scholarly journals Volatility spillovers and time-frequency correlations between Chinese and African stock markets

2020 ◽  
Vol 10 (2) ◽  
pp. 63-82
Author(s):  
Ngo Thai Hung
Keyword(s):  
Stock Markets ◽  
Time Frequency ◽  
Volatility Spillovers

scholarly journals Spillovers to Renewable Energy Stocks in the US and Europe: Are They Different?

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3162 ◽  
Author(s):  
Tiantian Liu ◽  
Shigeyuki Hamori
Keyword(s):  
Renewable Energy ◽  
Stock Markets ◽  
Low Frequency ◽  
Investment Horizon ◽  
Stock Market Index ◽  
Energy Investment ◽  
Time Frequency ◽  
Volatility Spillovers ◽  
Financial Variables ◽  
The Us

This paper examines the spillovers of return and volatility transmitted from fossil energies (crude oil and natural gas) and several important financial variables (stock market index, bonds, and the volatility index) to renewable stock markets in the US and Europe under the time-frequency domain frameworks. The total spillovers of return and volatility from all variables to renewable stock markets in the US are higher than those in Europe. Stock markets transmit the highest return spillovers to renewable energy stocks, which far exceed the spillovers from fossil energy to renewable energy stocks in both regions. In addition, both return and volatility spillovers could be enhanced, possibly due to specific events or sudden changes in prices. In particular, extreme events such as the Brexit referendum in 2016 influenced mostly the volatility spillovers across European markets. Moreover, the spillovers of return and volatility are contingent on frequency, and most return spillovers are concentrated at the high frequency, whereas most volatility spillovers are concentrated at the low frequency. These results remind investors that it is necessary to consider the investment horizon when making their financial decisions on renewable energy investment.

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.

The lead-lag relationship between US industry-level credit and stock markets

2017 ◽  
Vol 44 (4) ◽  
pp. 518-539
Author(s):  
Syed Jawad Hussain Shahzad ◽  
Safwan Mohd Nor ◽  
Nur Azura Sanusi ◽  
Ronald Ravinesh Kumar
Keyword(s):  
Stock Markets ◽  
Financial Crises ◽  
Credit Markets ◽  
Credit Default Swap ◽  
Content Type ◽  
Time Frequency ◽  
Industry Level ◽  
Time Horizons ◽  
Arbitrage Opportunities ◽  
Daily Data

Purpose The purpose of this paper is to identify the arbitrage opportunities between US industry-level credit and stock markets with a focus on dynamic lead-lag relationships given that these markets involve heterogeneous agents operating over various time horizons. Design/methodology/approach The authors use daily data of 11 US industries stock markets and their credit counterparts to model the dynamic dependence and casual nexuses using time-frequency approach, namely, wavelet squared coherence (WTC). Findings The WTC estimation results show that credit and stock markets are out of phase (counter cyclical) and stock markets lead their credit counterparts. The coherence between two markets increases during financial crises. The banks (utilities) industry credit and stock markets have relatively high (low) dependence. Research limitations/implications The casual nexuses between stock and credit markets have multilateral dimensions. Greater interest in examining the relationship between stock markets and credit default swap (CDS) spreads emerged as an important albeit a complex area of research, and gained prominence especially at the onset and following the global financial crises of 2007-2008 which clearly showed that the positive views of CDSs contribution in creating a resilient and efficient financial sector was nothing further from the truth. Practical implications The arbitrage and hedging opportunities between stock and credit markets are industry dependent and vary over investment time horizons. The utilities industry seems attractive for the investment with the objective to exploit arbitrage, but not for hedging. Originality/value The paper, for the first time, employs time-frequency approach to assess the arbitrage opportunities between US industry-level credit and stock markets.

scholarly journals Linkages between gold and emerging Asian stock markets: New evidence from the Chinese stock market crash

2021 ◽  
Vol 39 (2) ◽  
Author(s):  
Imran Yousaf ◽  
Shoaib Ali
Keyword(s):  
Financial Crisis ◽  
Stock Market ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Chinese Stock Market ◽  
Stock Market Crash ◽  
Volatility Spillovers ◽  
Hedge Ratios ◽  
The Global Financial Crisis ◽  
New Evidence

This study examines the return and volatility transmission between gold and nine emerging Asian Stock Markets during the global financial crisis and the Chinese stock market crash. We use the VAR-AGARCH model to estimate return and volatility spillovers over the period from January 2000 through June 30, 2018. The results reveal the substantial return and volatility spillovers between the gold and emerging Asian stock markets during the global financial crisis and the Chinese stock market crash. However, these return and volatility transmissions vary across the pairs of stock markets and the financial crises. Besides, we analyze the optimal portfolios and hedge ratios between gold and emerging Asian stock markets during all sample periods. Our findings have important implications for effective hedging and diversification strategies, asset pricing and risk management.

scholarly journals The Effects from The U.S. and Japan to Emerging Stock Markets in Asia and Vietnam

2021 ◽  
Author(s):  
SDAG Lab
Keyword(s):  
Emerging Markets ◽  
Stock Prices ◽  
Stock Markets ◽  
Spillover Effect ◽  
Spillover Effects ◽  
The Philippines ◽  
Volatility Spillovers ◽  
Return Effect ◽  
Asian Emerging Markets ◽  
The U.S

The subprime mortgage crisis in the U.S. in mid-2008 suggests that stock prices volatility do spillover from one market to another after international stock markets downturn. The purpose of this paper is to examine the magnitude of return and volatility spillovers from developed markets (the U.S. and Japan) to eight emerging equity markets (India, China, Indonesia, Korea, Malaysia, the Philippines, Taiwan, Thailand) and Vietnam. Employing a mean and volatility spillover model that deals with the U.S. and Japan shocks and day effects as exogenous variables in ARMA(1,1), GARCH(1,1) for Asian emerging markets, the study finds some interesting findings. Firstly, the day effect is present on six out of nine studied markets, except for the Indian, Taiwanese and Philippine. Secondly, the results of return spillover confirm significant spillover effects across the markets with different magnitudes. Specifically, the U.S. exerts a stronger influence on the Malaysian, Philippine and Vietnamese market compared with Japan. In contrast, Japan has a higher spillover effect on the Chinese, Indian, Korea, and Thailand than the U.S. For the Indonesian market, the the return effect is equal. Finally, there is no evidence of a volatility effect of the U.S. and Japanese markets on the Asian emerging markets in this study.

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