Econometric Measures of Connectedness and Systemic Risk in the Finance and Insurance Sectors

By Monica Billio, Mila Getmansky, Andrew W. Lo, Loriana Pelizzon. 2012

2,290 citations recorded by the source corpus.

We propose several econometric measures of connectedness based on principal-components analysis and Granger-causality networks, and apply them to the monthly returns of hedge funds, banks, broker/dealers, and insurance companies. We find that all four sectors have become highly interrelated over the past decade, likely increasing the level of systemic risk in the finance and insurance industries through a complex and time-varying network of relationships. These measures can also identify and quantify financial crisis periods, and seem to contain predictive power in out-of-sample tests. Our results show an asymmetry in the degree of connectedness among the four sectors, with banks playing a much more important role in transmitting shocks than other financial institutions.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/9dcd13ef4cf2809d7d0de4553d23132bd9b26ccd

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Citations in the corpus

Systemic Risk in Europe (2013, neutral): “Ht+1 = D −1/2 t+1 Γt+1D −1/2 t+1 , (6)”
Quantile Connectedness: Modelling Tail Behaviour in the Topology of Financial Networks (2018, positive): “A major advantage of the Diebold–Yilmaz framework relative to the Granger-causal network analysis of Billio et al. (2012) is that the resulting network is not only directed but also weighted and therefore provides an estimate of the strength of bilateral spillover effects.”
Systemic Co-Jumps (2017, background): “…and are more likely followed by a decline in stock prices, while detected multi-jumps associated with good news imply a decrease in the 1The recent literature on systemic risk links the word “systemic” to the propagation of local shocks to the whole financial system, see e.g. Billio et al. (2012).”
A network analysis of the volatility of high dimensional financial series (2017, background): “That type of networkbased analysis is of particular relevance in financial econometrics—see, among others, Billio et al. (2012), Acemoglu et al. (2015), Hautsch et al. (2014, 2015) or Diebold and Yilmaz (2014).”
Assessing the Contribution of Banks, Insurance and Other Financial Services to Systemic Risk (2014, positive): “Billio et al. (2012) rely on principal-components analysis and Granger-causality tests to study the interconnectedness between different financial sectors.”
A Network Approach to Portfolio Selection (2016, background): “…markets as networks in which securities correspond to the nodes and the links relate to the correlation of returns (Barigozzi and Brownlees, 2014; Billio et al., 2012; Bonanno et al., 2004; Diebold and Yilmaz, 2014; Hautsch et al., 2015; Mantegna, 1999; Onnela et al., 2003; Peralta, 2015; Tse et…”
Elimination of systemic risk in financial networks by means of a systemic risk transaction tax (2014, background): “[45] Monica Billio, Mila Getmansky, Andrew W Lo, and Loriana Pelizzon.”
Where the Risks Lie: A Survey on Systemic Risk (2017, neutral): “Billio et al. (2012) use quarterly returns on hedge funds, banks, broker-dealers, and insurance companies to develop several measures of interconnectedness based on Granger causality tests and principal component analysis (see also the absorption ratio of Kritzman et al., 2011).”
Climate risks and financial stability (2021, background): “In addition, the high degree of interconnectedness of financial actors can further amplify losses for individual financial actors and for the financial sector, as occurred in the last financial crisis (Haldane and May, 2011; Billio et al., 2012; Battiston et al., 2012; Battiston et al., 2016).”