Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging

2015 ◽  
Vol 50 (4) ◽  
pp. 1481-1509 ◽  
Author(s):  
Yudong Wang ◽  
Li Liu
Keyword(s):  
Crude Oil ◽  
Stock Markets ◽  
Volatility Spillovers ◽  
Dynamic Correlations

scholarly journals The COVID-19 Outbreak and Risk–Return Spillovers between Main and SME Stock Markets in the MENA Region

2022 ◽  
Vol 10 (1) ◽  
pp. 6
Author(s):  
Nassar S. Al-Nassar ◽  
Beljid Makram
Keyword(s):  
Saudi Arabia ◽  
Stock Markets ◽  
Practical Implication ◽  
Mena Region ◽  
Asymmetric Volatility ◽  
Volatility Spillovers ◽  
Dynamic Correlations ◽  
Stock Portfolio ◽  
Different Characteristics ◽  
Portfolio Design

This study investigates return and asymmetric volatility spillovers and dynamic correlations between the main and small and medium-sized enterprise (SME) stock markets in Saudi Arabia and Egypt for the periods before and during the COVID-19 pandemic. Return and volatility spillovers are modelled using a VAR-asymmetric BEKK–GARCH (1,1) model, while a VAR-asymmetric DCC–GARCH (1,1) model is employed to model the dynamic conditional correlations between these markets, which are then used to determine and explore portfolio design and hedging implications. The results show that while bidirectional return spillovers between the main and SME stock markets are limited to Saudi Arabia, shock and volatility spillovers have different characteristics and dynamics in both main–SME market pairs. In addition, the dynamic correlations between the main and SME markets are mostly positive and have notably increased during the COVID-19 pandemic, particularly in Saudi Arabia, suggesting that adding SME stocks to a main stock portfolio enhances its risk-adjusted return, especially during tranquil market phases. One practical implication of our results is that the development of SME stock markets can indirectly contribute to economic development via the main market channel and provide an avenue for portfolio diversification and risk management.

Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets

2021 ◽  
Vol 98 ◽  
pp. 105262
Author(s):  
Walid Mensi ◽  
Abdel Razzaq Al Rababa'a ◽  
Xuan Vinh Vo ◽  
Sang Hoon Kang
Keyword(s):  
Crude Oil ◽  
Stock Markets ◽  
Network Connectedness

scholarly journals Spillovers of Stock Markets among the BRICS: New Evidence in Time and Frequency Domains before the Outbreak of COVID-19 Pandemic

2021 ◽  
Vol 14 (3) ◽  
pp. 112
Author(s):  
Kai Shi
Keyword(s):  
Stock Market ◽  
Frequency Band ◽  
Stock Markets ◽  
Emerging Market ◽  
Low Frequency ◽  
Systematic Risk ◽  
Error Variance ◽  
Frequency Bands ◽  
Volatility Spillovers ◽  
Risk Sources

We attempted to comprehensively decode the connectedness among the abbreviation of five emerging market countries (BRICS) stock markets between 1 August 2002 and 31 December 2019 not only in time domain but also in frequency domain. A continuously varying spillover index based on forecasting error variance decomposition within a generalized abbreviation of vector-autoregression (VAR) framework was computed. With the help of spectral representation, heterogeneous frequency responses to shocks were separated into frequency-specific spillovers in five different frequency bands to reveal differentiated linkages among BRICS markets. Rolling sample analyses were introduced to allow for multiple changes during the sample period. It is found that return spillovers dominated by the high frequency band (within 1 week) part declined with the drop of frequencies, while volatility spillovers dominated by the low frequency band (above 1 quarter) part grew with the decline in frequencies; the dynamics of spillovers were influenced by crucial systematic risk events, and some similarities implied in the spillover dynamics in different frequency bands were found. From the perspective of identifying systematic risk sources, China’s stock market and Russia’s stock market, respectively, played an influential role for return spillover and volatility spillover across BRICS markets.

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