Work detail

Measuring systemic risk in time-frequency domain

Author: Mgr. Ivana Muzikářová
Year: 2015 - summer
Leaders: doc. PhDr. Jozef Baruník Ph.D.
Consultants:
Work type: Finance, Financial Markets and Banking
Masters
Language: English
Pages: 97
Awards and prizes:
Link: https://is.cuni.cz/webapps/zzp/detail/147482/
Abstract: This thesis provides an analysis of systemic risk in the US banking sector. We
use conditional value at risk (∆CoVaR), marginal expected shortfall (MES)
and cross-quantilogram (CQ) to statistically measure tail-dependence in return
series of individual institutions and the system as a whole. Wavelet multiresolution
analysis is used to study systemic risk in the time-frequency domain. Decomposition
of returns on different scales allows us to isolate cycles of 2-8 days,
8-32 days and 32-64 days and analyze co-movement patterns which would otherwise
stay hidden. Empirical results demonstrate that filtering out short-term
noise from the return series improves the forecast power of ∆CoVaR. Eventually,
we investigate the connection between statistical measures of systemic risk
and fundamental characteristics of institutions (size, leverage, market to book
ratio) and conclude that size is the most robust determinant of systemic risk.

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