Tail Risk Networks of Insurers Around the Globe: An Empirical Examination of Systemic Risk for G‐SIIs vs Non‐G‐SIIs

Chen, Hua; Sun, Tao

doi:10.1111/jori.12296

Cited by 15 publications

(7 citation statements)

References 27 publications

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“…By contrast, Weiß and Mühlnickel (2014) underline that the size of insurance companies helps determine their exposure and contribution to the risk of the financial system. Finally, Chen and Sun (2020) highlight that G‐SIIs are more systemically relevant than non‐G‐SIIs overall, but a small number of non‐G‐SIIs outweigh G‐SIIs during periods of market turbulence. We revisit this issue using a novel measure of interconnectedness, which captures exposures to both financial and nonfinancial shocks.…”

Section: Introductionmentioning

confidence: 99%

The rising interconnectedness of the insurance sector

Jourde

2022

J of Risk & Insurance

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This paper examines the long-term evolution of the linkages of the insurance sector with financial and nonfinancial companies. We develop a measure of connectedness using a multifactor model of weekly equity returns. The empirical analysis is conducted from 1973 to 2018, for 16 developed countries, at both the sectoral and institution levels. The results indicate that, unlike other sectors, the connectedness level of the insurance industry has strengthened over time.We also find that the linkages of the largest insurance companies with financial and nonfinancial firms are structurally different but as high as those of the largest banks.

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Section: Introductionmentioning

confidence: 99%

The rising interconnectedness of the insurance sector

Jourde

2022

J of Risk & Insurance

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“…Hardle et al (2016) propose a semiparametric measure to estimate systemic interconnectedness across financial institutions based on tail-driven spillover effects in a high dimensional network. Chen and Sun (2020) use this methodology for studying systemically important insurers.…”

Section: Empirical Motivationmentioning

confidence: 99%

TailCoR

Babić¹,

Ley²,

Ricci³

et al. 2020

Preprint

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Economic and financial crises are characterised by unusually large events. These tail events co-move because of linear and/or nonlinear dependencies. We introduce TailCoR, a metric that combines (and disentangles) these linear and non-linear dependencies. Tail-CoR between two variables is based on the tail inter quantile range of a simple projection.It is dimension-free, it performs well in small samples, and no optimisations are needed.

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“…Finally, this study contributes to the rather limited literature on cross-country studies of insurance firms' tail risk and its determinants (Bierth et al, 2015;Chen & Sun, 2020;Kaserer & Klein, 2019). This study is distinct from the existing body of literature by jointly examining two additional tail risk drivers (i.e., an insurance sector's GVC position measures and an individual insurer's relative size).…”

Section: Introductionmentioning

confidence: 96%

“…Additionally, we offer new empirical evidence that also supplements the view of "too big to fail," that is, an insurer may new tail risk channel related to interindustry linkages formed by insurance industries with other industries in a global production system. In particular, this study is connected to a strand of literature investigating the systemic risk of insurance firms in an international setting (Bierth et al, 2015;Chen & Sun, 2020). This study differs from previous ones by examining a new and important form of insurance sector interconnectedness in the global production network and its implications for insurers' tail risk.…”

Section: Introductionmentioning

confidence: 99%

Cross‐country evidence on the relationship between global value chain position and the tail risk of insurers

Sun¹

2022

Risk Manage Insurance Review

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This study investigates the relationship between insurance sectors' global value chain (GVC) positions and insurance firms' tail risk. Using a sample of 208 insurers from 25 countries between 2000 and 2015, we find that insurers' tail risk (i.e., expected shortfall, downside beta, and marginal expected shortfall) increases when an insurance sector's GVC upstreamness indices increase. This result suggests that when an insurance sector becomes more upstream in the global production network, the comovement between insurers' stock returns and the market returns become stronger and insurers become more exposed to market tail risk. By testing over a subsample of non-US insurers and a sample period excluding the 2008 Global Financial Crisis, we show that our main results remain unchanged. We also use 2SLS with instrumental variables to address the potential endogeneity problem. Using the nonfinancial sectors' GVC positions as the instrumental variable, we find that the main results are robust to the bias associated with any endogeneity problem. This paper provides the first empirical evidence that highlights the role of GVC linkages in tail risk spillover among insurers around the globe. Our findings have important policy implications for the regulation of insurance firms.

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Tail Risk Networks of Insurers Around the Globe: An Empirical Examination of Systemic Risk for G‐SIIs vs Non‐G‐SIIs

Cited by 15 publications

References 27 publications

The rising interconnectedness of the insurance sector

The rising interconnectedness of the insurance sector

TailCoR

Cross‐country evidence on the relationship between global value chain position and the tail risk of insurers

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