Modeling, analysis and mitigation of contagion in financial systems

Cheng, Xian; Zhao, Haichuan

doi:10.1016/j.econmod.2018.08.007

Cited by 13 publications

(5 citation statements)

References 53 publications

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“…Gaffeo and Molinari (2016) also find a stabilizing effect of vertical mergers in small networks modeling the direct channel. Although Cheng and Zhao (2019) consider different merger processes, they also find a stabilizing effect of mergers in some range of the connectivity.…”

Section: Discussionmentioning

confidence: 96%

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Effects of Mergers on Network Models of the Financial System

Nevermann,

Heckmann-Draisbach

2024

SSRN Journal

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Section: Discussionmentioning

confidence: 96%

“…Furthermore, Cheng and Zhao (2019) analyse a model for the interbank market similar to the GK model, where the authors discuss forced mergers as a possible intervention policy. The merging institutions are chosen by different micro-and macro-prudential regulation frameworks.…”

Section: Related Literaturementioning

confidence: 99%

Effects of Mergers on Network Models of the Financial System

Nevermann,

Heckmann-Draisbach

2024

SSRN Journal

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“…Systemic risk is a property of interrelated structures, by which the failure of a primarily minor set of bodies can lead to the failure of a substantial share of the system [3]. Such interconnectedness is a facet of the contemporary financial system due to financial innovation and liberalization [4]. Only after the global financial crisis triggered in 2007/2008 the non-banking parts of the financial sector started to attract more attention, and the first among them to be included in researchers' work was the insurance sector.…”

Section: Billion Eur)mentioning

confidence: 99%

A Markov Regime Switching Approach towards Assessing Resilience of Romanian Collective Investment Undertakings

et al. 2019

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This paper explores the sensitivity of Romanian collective investment undertakings’ returns to changes in equity, fixed income and foreign exchange market returns. We use a sample of 80 open-end investment funds and pension funds with daily returns between 2016 and 2018. Our methodology consists of measuring changes in the daily conditional volatility for the fund returns (EGARCH) and changes in their conditional correlation with selected market risk factors (DCC MV-GARCH) throughout different volatility regimes identified using a Markov Regime Switching model. We argue that, on average, the level of conditional correlations between funds and market risk factors remained stable and unconcerned by the volatility regimes. In addition, for only less than half of the funds in the sample, their volatility regimes were synchronized with those of the selected market risk factors. We found that, on average, fund returns are more correlated with equity returns and less correlated with changes in local bond yields, while not being significantly influenced by changes in foreign bond yields or changes in foreign exchange. During the period investigated equity returns were the most volatile while the funds returns volatility were, on average, much more reduced. Overall, our results show the resilience of the Romanian collective investment sector to the selected market risk factors, during the investigated period.

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“…Greenwood et al (2015) discuss the similarities in the findings of this strand of the literature with the one on common holdings. Finally, there is a complementary line of work in the literature that measures systemic risk through the interconnectedness of financial networks (Billio et al, 2012;Minoiu et al, 2015;Mezei and Sarlin, 2018;Cheng and Zhao, 2019).…”

Section: Introductionmentioning

confidence: 99%