Uncovering the mesoscale structure of the credit default swap market to improve portfolio risk modelling
نویسندگان
چکیده
One of the most challenging aspects in analysis and modelling financial markets, including Credit Default Swap (CDS) is presence an emergent, intermediate level structure standing between microscopic dynamics individual entities macroscopic market as a whole. This elusive, mesoscopic organisation often sought for via factor models that ultimately decompose according to geographic regions economic industries. However, at more general level, might be revealed entirely data-driven approach, looking modular possibly hierarchical empirical correlation matrix time series. The crucial ingredient such approach definition appropriate null model matrix. Recent research showed community detection techniques developed networks become intrinsically biased when applied matrices. For this reason, method based on Random Matrix Theory has been developed, which identifies optimal decomposition system into internally correlated mutually anti-correlated communities. Building upon technique, here we resolve CDS identify groups issuers cannot traced back standard industry/region taxonomies, thereby being inaccessible models. We use introduce novel default risk shown outperform traditional alternatives.
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ژورنال
عنوان ژورنال: Quantitative Finance
سال: 2021
ISSN: ['1469-7696', '1469-7688']
DOI: https://doi.org/10.1080/14697688.2021.1890807