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Type | Master's Thesis |
Scope | Discipline-based scholarship |
Title | Financial Risk Indicators based on Conditional Covariance Forecasts |
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Institution | University of Zurich |
Faculty | Faculty of Business, Economics and Informatics |
Number of Pages | 22 |
Date | 2020 |
Abstract Text | This thesis primarily investigate the improvement of financial indicators based on the dynamically varying covariances. In previous research and papers, financial indicators are usually calculated by convariance matrix based on i.i.d Gaussian assumptions. Here I employ two indicators, financial turbulence and absorption ratio and estimate them based on related covariance matrix obtained by 7 models, i.i.d. Gaussian model, multivariate student’s t model, DCC-GARCH based on multivariate normal model, DCC-GARCH based on multivariate student’t model, Go-GARCH based on multivariate normal model, Go-GARCH based on NIG model, MCD covariance estimator. I refer to the turbulenceresistant portfolio and portfolio based on absorption ratio to estimate the performance of the portfolios to assess the financial indicators accordingly. Then I evaluate the improvement of the DCC-GARCH models on the two financial indicators. Keywords: financial indicators; financial turbulence; absorption ratio; covariance matrix; DCC-GARCH model; Go-GARCH model. |
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