Principal Components as a Measure of Systemic Risk

By M. Kritzman, Yuanzhen Li, Sébastien Page, Roberto Rigobon. Journal of Portfolio Management, 2011

360 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/2adf6a5eb852a08da3b1d8409bec3c93ad2887e1

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Citations in the corpus

Fire‐Sale Spillovers and Systemic Risk (2015, neutral): “Figure 12 shows the time evolution of AV and 14 other measures of systemic risk compiled by Giglio, Kelly, and Pruitt (2016) for 2003q1 to 2009q1, with each series normalized to 100 in 2003q1.”
Systemic Risk and the Macroeconomy: An Empirical Evaluation (2016, neutral): “We construct the Absorption Ratio (AR) described by Kritzman et al. (2010) which measures the fraction of the financial system variance explained by the first 5 principal components, the Dynamic Causality Index (DCI) from Billio et al. (2012) which counts the number of significant Granger-causal…”
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).”
Interconnectedness and systemic risk of China's financial institutions (2017, methodology): “, 2013) and the principal component analysis (PCA) (Kritzman et al., 2011; Billio et al., 2012).”
Short-Term Wholesale Funding and Systemic Risk: A Global Covar Approach (2012, neutral): “Gray and Jobst (2010) examine contagion across markets and institutions using extreme value theory, while Kritzman et al. (2010) introduce the so-called absorption ratio measure to assess systemic risk using a principal components approach; see also Billio, et al. (2010) for a related analysis.”
Moment Component Analysis: An Illustration With International Stock Markets (2018, neutral): “On the one hand, we follow (Kritzman et al. 2011) and test if (positive or negative) spikes in the ARs help predict large (positive or negative) market changes.”