German Title: Modellierung und Vorhersage von Realisierten Kovarianzmatrizen
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Abstract
In this thesis, we use observation-driven models for time-series of daily RCs. That is, we assume a matrix-variate probability distribution for the daily RCs, whose parameters are updated based on the RC realizations from previous days.
In particular, Chapter 2 looks at different matrix-variate probability distributions for the RCs and their theoretical and empirical properties. Chapter 3 proposes a flexible observation-driven model to update all distribution-specific time-varying parameters, not just the expected value matrix as is done in the literature so far. Chapter 4 introduces an observation-driven updating mechanism that is applicable to high-dimensional time-series of RCs. Each of these three chapters is a self-contained paper.
Document type: | Dissertation |
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Supervisor: | Conrad, Prof. Dr. Christian |
Place of Publication: | Heidelberg |
Date of thesis defense: | 1 June 2023 |
Date Deposited: | 22 Aug 2023 08:45 |
Date: | 2023 |
Faculties / Institutes: | The Faculty of Economics and Social Studies > Alfred-Weber-Institut for Economics |
DDC-classification: | 300 Social sciences 310 General statistics 330 Economics 510 Mathematics |