Mean Spillover Effects Research Articles

Financial connectedness in BRICS: Quantile effects and BRICS SUMMIT impacts

This study examines the financial connectedness among BRICS using a two-step framework. In the first step, financial indices for each BRICS country are estimated by dynamic factor models in which three market characteristics and six sub-financial markets are considered. The estimated financial indices provide more comprehensive pictures of the financial markets in BRICS countries. Then we use the quantile variance decomposition model to discover the financial connectedness in BRICS. The study finds significant heterogeneity in financial connectedness among BRICS countries across quantile levels, with the tail spillover effects being stronger than the mean spillover effects. Russia is a risk transmitter while India is a recipient of risk during the crisis. We also find that the BRICS SUMMIT significantly strengthens the financial connectedness in the BRICS. The study provides international investors with new portfolio strategies and a risk-hedging perspective.

The Spillover Effects among Crude Oil Future Markets under High-Frequency Data Environment: Trivariate VAR-BEKK-GARCH Model Based on Wavelet Multiresolution Analysis

With the rapid development of financial globalization, the interconnection of international financial markets has deepened, and the relationship between domestic and international crude oil futures market price fluctuations has been increasingly strengthened. This paper utilizes 1-minute high-frequency price data of INE, WTI, and BRENT crude oil. By employing wavelet multiresolution analysis to address the ‘Calendar Effect’ present in intraday high-frequency data, and decomposing financial time series into different hierarchy of time scales. On this basis, the VAR-BEKK-GARCH model is established to study the spillover effect among the three crude oil future markets from the perspective of different trading cycles. The main conclusions of this paper are as follows: (1) The energy spectrum of wavelet multiresolution analysis shows that the price fluctuations of domestic and international crude oil futures are mainly reflected in the short-term trading cycles of 1-4 minutes; (2) The empirical results of the VAR-BEKK-GARCH model indicate that there are significant bidirectional mean and volatility spillover effects among INE, WTI, and BRENT crude oil in each trading cycle. Specifically, the mean spillover effect between INE and WTI markets shows that the short-term mean spillover effect of INE crude oil on WTI crude oil is larger, which is contrast to the medium- and long-term effect, and there is no significant pattern in the volatility spillover effect. The overall mean and volatility spillover effects of INE crude oil on BRENT crude oil are relatively larger. The overall mean and volatility spillover effects of WTI crude oil on BRENT crude oil are also relatively larger.

Comparing the EU and Chinese carbon trading market operations and their spillover effects

A carbon trading market (CTM) policy for trading carbon dioxide emission rights as a commodity was created to reduce greenhouse gas emissions. CTMs operate differently in different countries and regions, and their interactions deserve an in-depth study. This study focused on the world's largest CTM, the European Union (EU), and the CTM of China, largest carbon-emitting country. First, we evaluate the liquidity and volatility of the two CTMs. Subsequently, the VAR model is used to explore the mean spillover effect between the two markets and the BEKK-GARCH model is used to explore the volatility spillover effect between the two markets. The study concludes that: (1) The liquidity of China's CTM is better than that of the EU's CTM. (2) Both the EU and Chinese CTMs are unstable, but the volatility of the Chinese CTM is lower than that of the EU CTM. (3) Price changes in the EU and Hubei CTMs have a mutual influence. (4) There are interactions between the market fluctuations of the EU CTM and the Shanghai CTM and those of the EU CTM and the Hubei CTM. The results of this study have implications for the construction and development of CTMs in the EU and China.

Research on the Spillover Effect of China’s Carbon Market from the Perspective of Regional Cooperation

After the official launch of China’s unified carbon market, the potential for carbon emission reduction is huge. The pilot regional markets urgently need to be connected with the national carbon market to form a regional synergy and linkage mechanism and further promote the development of a unified carbon market. Spillover effects can be used to analyze the interaction between multiple markets. In this context, this study focuses on the overall spillover relationship among regional carbon trading markets. Using the VAR-GARCH-BEKK model and social network analysis (SNA), this study empirically analyzes the mean spillover effect and volatility spillover effect of regional carbon markets, and it establishes a spillover network between markets. The results show that the spillover effect of China’s regional carbon markets is widespread. Among them, the mean spillover effect is weak, and the impact period is short;. The volatility spillover effect is strong and has various directions; the spillover network connection between regional carbon markets is strong, but the spillover intensity is weak. Spillover effects will spread to the overall carbon market through information spillover paths and risk spillover paths. The stronger spillover effect and the stronger linkage between markets can bring more resource integration and unified supervision. Finally, we put forward policy recommendations, such as improving the carbon market mechanism and enhancing the maturity of carbon market development, increasing the participation and activity of the carbon market to encourage more participants to join the carbon market, improving the institutional system of the carbon market, and effectively supervising the process of information and risk spillover between carbon markets.

EXAMINING MEAN AND VOLATILITY SPILLOVER IN FOREIGN EXCHANGE MARKETS: THE TURKISH CASE

Bu çalışmada Euro, İngiliz sterlini, Japon yeni, Brezilya reali, G.Afrika randı, Meksika pesosu ve G.Kore wonu ile Türk lirası arasındaki getiri ve volatilite yayılımı Cheung-Ng (1996) testi ile incelenmiştir. Analizlerde volatilite serilerindeki yapısal kırılmalar da dikkate alınmıştır. Volatilitenin modellenmesinde FIGARCH modelinden, volatilite serilerindeki yapısal kırılmaların belirlenmesinde ise Bai ve Perron (1998, 2003) testinden yararlanılmıştır. Getiri yayılımına ilişkin bulgular; Japon yeni, İngiliz sterlini, Meksika pesosu ile G.Afrika randından Türk Lirasına doğru tek yönlü bir getiri yayılımının söz konusu olduğunu; Türk lirası ile Brezilya reali, Euro ve G.Kore wonu arasında ise çift yönlü bir getiri yayılımının bulunduğunu göstermektedir. Volatilite yayılımına ilişkin bulgular ise inceleme kapsamındaki tüm para birimlerinin volatilitesinin Türk lirası volatilitesi üzerinde etkili olduğunu, fakat Türk lirası volatilitesinin daha çok kendi iç dinamiklerinden kaynaklandığını göstermektedir. Çalışma bulguları hem uluslararası yatırımcılar hem de politika yapıcılar için önemli sonuçlar içermektedir.

Spillover effect of the RMB and Non-USD currencies after the COVID-19 pandemic: Evidence captured from 30-minute high frequency data

Amid the faster- and wider-than-expected spread of COVID-19, which has added new twists to the global economic outlook and profoundly impacted the performance of major currencies around the world, the RMB has been performing well, and thus, its market standing has improved. However, uncertainties about the future pose enormous challenges to the RMB internationalization. By processing 30-min high-frequency data, this paper aims to study changes in the characteristics of the relationship between the RMB and other non-USD currencies at five stages of the pandemic, first by means of auxiliary regression analysis, in which the pandemic is accounted for with a dummy variable, and then with a VAR-BEKK-GARCH model. The research shows that since the latter stages of the global pandemic, significant negative spillover effects among major non-USD currencies can be observed, while the independence of offshore RMB has increased gradually, and there have been weakening trends in the sustainability of the mean spillover and volatility spillover effects among other currencies. As the “regular pandemic prevention and control” begins to take hold in China and the geopolitical uncertainty increasingly outbreaks, the top priority in global currency market should be to resist the pressure of RMB independence with policy changes and increase caution in investing RMB assets.

A comparison of the operation of China's carbon trading market and energy market and their spillover effects

This study measures the liquidity and volatility of the operation of the carbon trading and energy markets using liquidity ratio indicators and log return indicators. It adopts China's carbon trading and energy markets as the research objects, and evaluates the mean spillover effects and volatility spillover effects between the two using the vector autoregression (VAR) model and the BEKK-MGARCH model. The findings indicate that: (1) The liquidity of China's carbon trading market is better than that of the energy market. The average liquidity ratio of the Hubei and Shenzhen carbon trading markets is much lower than that of the coal market, 43016.131. It may be attributed to the fact that China's carbon trading market is currently small and easy to regulate. (2) The volatility of both the Chinese carbon trading market and energy market is small, and the absolute values of the mean log return rate are close to 0. It could be because China's carbon trading market is mainly distributed through free quota allocation, while the energy market has been mature and stable for many years. (3) There is a spillover effect between the carbon trading and energy markets in some parts of China, but the direction and degree of spillover effect vary, which may be due to differences in the economic development level, energy consumption structure, and environmental policies of each pilot carbon trading region. (4) The spillover effect between the two markets is stronger, perhaps due to China's current model of using coal as the main fuel.

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.

Relationships between Copper Futures Markets from the Perspective of Jump Diffusion

This paper analyzes the price correlation effect between domestic and foreign copper futures contracts. The VAR-BEKK-GARCH (1,1) spillover effect model and the BN-S class non-parametric model based on the jumping perspective are used. The co-integration test shows a long-term equilibrium relationship between the three copper futures markets, and the Granger causality test shows that copper futures contracts have significant two-way spillover effects between different periods in Shanghai for New York copper and unidirectional mean spillover effects for London copper. The BEKK model shows significant bidirectional fluctuation spillover effects between the futures contracts of the Shanghai, London, and New York copper markets before the stock market crash. After the crash, Shanghai and New York copper have significant one-way fluctuation spillover effects on London copper futures contracts. There are jumps within a single market, and the number of joint jumps between markets increases with the significance level.

Time-varying Effects of U.S. Economic Policy Uncertainty on Exchange Rate Return and Volatility in China

ABSTRACT We examine the mean and volatility spillover effects of U.S. economic policy uncertainty (EPU) on the RMB exchange rate return and the effects’ time-varying features corresponding to the 2015 “8.11” RMB exchange rate reform and the Sino–U.S. trade friction. We find that rising U.S. EPU amplifies the RMB exchange rate return’s volatility at the volatility spillover level while driving the RMB’s appreciation against the USD at the mean spillover level. After the reform’s implementation, the U.S. EPU’s mean spillover on the RMB exchange rate return disappears, while the volatility spillover increases and is further enhanced by trade friction.

RETRACTED ARTICLE: Analysis of the hedging effect of financial futures based on improved machine learning algorithms

As a financial asset with multiple values, financial futures are widely welcomed by people, and many investors are willing to invest in and hold financial futures. However, although financial futures have good hedging characteristics, their prices will still be affected by external factors and fluctuate. The supplement to the existing mean spillover and volatility spillover effects enriches the research system on spillover effects in financial futures markets and helps to deepen the understanding of spillover effects in financial futures markets. Based on machine learning algorithms, this paper constructs an analysis model of the hedging effect of financial futures. Moreover, this paper combines financial theory for modeling and empirical analysis, and follows a simple to complex research strategy, and uses a combination of quantitative analysis and qualitative analysis to conduct research. In addition, based on the continuous quadratic variation theory, this paper combines the market microstructure noise model and the high-frequency financial measurement model to analyze the hedging effect of financial futures, and conducts research through examples. The research results show that the performance of the model constructed in this paper is good.

Directional Spillover Effects Between BRICS Stock Markets and Economic Policy Uncertainty

In recent years, researchers have increasingly studied the association between the stock market and economic policy uncertainty (EPU). To have more profound knowledge, this paper investigates the evolution of the mean spillover effects between EPU and BRICS stock markets by employing both the multivariate DECO-GARCH model proposed by Engle and Kelly (J Bus Econ Stat 30(2):212–228, 2012) and the spillover index of Diebold and Yilmaz (Int J Forecast 26(1):57–66, 2012). The results uncover that the average return equicorrelation between the BRICS stock indices and EPU is positive. In addition, there is a bidirectional return spillover between EPU and BRICS stock returns in the aftermath of the recent European debt crises and the global financial crisis. Overall, our results reveal the existence of the short term, the pass-through impact of EPU via stock price fluctuation in BRICS countries. These findings might provide significant implications for portfolio managers, investors, and government agencies.

Spillover effect between carbon spot and futures market: evidence from EU ETS.

The spillover effects ofEuropean Union Allowances (EUA) spot and futuresmarkets are important for investors in order to understand the relevance and risk management of product prices. This paper uses non-linear methods of Granger causality to test the mean spillover relationship between the two markets and then analyzes volatility spillovers between the two by the non-linear TVP-VAR spillover index. The results show that (1) the non-linear Granger causality test better reflects the mean spillover relationship between EUA spot and futures; (2) there is a bidirectional non-linear mean spillover effect between EUA spot and futures prices for the European Union Emissions Trading Scheme (EU ETS) phases II and III; and (3) volatility spillovers, appearing in EUA spot and future markets in both phases, work increasingly strong over time and are vulnerable to financial crises and extreme events.

An Analysis of Mean Spillover Effects of US-China Trade War on Sub-Saharan Africa

Since 2018, the United States of America increased import tariffs especially to trading partners like China. This was in response to a huge trade deficit leading to escalating the US–China trade war. The spillover effects of the US–China trade war on some leading Sub-Saharan African countries namely Nigeria and South Africa is worthy of consideration. Using the (1) autoregressive distributive lag methodology and (2) formulated four trade models for current account balance, trade balance, tariff rates and foreign direct investment (FDI) in the US–China–Africa saga provide this perspective. They show strong spillover effects on the current account balance model, tariff rates, and FDI relationships. Consideration of trade balance as an indicator showed insignificant results. The result is an endorsement of open trade because it contributes to economic success in so many ways.

Unveiling the Effect of Mean and Volatility Spillover between the United States Economic Policy Uncertainty and WTI Crude Oil Price

Grounded in the Granger causality test, vector autoregression (VAR) model, and BEKK-GARCH model, our current study aims to examine the effect of mean and volatility spillover between the United States (US) economic policy uncertainty (EPU) and West Texas Intermediate (WTI) crude oil price. Using the US EPU monthly index and WTI spot price data from 1996 to 2019, we revealed that there is a one-way Granger causality link between the US EPU and spot price of WTI crude oil. The VAR model not only illustrated that there is a mean spillover effect between WTI oil price and US EPU, but they will also be affected by its memory, as well as the other’s past. At the same time, it also pointed out that this correlation has positive and negative directions. The BEKK-GARCH model test yielded similar conclusions to the VAR model and, importantly, proved a two-way volatility spillover effect between the US EPU and WTI spot price fluctuations. In conclusion, US economic policy has a substantial influence on the variation of global crude oil prices, as an essential strategic reserve resource and will also influence the government’s economic policy formulation. Understanding the association between WTI crude oil price and policy uncertainty not only helps investors to manage assets allocations and mitigate losses but also guides US policymakers to adjust the energy structure for economic sustainability.

Is bitcoin a safe haven or a hedging asset? Evidence from China

Based on daily data about Bitcoin and six other major financial assets (stocks, commodity futures (commodities), gold, foreign exchange (FX), monetary assets, and bonds) in China from 2013 to 2017, we use a VAR-GARCH-BEKK model to investigate mean and volatility spillover effects between Bitcoin and other major assets and explore whether Bitcoin can be used either as a hedging asset or a safe haven. Our empirical results show that (i) only the monetary market, i.e., the Shanghai Interbank Offered Rate (SHIIBOR) has a mean spillover effect on Bitcoin and (ii) gold, monetary, and bond markets have volatility spillover effects on Bitcoin, while Bitcoin has a volatility spillover effect only on the gold market. We further find that Bitcoin can be hedged against stocks, bonds and SHIBOR and is a safe haven when extreme price changes occur in the monetary market. Our findings provide useful information for investors and portfolio risk managers who have invested or hedged with Bitcoin.

Long-Run Association Across Stock Markets in South-East Europe and Mean-Volatility Spillovers With Mature Markets

This paper explores the inter-market linkages and the transmission of financial information among the capital markets of five South-Eastern European countries and their relationships with some of the mature markets. The Johansen co-integration framework pointed to the existence of one co-integrating vector, but the results could not be validated through standard tests. The VAR model that included the mature markets as well, revealed certain causal dependencies among the markets. Positive and significant ARCH and GARCH effects were found to exist on all of the markets, except in Slovenia and mean spillover effects from Germany into all of the younger markets were identified, as well as between some of the younger markets themselves. Volatility spillovers were also confirmed in almost the same instances. The implication for the investors is that they should closely monitor the trends in the leading markets as a source of valuable information for the composition of their portfolios. For the policymakers, the knowledge of the direction of the impacts is important for the purpose of predicting future exogenous shocks. An additional value of the paper is that these five markets, their mutual relationships and the linkages with mature markets are jointly analysed for the first time.

Evidence of leverage effects and volatility spillover among exchange rates of selected emerging and growth leading economies

PurposeThe purpose of this study is to examine the evidences of leverage effects on the conditional volatility of exchange rates because of asymmetric innovations and its spillover effects among the exchange rates of selected emerging and growth-leading economies.Design/methodology/approachThe empirical analysis uses the sign bias test and asymmetric generalized autoregressive conditional heteroskedasticity (GARCH) models to capture the leverage effects on conditional volatility of exchange rates and also uses multivariate GARCH (MGARCH) model to address volatility spillovers among the studied exchange rates.FindingsThe study finds substantial impact of asymmetric innovations (news) on the conditional volatility of exchange rates, where Russian Ruble is showing significant leverage effect followed by Indian Rupee. The exchange rates depict significant mean spillover effects, where Rupee, Peso and Ruble are strongly connected; Real, Rupiah and Lira are moderately connected; and Yuan is the least connected exchange rate within the sample. The study also finds the assimilation of information in foreign exchanges and increased spillover effects in the post 2008 periods.Practical implicationsThe results probably have the implications for international investment and asset management. Portfolio managers could use this research to optimize their international portfolio. Policymakers such as central banks may find the study useful to monitor and design interventions strategies in foreign exchange markets keeping an eye on the nature of movements among these exchange rates.Originality/valueThis is one of the few empirical research studies that aim to explore the leverage effects on exchange rates and their volatility spillovers among seven emerging and growth-leading economies using advanced econometric methodologies.

Information Transfer Effect Among International Stock Markets

We examined the information transmission mechanisms in returns and volatility across international stock markets using the GJR-GARCH(1,1)-M models. In other words, we analyzed whether there is spillover effects of the mean, volatility and asymmetric transfer effect of information from the US regional equity index into Germany, Korea, Japanese, Nigeria and Republic of the South Africa equity market over the period July 1, 2010 and December 30, 2015. The main results are as follows. First, the mean spillover effects from US stock market are positive in stock markets of most countries(Germany, Korea, Japanese, Nigeria, Republic of the South Africa). Second, the volatility spillover effects from US are positive for equity index of Germany, Korea, Republic of the South Africa, Nigeria except for Japan. Finally, we find that asymmetric spillover effect of information exist, except for Nigeria, in the Germany, Korean, Japan and Republic of the South Africa stock markets. Therefore, bad news has a greater effect on the response than good news in most countries.