Do volatility spillover effects vary across stock market crashes An empirical analysis

With the openness and marketization of China’s financial market accelerating, the linkage between various financial markets is increasingly significant. By utilizing VAR model and asymmetric GARCH (1,1)-BEKK model, this paper analyzes the price spillover effect and the volatility spillover effect among stocks returns, exchange rate of returns and money rate. The results show that 1) between currency market and stock market there is only unidirectional mean spillover effect from currency market to stock market; 2) however, there exists asymmetrical bidirectional mean spillover effect both between stock market and money market and currency market and money market, which exhibits time-varying variance and volatility persistence; 3) there exists bidirectional volatility spillover effect between currency market and money market, however there is only unidirectional volatility spillover effect from stock market to money market, which is demonstrated from money market to currency market.

According to the weekly return data of Shanghai composite index, China securities exchange index (net price) and SDR exchange rate index from December 2015 to May 2019, this paper respectively used the VS-MSV model to test the volatility spillover effect, and the CoVaR model to measure the volatility spillover effect in China's foreign exchange bond market. The empirical results show that there is an asymmetric two-way volatility spillover effect between the stock and the foreign exchange market in China, which is 124.7066% and 69.5448% respectively. Between the stock and the bond market, there is only one-way volatility spillover effect of the bond market on the stock market, and the volatility spillover effect is relatively small (2.5515%), while there is no volatility spillover effect of the stock market on the bond market. There is no spillover effect between bond and foreign exchange markets. In recent years, China's foreign exchange share and bond markets have been closely linked. Therefore, it is of great significance to study the spillover effect of fluctuations between foreign exchange share and bond markets to strictly guard against the bottom line of systemic financial risks.

PurposeSeveral studies focus on asymmetric impact of shocks on conventional stocks. However, only few studies explore Islamic stocks, but none has examined the asymmetric impact of shocks on Islamic stocks. This study aims to fill the gap by investigating the asymmetric impact of shocks on Islamic stocks. Specifically, it identifies the effect of good and bad news on Islamic stock market. The study also aims to examine the returns and volatility spillover effects across different Islamic markets.Design/methodology/approachTo carry out the empirical analysis, the authors have applied the exponential generalized autoregressive conditional heteroscedasticity (ARCH) model on daily Islamic stock indices of 18 countries. The study covers the period from July 2009 to July 2016. The authors have started their empirical analysis by examining the time series properties and testing the presence of ARCH effects. Further, the authors have applied several post-estimation tests to ensure the robustness of the results.FindingsThe results indicate that there is significant leverage effect in Islamic stocks traded in the sampled countries. That is, negative shocks or bad news have stronger effects on Islamic stock returns’ volatility as compared to positive shocks or good news. The authors also found that there are significant mean spillover effects for the examined countries. This finding implies that increased Islamic stock returns in country have significant and positive effects in Islamic stocks’ returns in another other. Similarly, the results regarding the volatility spillover effects suggest that there are significant volatility spillover effects across all examined countries. However, the authors found both positive and negative volatility spillover effects. It should also be noted that in some cases, the authors did not find any significant volatility spillover effect.Practical implicationsThe findings of this study have several important policy implications for both investors and policymakers. As the findings suggest that Islamic stock indices are integrated across countries both in terms of returns (mean) and risk (volatility), they are useful for investors to design well-diversified portfolios. The significant volatility spillovers suggest policymakers to design such policy that may help in reducing the adverse effects of increased volatility of Islamic stock of other/foreign countries on the Islamic stocks of the home countries. The significant evidence of the presence of leverage (asymmetric) effects suggest investors to use effective and active hedging instruments to hedge risk, particularly, in bad times.Originality/valueUnlike other studies on Islamic stocks, this study takes into account the asymmetric effects of positive and negative shocks. Further, the study examines the mean and variance spillover effects for a large panel of countries having Islamic stocks. Finally, several pre- and post-estimation tests are applied to ensure the robustness of the results.

The paper investigates mean and volatility spillover effects from the U.S and EU stock markets as well as oil price market into national stock markets of eight European countries. The study finds strong indication of volatility spillover effects from the US-global, EU-regional, and the world factor oil towards individual stock markets. While both mean and volatility spillover transmissions from the US are found to be significant, EU mean spillover effects are negligible. To evaluate the magnitude of volatility spillovers, the variance ratios are also computed and the results draw to attention that the individual emerging countries’ stock returns are mostly influenced by the U.S volatility spillovers rather than EU or oil markets. Additionally, examination of only global and regional stock markets spillover transmissions into European stock markets also confirms the dominating presence of the U.S spillover transmissions. Furthermore, I also implement asymmetric tests on stock returns of eight markets. The stock market returns of Hungary, Poland, Russia and the Ukraine are found to respond asymmetrically to negative and positive shocks in the US stock returns. The weak evidence of asymmetric effects with respect to oil market shocks is found only in the case of Russia and the quantified variance ratios indicate that presence of oil market shocks are relatively higher for Russia. Moreover, a model with dummy variable confirms the effect of European Union enlargement on stock returns only for Romania. Finally, a conditional model suggests that the spillover effects are partially explained by instrumental macroeconomic variables, out of which exchange rate fluctuations play the key role in explaining the spillover parameters rather than total trade to GDP ratios in most investigated countries.

Information transmission and dynamics of stock price movements: An empirical analysis of BRICS and US stock markets

<p>Volatility is an important component in the risk-return analysis of financial assets. It imparts liquidity to the financial system and also serves as an information source for rational decision-making. Since the latter half of the 20th century, volatility in stock returns has been found to be time-varying and exhibiting patterns and therefore, various models have been developed to capture such dynamic properties of volatility. The introduction of Autoregressive Conditional Heteroscedasticity (ARCH) models by Engle in 1982 has led to a better understanding of the behavior of stock market volatility than the traditional measures including standard deviation. The present study attempts to model various aspects including clustering, leverage effect, and spillover effect of stock market volatility in Indian and Chinese stock markets during 2001-2016 using daily time-series data with Generalised Autoregressive Conditional Heteroscedasticity (GARCH) models. Volatility has been seen to be highly persistent in both markets. The T-GARCH model has been applied in order to assess the presence of information asymmetry in that bad news impacts volatility more than good news. Our results reveal that both Indian and Chinese stock markets’ volatility shows time-varying behavior. The theoretical reasoning of the asymmetric impact of news that bad news affects volatility more than good news has been confirmed in both markets. Furthermore, the spillover effect of volatility across the two markets has been tested using the T-GARCH-X model. The results show a unidirectional spillover effect of volatility from the Chinese stock market to the Indian stock market. This implies that shocks from the Chinese stock market impact conditional volatility in the Indian stock markets only but not vice-versa.</p>

Focusing on whether “Through train of Hong Kong stock” has a significant impact on return and volatility spillover relationship between Hong Kong, Shanghai and Shenzhen stock market, this paper applies the VAR and Multiple GARCH model to the research based on the three stock markets data. The evidence shows that no return spillover effect exits between Hong Kong stock market and Shanghai or Shenzhen stock markets before the announcement of “Through train of Hong Kong stock”, while there is a one-way volatility spillover effect. Additionally, one-way return and two-way volatility spillover effect exist between Hong Kong and Shanghai stock market but one-way return and volatility spillover effects between Hong Kong and Shenzhen stock market after the announcement of “Through train of Hong Kong stock”.

Purpose This study aims to examine the spillover effects of the mean and volatility between oil prices and stock indices of six Gulf Cooperation Council (GCC) countries (UAE, Kuwait, Saudi Arabia, Qatar, Oman and Bahrain). Design/methodology/approach Over the period 2008–2019, a bivariate VARMA-GARCH-ADCC model was combined with the maximal overlap discrete wavelet transform technique filter to shed light on a wide range of possible spillover effects in the mean and variances of level prices at various time horizons. Findings The authors find that the spillover effects between oil prices and the GCC stock markets are time-varying and spread across various time horizons. Besides, oil prices and stock market indices are directly impacted by their own shocks and variations and indirectly influenced by other price volatilities and wavelet scales. The linkages in volatility spillovers between oil prices and the GCC stock markets occur in the short-term, midterm and long-term horizons. More specifically, the results also show that the asymmetric estimates are statistically significant for the associations between oil prices and each stock market in the GCC countries. This implies that negative shocks play a more vital role than positive shocks in driving the dynamic condition correlations between oil and stock markets under study. Practical implications The significant interrelatedness between oil prices and each stock market in the GCC countries has important implications for investors, portfolio managers, and other market participants. They can use the findings of this research to create the best oil-GCC stock portfolios and predict more precisely the volatility spillover patterns in constructing their hedging strategies. Originality/value In several ways, this study differs from previous research. First, while previous empirical studies of the dynamic link between oil prices and stock markets have focused primarily on developed or emerging markets, the focus of this is on six GCC countries. Second, the linkage between oil prices and stock markets is typically studied at the original data level in the time domain in relevant literature, while frequency information is overlooked. Therefore, the current study examines this relationship from a multiscale perspective. Third, in this paper, to capture a wide range of possible spillover effects in the mean and variance of level prices at multiple wavelet scales, the authors use a VARMA-GARCH-ADCC model in conjunction with wavelet multiresolution analysis. Additionally, this article also applies wavelet hedge ratio and wavelet hedge portfolio analysis at various time horizons.

This paper analyzed how economic variables affect the Chinese B-share market. For this purpose, we investigated the monthly data of major economic variables (consumer price index, imports and exports volume, money supply, real estate index and retail sales volume) and B-share price index of Shanghai and Shenzhen Exchange of China from 2009 to 2019 by employing the multivariate VAR-GARCH-BEKK model. We measured the return spillover effect between Chinese major economic variables and B-share market index from the estimation results of VAR conditional mean equation, and volatility spillover effect between the economic variables and B-share index from the estimation results of GARCH-BEKK conditional variance equation. From these results, we investigated whether there is any difference between the Shanghai and Shenzhen Exchange markets. The main findings are as follows. First, the return spillover effect does not exist in both markets except the Consumer Price Index (CPI). Second, there is the volatility spillover effect between economic variables and Shenzhen B-share market, implying that the volatility spillover effect is more important than the return spillover effect in the Chinese B-share market. Third, compared with Shanghai, the change of the Shenzhen stock market is more affected by the change of economic variables. These findings have some important policy implications. First, investors in Chinese stock market need to make good use of the information inherent in China’s economic changes to increase returns and reduce investment risks. Second, the investors should pay close attention to the overall trends of the Chinese economy and the global economy, not just to the trends of the Chinese market.

Oil is the basic factor of economic development, and its impacts of international crude oil market on stock markets have attracted wide attention from scholars. Based on the historical data of stock markets in China and the United States and international crude oil price during January 2003–December 2016, this paper employs the Vector Auto Regression-Generalized Auto Regressive Conditional Heteroskedasticity (VAR-GARCH) model to explore the mean and volatility spillover effects between international crude oil market and stock market. The results show that, first, there are two-way mean spillover effects between the US stock market and international crude oil market, while only one-way volatility effects from international crude oil market to the US stock market. Second, only one-way mean spillover effects from international crude oil market to Chinese stock market, and there is no evidence of volatility spillover effects between Chinese stock market and international crude oil market. The relationship between international crude oil price and China’s stock market shows a gradual strengthening trend, the linkage between them should not be ignored.

This study investigates the time–frequency dynamics of return and volatility spillovers between the stock market and three commodity markets: natural gas, crude oil, and gold via a comparative analysis between the United States and China is conducted with the help of new empirical methods. Our findings are as follows. First, in terms of time, return spillovers between crude oil and the stock market are strongest in two of the three commodity markets. Crude oil emits a net negative return spillover to the US stock market, and a net positive return spillover to the Chinese stock market. By contrast, the strongest volatility spillover effect is transmitted to the stock markets of both countries through gold. However, gold has a net positive volatility spillover effect on the US stock market and a net negative effect on the Chinese stock market. In the frequency domain, most of the return spillover is produced in the short term, and most of the volatility spillover occurs in the long term. In addition, the moving-window method reveals the dynamic nature of the spillover effect. Some extreme events can have a dramatic effect on the spillover index. Conversely, the spillover effect differs significantly between the two countries and is characterized by time variation and frequency dependence.

Tracing dynamic linkages and spillover effect between Pakistani and leading foreign stock markets

The volatility spillover effect between the foreign exchange and stock markets has been a major issue in economic and financial studies. In this paper, GC-MSV model was used to study the spillover effect between the foreign exchange market and the stock market after the reform of the RMB exchange rate mechanism. The empirical results show that there is a negative correlation of dynamic price spillovers between the foreign exchange and stock markets. There are asymmetric volatility spillover effects between these two markets for both RMB stages—continued RMB appreciation or constant RMB shock (a significant reduction in appreciation). However, this has been reduced over time. In conclusion, The RMB exchange rate is a key variable that can affect the internal and external equilibrium of the national economy in an open economic environment, and the stock market is capable of quickly reflecting subtle changes in the real economy. In order to keep the stability of the financial markets and the healthy and rapid development of national economy, some suggestions were proposed.

This study aims to examine the spillover effects of return and volatility between three different assets (Bitcoin, Gold, and Nasdaq) using GARCH-ARMA models. The data is taken from monthly closing prices from January 2015 to February 2024 through Investing.com. The analysis focuses on understanding how these three assets interact regarding the spillover effect of return and volatility, particularly during periods o f economic uncertainty. Our findings indicate that spillover effects o f return are visible from Bitcoin to Nasdaq, Nasdaq to Bitcoin, and Nasdaq to Gold. In addition, spillover effects o f volatility are visible from Gold to Bitcoin, Bitcoin to Nasdaq, Nasdaq to Bitcoin, and Nasdaq to Gold. Our finding highlights the dynamic relationship between traditional and digital assets, emphasizing Bitcoin's potential role as a financial hedge likely to Gold and Nasdaq.

In recent years, the rapid transmission of information and interconnectedness of global financial markets have amplified the convergence and influence among them. Consequently, the occurrence of spillover effects in one market can significantly impact other markets. Accurately identifying and understanding these spillover effects is crucial for effectively managing and controlling market fluctuations. This research aims to measure and analyze the spillover effects between China's stock market and selected emerging economies in the Middle East, with a focus on exploring diversification opportunities. The analysis encompasses three distinct time periods, including the overall period from May 1, 2005, to May 31, 2023. The sub-periods consist of the first sub-period from May 1, 2005, to October 31, 2009, and the second sub-period from December 1, 2010, to May 31, 2023. Multivariate Generalized Heterogeneous Autoregression (MGARCH) is employed in this study to examine the spillover effects between China's economy and the emerging economies under consideration. The Granger causality analysis reveals a unidirectional causality running from the Chinese stock market to Jordan, as well as from the UAE to China throughout the entire observation period. However, no spillover effects are found between China and Saudi Arabia in either direction during any of the periods. Notably, a two-way causality is detected between the Chinese and UAE markets in the second sub-period. Furthermore, MGARCH results indicate no spillover effects from China to the emerging economies during the overall period, first sub-period, or second sub-period. The findings of this research offer valuable insights for investment portfolio managers in the Chinese economy, who may consider the examined emerging economies as potential destinations for risk diversification.