Was a deterioration in ‘connectedness’ a leading indicator of the European sovereign debt crisis?

Hamill, Philip; Li, Youwei; Pantelous, Athanasios A.; Vigne, Samuel A.; Waterworth, James

doi:10.1016/j.intfin.2021.101300

Cited by 19 publications

(11 citation statements)

References 57 publications

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“…Since the mid-1990s, international financial markets have been prone to economic and financial distress with notable regularity. Therefore, the impact of contagion, financial networks and connectedness has been widely discussed in the academic literature (Anand et al, 2015;Baruník & Křehlík, 2018;Billio et al, 2012;Bostanci & Yilmaz, 2020;Hamill et al, 2021;Kenourgios, 2014;Minoiu et al, 2015). A significant strand in research is dedicated to analyzing spillovers in cross-country settings: European stock and bond markets (Baele, 2005;Karkowska & Urjasz, 2021;Skintzi & Refenes, 2006), eurozone credit market (Shahzad et al, 2019), North America, Europe and Asia (Singh et al, 2010), BRIC markets (Bekiros, 2014), G-7 countries (Andrikopoulos et al, 2014;Yang & Doong, 2004), Australia (Dean et al, 2010), Islamic and conventional stock markets (Shahzad et al, 2017), India (Narayan et al, 2014), currency, futures and commodity markets (Chen et al, 2022;Kang et al, 2017;Mensi et al, 2021), cryptocurrency markets (Ji et al, 2019, Al-Shboul et al, 2022Ghabri et al, 2022).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Understanding connectedness among Asian markets is crucial for academics, policymakers, and practitioners as it provides a comprehensive picture of counterparty and market risk, systematic risk and macroeconomic instability (Minoiu et al, 2015). From a policy perspective, cross market connectedness serves as an important pre‐requisite that helps to develop forward‐looking monitoring programmes aiming to identify and track sources of systemic risk over time, thus, contributing to the formulations of policy to restore and safeguard financial stability (Adrian et al, 2015; Diebold & Yılmaz, 2014; Hamill et al, 2021). Furthermore, analyzing return and volatility connectedness across Asian markets has a wide set of implications in asset allocation and risk management since it helps investors to assess and make suitable decisions about international portfolio diversification opportunities and hedging strategies.…”

Section: Introductionmentioning

confidence: 99%

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Return and volatility connectedness and net directional patterns in spillover transmissions: East and Southeast Asian equity markets

Mateus,

Bagirov,

Mateus

2023

Int Rev Finance

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In this article, we investigate the pattern and dynamics of return and volatility connectedness across East and Southeast Asian markets (referred to as the ASEAN5 + 5 group) by utilizing forecast‐error variance decompositions in a generalized VAR framework in conjunction with the Bai‐Perron procedure to control for structural breaks. Our analysis of the dynamics of return spillovers in static and time‐varying settings identifies that the stock markets of Singapore, Hong Kong and South Korea act as constant and largest net transmitters of shocks throughout the period from January 2003 to July 2021. The Chinese stock market is found to have the lowest return connectedness with other regional markets, which could be due to the local foreign ownership regulations. Visualization of the net pairwise return spillover network shows that Singapore is the sole net transmitter of shocks to all other markets in the ASEAN5 + 5 group, whereas, China, despite its market size is the sole net recipient. Two other markets in the regional group are identified as the net receivers, Japan and the Philippines, with the former becoming a net recipient from 2007. Our analysis of structural breaks shows that return spillovers across the markets intensify during periods of economic turmoil, financial shocks and the health crisis (COVID‐19), however, return to the pre‐shock levels during stable market periods. Further analysis of time‐varying patterns revealed that the dynamic connectedness across the region is not symmetrical and the influence of negative returns is more pronounced. The investigation of volatility spillovers shows no substantial differences. The stock markets generally retain their roles. Importantly, the time‐varying volatility connectedness exhibits similar patterns and tends to reach peak levels during turbulent episodes.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Return and volatility connectedness and net directional patterns in spillover transmissions: East and Southeast Asian equity markets

Mateus,

Bagirov,

Mateus

2023

Int Rev Finance

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“…Lanne and Nyberg (2016) proposed a modified GFEVD that makes the relative contributions to the H ‐period impact of the shocks sum to unity. Later, other scholars, such as Hamill et al (2021) and Tan et al (2020), combined the Lanne–Nyberg GFEVD with the original connectedness approach and then applied it.…”

Section: Literature Reviewmentioning

confidence: 99%

Spillover effects in Chinese carbon, energy and financial markets

Cao

Xie

Ling

2022

International Finance

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As China's carbon market continues to develop, its close connection with the financial and energy markets is becoming increasingly apparent. A systematic study of the spillover effects between markets is important, as it can help prevent excessive fluctuations in carbon prices. With this in mind, this study proposes a time-varying parameter vector autoregression with Lanne-Nyberg decomposition extended joint connectedness approach to analyze quantitatively the spillover effects in the "carbon-energy-financial" system. Empirical results show that a bidirectional spillover effect exists among markets. Not only does the carbon market have the most pronounced return (volatility) linkages with the natural gas (clean energy) market, but the information connected with the energy markets is also more closely linked than with the financial markets. We also find that market fluctuations, caused by the China-US trade conflict and the COVID-19 pandemic, have increased spillovers in the system.

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“…Several studies have analyzed the connectedness of returns among different asset classes (Bouri et al , 2021; Hamill et al , 2021; Lau et al , 2017). Some studies have also explored the impact of a rise in uncertainty on asset return (Bilgin et al , 2018; Karaömer, 2022; Loudon, 2017).…”

Section: Introductionmentioning

confidence: 99%

Time and frequency uncertainty spillover among macro uncertainty, financial stress and asset markets

Sawarn

Dash

2023

SEF

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Purpose This study aims to examine the uncertainty spillover among eight important asset classes (cryptocurrencies, US stocks, US bonds, US dollar, agriculture, metal, oil and gold) using weekly data from 2014 to 2020. This study also examines the US macro uncertainty and US financial stress spillover on these assets. Design/methodology/approach The authors use time–frequency connectedness method to study the uncertainty spillover among the asset classes. Findings This study’s findings revealed that the uncertainty spillover is time-varying and peaked during the 2016 oil supply glut and COVID-19 pandemic. US stocks are the highest transmitter of uncertainty to all other assets, followed by the US dollar and oil. US stocks (US dollar and oil) transmit uncertainty in long (short) term. Furthermore, US macro uncertainty is the net transmitter of uncertainty to the US stocks, industrial metals and oil markets. In contrast, US financial stress is the net transmitter of uncertainty to the US bonds, cryptocurrencies, the US dollar and gold markets. US financial stress (US macro uncertainty) has long (short)-term effects on asset price volatility. Originality/value This study complements the studies on volatility spillover among the important asset classes. This study also includes recently financialized asset classes such as cryptocurrencies, agricultural and industrial commodities. This study examines the macro uncertainty and financial stress spillover on these assets.

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Was a deterioration in ‘connectedness’ a leading indicator of the European sovereign debt crisis?

Cited by 19 publications

References 57 publications

Return and volatility connectedness and net directional patterns in spillover transmissions: East and Southeast Asian equity markets

Return and volatility connectedness and net directional patterns in spillover transmissions: East and Southeast Asian equity markets

Spillover effects in Chinese carbon, energy and financial markets

Time and frequency uncertainty spillover among macro uncertainty, financial stress and asset markets

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