scholarly journals Volatility-Spillover Effects in European Bond Markets

2003 ◽  
Author(s):  
Charlotte Christiansen
Keyword(s):  
Spillover Effects ◽  
Bond Markets ◽  
Volatility Spillover

scholarly journals Volatility Spillovers between Equity and Green Bond Markets

2020 ◽  
Vol 12 (9) ◽  
pp. 3722 ◽  
Author(s):  
Daehyeon Park ◽  
Jiyeon Park ◽  
Doojin Ryu
Keyword(s):  
Equity Markets ◽  
Spillover Effects ◽  
The Other ◽  
Bond Markets ◽  
Volatility Spillover ◽  
Asymmetric Volatility ◽  
Volatility Spillovers ◽  
Financial Products ◽  
Return Dynamics ◽  
Positive Return

This study examines the market for green bonds, which have been in the spotlight as an eco-friendly investment product. We analyze the volatility dynamics and spillovers between the equity and green bond markets. As the return dynamics of financial products typically exhibit asymmetric volatility, we check whether green bonds also share this property. Our analyses confirm that although green bonds do exhibit the asymmetric volatility phenomenon, their volatility, unlike that of equity, is also sensitive to positive return shocks. An analysis of the association between the green bond and equity markets confirms that although the two markets have some volatility spillover effects, neither responds significantly to negative shocks in the other market.

Nexus between Southeast Asian stock markets, bitcoin and gold: spillover effect before and during the COVID-19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yosuke Kakinuma
Keyword(s):  
Southeast Asia ◽  
Stock Markets ◽  
Spillover Effect ◽  
Spillover Effects ◽  
Southeast Asian ◽  
Series Data ◽  
Financial Assets ◽  
Volatility Spillover ◽  
Content Type ◽  
Asset Classes

Purpose This study aims to provide empirical evidence on the return and volatility spillover effects between Southeast Asian stock markets, bitcoin and gold in the periods before and during the COVID-19 pandemic. The interdependence among different asset classes, the two leading stock markets in Southeast Asia (Singapore and Thailand), bitcoin and gold, is analyzed for diversification opportunities. Design/methodology/approach The vector autoregressive-Baba, Engle, Kraft, and Kroner-generalized autoregressive conditional heteroskedasticity model is used to capture the return and volatility spillover effects between different financial assets. The data cover the period from October 2013 to May 2021. The full period is divided into two sub-sample periods, the pre-pandemic period and the during-pandemic period, to examine whether the financial turbulence caused by COVID-19 affects the interconnectedness between the assets. Findings The stocks in Southeast Asia, bitcoin and gold become more interdependent during the pandemic. During turbulent times, the contagion effect is inevitable regardless of region and asset class. Furthermore, bitcoin does not provide protection for investors in Southeast Asia. The pricing mechanism and technology behind bitcoin are different from common stocks, yet the results indicate the co-movement of bitcoin and the Singaporean and Thai stocks during the crisis. Finally, risk-averse investors should ensure that gold constitutes a significant proportion of their portfolio, approximately 40%–55%. This strategy provides the most effective hedge against risk. Originality/value The mean return and volatility spillover is analyzed between bitcoin, gold and two preeminent stock markets in Southeast Asia. Most prior studies test the spillover effect between the same asset classes such as equities in different regions or different commodities, currencies and cryptocurrencies. Moreover, the time-series data are divided into two groups based on the structural break caused by the COVID-19 pandemic. The findings of this study offer practical implications for risk management and portfolio diversification. Diversification opportunities are becoming scarce as different financial assets witness increasing integration.

The connectedness between Sukuk and conventional bond markets and the implications for investors

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aristeidis Samitas ◽  
Spyros Papathanasiou ◽  
Drosos Koutsokostas
Keyword(s):  
Asset Allocation ◽  
Spillover Effects ◽  
Bond Markets ◽  
Data Set ◽  
Content Type ◽  
Vector Autoregressive ◽  
Volatility Spillovers ◽  
Exogenous Shocks ◽  
Time Varying Parameter ◽  
Optimal Hedge

Purpose The purpose of this paper is to examine the connectedness across a variety of Sukuk and conventional bond indices and the implications for optimal asset allocation for the period January 1, 2010–April 30, 2020. Design/methodology/approach The data set consists of five major Sukuk (Dow Jones Sukuk, Thompson Reuters BPA Malaysia Sukuk, Indonesia Government Sukuk, S&P MENA Sukuk and Tadawul Sukuk and Bonds Index) and five conventional bond indexes, one for developed (USA) and four for emerging markets (Malaysia, Indonesia, Africa and Qatar). This study investigates the connectedness and volatility spillover effects across the aforementioned indices, by following the Diebold and Yilmaz (2012) approach, based on the time-varying parameter vector autoregressive (TVP-VAR) model. In addition, this paper provides optimal hedge ratios and portfolio weights for investors. Findings The empirical results show that Sukuk and conventional bond markets are highly integrated and that total connectedness exhibits sensitivity to exogenous shocks. The Dow Jones and the Malaysian Sukuk indices are the primary shock transmitters to other markets. However, the weak volatility spillovers between the Dow Jones and conventional bonds suggest that opportunities for optimal asset allocation may in fact exist. The highest (lowest) hedging effectiveness can be achieved by taking a short position in Malaysian (Qatarian) bonds. Originality/value To the best of the knowledge, this is the largest sample taken into account to investigate the connectedness between Sukuk and conventional bonds.

scholarly journals Volatility spillover effects in leading cryptocurrencies: A BEKK-MGARCH analysis

2019 ◽  
Vol 29 ◽  
pp. 68-74 ◽  
Author(s):  
Paraskevi Katsiampa ◽  
Shaen Corbet ◽  
Brian Lucey
Keyword(s):  
Spillover Effects ◽  
Volatility Spillover
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