Spillovers of volatility index: evidence from U.S., European, and Asian stock markets

Shu, Hui-Chu; Chang, Jung-Hsien

doi:10.1080/00036846.2018.1540846

Cited by 35 publications

(24 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These results show the strong connectedness between the four implied volatility indices. However, the informative capacity of V IX stands out over other equity volatility indices, a finding that has been well-supported by recent literature [43][44][45] In the case of clean energy stocks, the total directional connectedness for most of the estimations was greater from V IX than from VSTOXX (see columns 3 and 4). VSTOXX was more crucial for only three European companies: Falckrenewables from Italy (C H AA4←VSTOXX = 4.81%), Siemens Gamesa Energy from Spain (C H SGRE←VSTOXX = 6.44%), and Vestas Wind Systems AS of Denmark (C H VWS←VSTOXX = 6.03%).…”

Section: Full-sample Analysissupporting

confidence: 76%

Dynamics of Connectedness in Clean Energy Stocks

Fuentes

Herrera

2020

Energies

View full text Add to dashboard Cite

This paper examines the dynamics of connectedness among the realized volatility indices of 16 clean energy stocks belonging to the SPGCE and the implied volatility indices of two important stock markets—the S&P 500 and the STOXX50—and two commodities markets—the crude oil and gold markets. The empirical results show a unidirectional connectedness from the implied volatility indices to the clean energy stocks. Our analysis further reveals similar volatility connectedness behaviors among companies in the same energy production subsector. However, there exists heterogeneous behavior between different energy production subsectors over time. Further, we identify pairwise directional connectedness clusters among related companies, indicating that there are few possibilities for portfolio diversification within the energy production subsectors. Finally, through an impulse–response analysis, we confirm that the expectation of future market volatility of the S&P 500 index and the gold price plays a leading role in volatility connectedness with clean energy stocks.

show abstract

Section: Full-sample Analysissupporting

confidence: 76%

Dynamics of Connectedness in Clean Energy Stocks

Fuentes

Herrera

2020

Energies

View full text Add to dashboard Cite

show abstract

“…Across panels B ( Figure 2) and C (Figure 3), the US, Germany, China continue to be the primary transmitters of fear over the short-and long-term horizons, while Japan, South Korea, and Hong Kong remain as the leading recipients of fear shock across the frequency bands. Being among dominant stock markets in the world and European stock markets, the US and Germany's fear shocks are more contagious towards other markets, a finding also supported by [7,19,21]. However, China is quite remarkable as one of the top transmitters of shocks of fear.…”

Section: Empirical Findingsmentioning

confidence: 91%

“…Using a copula-based bivariate Markov-switching model, the authors provide a strong evidence of dependencies, contagion, and causalities between the four implied volatility indices. Shu and Chang [21] investigated the cross-market interaction between implied volatility indices of the US, the Europe, and South Korean, and stock returns of the US and non-US markets. The authors found that the pervasive influence of VIX on both US and non-US stock markets.…”

Section: The Theoretical Issuesmentioning

confidence: 99%

Role of Economic Policy Uncertainty in the Connectedness of Cross-Country Stock Market Volatilities

et al. 2020

View full text Add to dashboard Cite

The implied volatility index is a forward-looking indicator of fear among stock market participants. We examine the extent to which the connectedness of fear among global stock markets is driven by the cross-country connectedness of economic policy uncertainty (EPU). We use data on stock market fear and EPU indices for 13 countries, which spans from January 2011 to December 2018. To measure the connectedness among stock market fear and EPU of our sample countries, we employ two connectedness models. A cross-sectional regression model is further employed to ascertain the extent to which EPU connectedness between two countries explains the connectedness of fear between their stock markets, while controlling for bilateral linkage and country-specific factors. We find that EPU connectedness between any two partner countries significantly drives the connectedness of fear between their stock markets. The driving potential not only holds for short- and long-term connectedness, but also after controlling for bilateral linkages (bilateral trade, geographical distance, common language) and country-specific (trade and financial openness of the transmitter country) factors indicating robustness in our results.

show abstract

“…Investigating the cross-market relations of volatility indexes with US and non-US stock market returns, Shu et. al [ 26 ] report a pervasive VIX influence at both US and non-US stock markets. They find that information flow is unidirectional from VIX to the stock market, being the VIX change a critical determinant of stock market returns.…”

Section: Vix and Stock Markets Behaviormentioning

confidence: 99%

“…Finally, when comparing the VIX versus other volatility indexes such as VSTOXX and VKOSPI, Shu et. al [ 26 ] show that VIX is the most significant contributor of spillovers towards other volatility indexes, pointing VIX with a leading role in the international markets. Similar results document Kang et.…”

Section: Vix and Stock Markets Behaviormentioning

confidence: 99%

The predictive power of stock market’s expectations volatility: A financial synchronization phenomenon

et al. 2021

View full text Add to dashboard Cite

We explore the use of implied volatility indices as a tool for estimate changes in the synchronization of stock markets. Specifically, we assess the implied stock market’s volatility indices’ predictive power on synchronizing global equity indices returns. We built the correlation network of 26 stock indices and implemented in-sample and out-of-sample tests to evaluate the predictive power of VIX, VSTOXX, and VXJ implied volatility indices. To measure markets’ synchronization, we use the Minimum Spanning Tree length and the length of the Planar Maximally Filtered Graph. Our results indicate a high predictive power of all the volatility indices, both individually and together, though the VIX predominates over the evaluated options. We find that an increase in the markets’ volatility expectations, captured by the implied volatility indices, is a good Granger predictor of an increase in the synchronization of returns in the following month. Estimating, monitoring, and predicting returns’ synchronization is essential for investment decision-making, especially for diversification strategies and regulating financial systems.

show abstract

Spillovers of volatility index: evidence from U.S., European, and Asian stock markets

Cited by 35 publications

References 23 publications

Dynamics of Connectedness in Clean Energy Stocks

Dynamics of Connectedness in Clean Energy Stocks

Role of Economic Policy Uncertainty in the Connectedness of Cross-Country Stock Market Volatilities

The predictive power of stock market’s expectations volatility: A financial synchronization phenomenon

Contact Info

Product

Resources

About