? Based on the perspective of price discovery and hedging functions

ABSTRACT Based on daily data of China’s hog futures and spot prices from January 2021 to October 2023, this paper uses VAR-GARCH-BEKK to test the effectiveness of China’s hog futures market. The results of the study indicate that there is a two-way positive leading relationship between the hog futures market and the spot market. There is a significant two-way volatility spillover effect between hog futures market and hog spot market, but the hedging performance of hog futures is poor. Therefore, the effectiveness of China’s hog futures market needs to be further improved.

Study on The Impact of Shanghai Crude Oil Price Volatility and Stock Indices of China's Oil-related Industries

This paper takes Shanghai crude oil futures price and the industry stock index related to it as the research object, and selects the daily data from March 26, 2018 to December 31, 2022, and adopts the BEKK-GARCH model. To explore the correlation between Shanghai crude oil futures price volatility and different segmented industry stock markets. It is found that there is a significant asymmetric volatility spillover effect effect between the vast majority of oil-related industry markets and the Shanghai crude oil market. Based on the relationship between Shanghai crude oil futures prices and oil-related industry stock indexes, investors can make investments based on the fluctuations of Shanghai crude oil futures prices, rationally study the changes in the stock prices of oil-related industries, and do not follow the market panic operations using futures to control risk. And with the oil industry chain related to a higher degree of industry, by increasing the asset allocation method, can effectively reduce risk.

Uncovering Systematic Risk in Crypto currency Markets: An Empirical Investigation Using DCC-GARCH Model.

This study presents an analysis of the occurrence of structural flaws and spillovers of volatility among eight popular digital currencies, such as Bit coin (BTC), Litecoin (LTC), Ripple (XRP), BNBPrice, DOGECOINPrice,ETHEREUMPrice, TETHERPrice, and USDCOINPrice. The analysis covers the period from December 25, 2019, to August 25, 2022, utilizing various statistical tests such as the Chow Breakpoint Test, Cumulative Sum test, The Granger Causality Test, the LM test for ARCH, and Dynamic Conditional Correlation (DCC) GARCH model. The results of this research reveal being present structural breaks in all the evaluated cryptocurrencies, highlighting the unpredictable nature of the cryptocurrency market. Additionally, these cryptocurrencies exhibit notable volatility spillovers and substantial positive correlations, which point to limited benefits of diversification within the cryptocurrency market. (Chowdhury, 2020; Treiblmaier, 2018; Quispe, 2023). These results have implications for investors, policymakers, and other stakeholders in the cryptocurrency market. The study recommends including cryptocurrencies as an important component in investment portfolios to stimulate returns and reduce overall portfolio risks, it is noted that direct investment incryptocurrencies can generate higher abnormal returns, but this comes with increased risk due to their inherent volatility. Investor preference for firms involved in cryptocurrency is influenced by factors such as legal protection and familiarity. Thus, policymakers should prioritize financial stability and implement careful regulation of cryptocurrency-related announcements to prevent artificial premiums and fraudulent activities (Chowdhury, 2020; Treiblmaier, 2018; Quispe, 2023). Furthermore, the analysis highlights the presence of high volatility spillover effects among certain cryptocurrencies, particularly Bitcoin, Ethereum, and Litecoin.. While volatility offersdiversification advantages, concerns arise due to the lack of intrinsic value and dividends in cryptocurrencies (Özdemir, 2022). The presence of systematic structural breaks suggests the possibility of manipulative behaviors and potential trading strategies that warrant further investigation. The DCC GARCH analysis reveals a high correlation and significant volatility spillover effects among most cryptocurrencies. These findings emphasize the need for a more diversified cryptocurrency market to mitigate risk and promote stability within this emerging financial sector.

Comparative Study of Hedging Models in US

This study focuses on the use of three dynamic hedging models in the American stock market, and it computes the dynamic correlation coefficient, dynamic hedging ratio, and hedging effectiveness of three common models (DCC, BEKK, CCC). This paper fills in the gaps in the application and comparison of three hedging models commonly used in the US stock market during the pandemic. The results showed that NASDAQ index and futures were highly correlated and had significant volatility spillover effect before and during the epidemic. The hedging efficiency of the three models before the epidemic was higher than 0.931, and the hedging efficiency of the three models during the epidemic was higher than 0.936. It is proved that futures hedging is a good way to avoid risk no matter before or during the epidemic, and the highest hedging efficiency is dcc-garch.

Dynamic Volatility Spillover Effects and Portfolio Strategies among Crude Oil, Gold, and Chinese Electricity Companies

This paper examines the dynamic relationships and the volatility spillover effects among crude oil, gold, and Chinese electricity companies’ stock prices, from 2 December 2008 to 25 July 2022. By estimating the dynamic conditional correlation (DCC) model, we identify the time-varying correlation between crude oil, gold, and Chinese electricity stocks. Then, we use the time-varying parameter VAR model (TVP-VAR) to analyze the total and net volatility spillover effects. In addition, we compare the hedge ratio strategy and the portfolio weights strategy, as well as the corresponding hedging effectiveness among the crude oil, gold, and Chinese electricity companies. Considering the impact of the extreme events, we also extend the examination to the special period analysis of two crises, the Chinese stock market crash in 2015 and the COVID-19 pandemic in 2020. The results indicate that significant volatility spillover effects exist among crude oil, gold, and Chinese electricity companies’ stock volatility, and the total spillover effects show a sharp increase under the impact of the crisis. On average, gold is a much cheaper hedging tool than crude oil, whereas these two commodity assets remain net volatility receivers during the whole period and the crisis. However, it is worth noting that for specific assets, the impact of the crisis on spillover effects depends on the characteristics of crisis events and the assets analyzed. Additionally, most optimal weight strategies provide better hedging effectiveness than hedging strategies from the perspective of hedging effectiveness.

The impacts of infectious disease pandemic on China’s edible vegetable oil futures markets: A long-term perspective

For the extremely important role of China in global edible vegetable oil market and its decisive measures in the epidemic controlling and stable economic recovery during the COVID-19 pandemic, the aim of this article is to inspect the quantitative impacts of infectious disease pandemic on the returns, volatilities and correlations of China’s edible vegetable oil futures markets by using a DCC-MVGARCH-X model incorporating Baidu searching index as the proxy of pandemic severity. Our empirical results show that infectious disease pandemic does have significantly positive impacts on the returns and volatilities of China’s soybean, canola and palm oil futures markets. Second, there are significant volatility spillover effects among the three vegetable oils, suggesting strong contagion effect from one oil market to the others. Third, soybean oil and palm oil show the largest correlation, while the dependence between canola oil and palm oil is the smallest one among the three pairwise correlations. Moreover, no matter to consider epidemic situation in China or in global environment, infectious disease pandemic has significant effects on these correlations.

Spillover of international crude oil prices on China's refined oil wholesale prices and price forecasting: Daily-frequency data of private enterprises and local refineries

Compared with retail prices of state-owned companies used in almost all existing studies, China's refined oil wholesale prices of private enterprises and local refineries are more affected by the market and better reflect the real supply-demand situation. For the first time, this paper applies own-monitored daily-frequency wholesale prices of China's private enterprises and local refineries during 2013–2020 to derive spillover effects of international crude oil prices on China's refined oil prices through the VAR-BEKK-GARCH (vector autoregression-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroscedasticity) model, and then tries to forecast wholesale prices through the PCA-BP (principal component analysis-back propagation) neural network model. Results show that international crude oil prices have significant mean spillover and volatility spillover effects on China's refined oil wholesale prices. Changes in crude oil prices are the Granger cause of changes in refined oil wholesale prices. With the improvement of China's oil-pricing mechanism in 2016, the volatility spillover from the international crude oil market to China's refined oil market gradually increases, and the BRENT price variation has an increasing impact on the refined oil wholesale price variation. The PCA-BP model could serve as a candidate tool for forecasting China's refined oil wholesale prices.

RETRACTED ARTICLE: Social and economic analysis on the price spillover effect of agricultural products from the perspective of financialization: evidence from China’s oil and oilseeds industrial chain

The future price of agricultural products in the oil and oilseeds industry has direct impact on the spot price, therefore, it is important to understand the price transmission mechanism in the industrial chains to stabilize the production and to enhance the food security of a nation. This study aims to examine the spillover effects of the oil and oilseeds industry and the inter-industry agricultural products prices from the perspective of financialization and takes soybean and rapeseed industry chain of the oil and oilseeds industry as the research objects, using the six-element VAR–GARCH–BEKK model. The key findings are as follows: (1) there are difference mean spillover effects between the futures prices of products in each link of two industry chains, and there is a vertical spillover effect between product prices in each link of the soybean industry chain; and, (2) there is a significant two-way volatility spillover effect between the futures prices of products in each link of two industrial chains. In the future, to stabilize the price fluctuations of soybean and its alternative industrial chain, comprehensive measures may be considered, such as strengthening the international trade and cooperation of the oil and oilseeds industry, developing the derivative products of the oil and oilseeds alternative industry, and improving the intensive production of the oil and oilseeds industry.

Impact of cryptos on the inflation volatility in India: an application of bivariate BEKK-GARCH models

Purpose The main aim of the study is to explore the volatility spillover effect of cryptocurrencies (Bitcoin, Ethereum and Litecoin) on inflation volatility in India.Design/methodology/approach A popular tool, the Bivariate GARCH model (BEKK-GARCH), to study the volatility spillover effect, is applied in the study. Monthly data of cryptocurrencies and inflation (WPI and CPI indices) are gathered from 2015 to 2021.Findings Significant short-term responsiveness of volatility of cryptocurrencies on the inflation volatility is found. In addition to this, the significant volatility spillover effect from the cryptocurrencies to the inflation volatility is found.Practical implications The findings of the current paper can be of use for inflation management, target inflation policies and policies to contain the volatility of cryptocurrencies. The significance of the current paper is relevant as governments worldwide are officially recognizing cryptocurrencies and starting the process of launching their official virtual currency.Originality/value No other study is observed on the topic. Hence, the contribution and novelty of the findings of the current paper are very high and add value to the nonexistent literature on the topic. Lack of the number of inflation observations (data of CPI and WPI are available only in monthly frequency) crimps the model estimation. As the cryptocurrencies become old, more data points will be available by design, and such problems can be resolved, and better model estimation may be possible.

Major determinants of food price volatility in Turkey: inflation surge aftermath of 2016

Food price index is a crucial indicator for the stability of overall economic conditions in emerging markets since it has a considerable weight in regular spending of households. In the last decade, Turkey experienced higher food price inflation compared to consumer price index. In this context our main purpose is to provide useful insight for policymakers and governors to manage food price inflation. This paper undertakes the analysis of volatility and volatility spillover between Turkey Food Price Index (Turkey), Dollar-TL exchange rate (USDTRY), Turkish Producer Price Index of Agricultural (TRAGRIINP) and Turkish Food Price Index (World). The monthly data set covers the period 1 January 2000–31 December 2020. The results indicate that the volatility spillover effect between Turkish food price index and world food price index is more significant compared to the return spillover effect. Also, our results indicate a significant volatility spillover effect between Turkish food price index, exchange rates and world food price index exist in the short run while the effect vanishes in the long run. However, in the long run the main indicator for Turkish food prices index is Production Price Index of Agricultural Products after 2016 which is the milestone for the food price index surge.

Major Determinants of Food Price Volatility in Turkey: Inflation Surge Aftermath of 2016

Food price index is a crucial indicator for the stability of overall economic conditions in emerging markets since it has a considerable weight in regular spending of households. In the last decade, Turkey experienced higher food price inflation compared to consumer price index. In this context our main purpose is to provide useful insight for policymakers and governors to manage food price inflation. This paper undertakes the analysis of volatility and volatility spillover between Turkey Food Price Index (Turkey), Dollar-TL exchange rate (USDTRY), Turkish Producer Price Index of Agricultural (TRAGRIINP) and Turkish Food Price Index (World). The monthly data set covers the period 1 January 2000–31 December 2020. The results indicate that the volatility spillover effect between Turkish food price index and world food price index is more significant compared to the return spillover effect. Also, our results indicate a significant volatility spillover effect between Turkish food price index, exchange rates and world food price index exist in the short run while the effect vanishes in the long run. However, in the long run the main indicator for Turkish food prices index is Production Price Index of Agricultural Products after 2016 which is the milestone for the food price index surge.

The volatility spillover effect of the European Union (EU) carbon financial market

This paper modifies the BEKK-GARCH model based on the empirical results of the VAR model to analyze the dynamic volatility spillover effect between the European Union allowance (EUA) and certified emissions reduction (CER) markets during the second and third phases of the European Union Emission Trading System (EU ETS). The empirical results show that (1) an asymmetric volatility spillover effect exists between the EUA and CER markets and that the EUA market has a more significant volatility spillover effect on the CER market, and (2) the volatility spillover effect between the EUA and CER becomes weaker in phase III since the European Commission has limited the substitution of CER for EUA more strictly and the global carbon reduction requirements have become less demanding. Our study can help investors and managers of carbon market to have a more comprehensive understanding of the information and risk transmission mechanism between the EUA and CER markets, thus, providing them with a basis to make investment decisions and formulate policies.

Döviz Kurları ile BİST Turizm Endeksi Getirileri Arasındaki Volatilite Yayılım Etkisinin Belirlenmesi

The purpose of this study is to determine the volatility spillover effects between exchange rates and BIST Tourism Index (XTRZM) returns by using econometric methods. In this concept, the volatility spillover between USD, EUR, JPY, and GBP as highly convertible currencies and RUB, the currency of Russia which is a country that sends large amounts of tourists to Turkey, and BIST XTRZM returns has been analyzed by Diagonal VECH-GARCH method which is one of the multivariate GARCH models. The findings show that volatility has constant effects on XTRZM and exchange rates and volatility clusters are formed. According to the results of Diagonal VECH-GARCH model, statistically significant volatility spillover effects between USD/TRY, EUR/TRY, GBP/TRY and RUB/TRY exchange rates and XTRZM Index returns have been determined. According to the results of the analysis, there is no statistically significant volatility spillover effect between JPY/TRY and XTRZM Index returns. The findings of the study indicate that volatility in XTRZM index returns increased especially during periods of volatility in exchange rates.

The impacts of circuit breakers on China's stock market

In this paper, we empirically investigate the impacts of the circuit breaker mechanism installed in the Shanghai Stock Exchange using high-frequency intraday data. We find that trade impediments have liquidity effects. In the presence of circuit breakers, investors' behavior will accelerate the arrival of price limits. We also document significant downward magnet effects for individual stocks and for the market index but find no significant volatility spillover effects.

Dynamic Spillovers Between International Crude Oil Market and China's Commodity Sectors: Evidence From Time-Frequency Perspective of Stochastic Volatility

We study the time-frequency dynamics of stochastic volatility spillovers between international crude oil markets and China’s commodity sectors in the spectral representation framework of generalized forecast error variance decomposition (GFEVD). We find evidence that international crude oil markets has significant volatility spillover effects on China's bulk commodity markets, and the volatility spillovers are sensitive to extreme geopolitical or financial events. The net spillovers of international oil markets are almost positive and driven mainly by short-term components (within a week). However, uncertain financial factors from China such as the market-oriented reform in 2013 and the stock disaster in 2015 adversely affect the net oil-commodity volatility spillovers through the medium-term components (week to a month) and long-term components (month to a year). Moreover, the volatility spillover effects of crude oil prices on different commodity sectors in China are heterogeneous. Metal, coal coke and steel ore and energy commodity sectors are more affected by crude oil prices, while non-metal building materials and agricultural commodities are less affected. These outcomes implement necessary implications for investors and policymakers.

Volatility Spillover between Uncertainty in Financial and Commodity Markets and Turkish Stock Market

The aim of this study is to investigate risk spillovers between uncertainty about financial and commodity markets and Turkish stock market by using a causality-in-variance test. To this end, we use implied volatility indexes (the implied volatility of the gold, oil, stock, and currency prices from options markets) and Morgan Stanley Capital International (MSCI) Turkish stock market index. The volatility model estimates demonstrate that implied volatilities and Turkish stock market index are strongly influenced by long-run volatility. The causality-in-variance test results provide evidence of a significant one-way volatility spillover effect from uncertainty in financial and commodity markets to the Turkish stock market. The results suggest that Turkish stock market returns are highly sensitive to uncertainty shocks in global markets, and hence this high-sensitivity reduces the attractiveness of investments in the Turkish market. Our findings present important implications for the implementation of sound economic policies and for the formation of optimal portfolios.

Are global ethanol markets a ‘one great pool’?

The main objective of this empirical work is to test whether the global ethanol markets move together. To serve this purpose, prices of the US and Brazilian ethanol sectors have been analyzed. Employing the asymmetric multivariate GARCH model, we document significant price and volatility spillover effects between the ethanol markets under study. Such findings indicate that world ethanol markets move together and they are not regionalized. These results have important implications. For example, given that ethanol markets are codependent, information flow across ethanol markets could guide policymaking and the formulation of hedging strategies for contagion risk prevention during ethanol market downturns. In addition, this type of information on ethanol markets is also crucial for investors to maintain well-diversified portfolios, and for opening (closing) investment positions.

An Investigation of Dynamic Price Movements of the Cryptocurrency Coin in Korea

This paper investigates the dynamic price movements of cryptocurrency market in Korea by employing asymmetric DCC multivariate GARCH and risk decomposition model to reflect the time-varying integration process. We find that the law of one price does not hold between Korean and developed markets like U.S. and Japan, implying that emerging cryptocurrency market can be exploited as a scapegoat of arbitragers. Specifically, the price spreads of 20 to 30 percent between BTC-KRW and BTC-USD persist, exhibiting a sign of economic speculative bubble in Korean cryptocurrency market. Additionally, while there are significant price and volatility spillover effects between cryptocurrency markets of U.S. and Japan, the feedback effects do not exist in the case of Korean market. Our analyses also indicate that the pricing in Korea is mostly based on domestic factors rather than global factors. Finally, we show that this arbitrage opportunity in Korean market has disappeared after a government regulation, which includes banning foreigners and minors from opening new cryptocurrency accounts and prohibiting initial coin offerings (ICOs). The results suggest that a suitable regulation is important to eliminate bubbles.

High-frequency asymmetric volatility connectedness between Bitcoin and major precious metals markets

This study examines the asymmetric volatility connectedness between Bitcoin and major precious metals markets (gold, silver, palladium, and platinum). We use high-frequency data with methodologies introduced by Diebold and Yilmaz (2014) and Baruník, Kočcenda, and Vácha (2017). The results show evidence of significant volatility spillover effects between Bitcoin and precious metals. Moreover, the risk spillovers vary over time and are sensitive to slowdowns in economic activity and political events (e.g., the Brexit vote and the US presidential election). Palladium is the largest net contributor of spillovers while Bitcoin is a net recipient. Finally, evidence of asymmetry in semi-volatility transmission shows that Bitcoin heavily transmits net-positive spillovers to other assets. The results of our research are of interest and importance to investors, portfolio managers, and policy-makers, as the results can readily inform their decision-making.