eprintid: 33700
rev_number: 15
eprint_status: archive
userid: 7550
dir: disk0/00/03/37/00
datestamp: 2023-08-22 08:45:57
lastmod: 2023-08-29 13:11:15
status_changed: 2023-08-22 08:45:57
type: doctoralThesis
metadata_visibility: show
creators_name: Stollenwerk, Michael
title: Modelling and Forecasting of Realized Covariance Matrices
title_de: Modellierung und Vorhersage von Realisierten Kovarianzmatrizen
subjects: ddc-300
subjects: ddc-310
subjects: ddc-330
subjects: ddc-510
divisions: i-181000
adv_faculty: af-18
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.
date: 2023
id_scheme: DOI
id_number: 10.11588/heidok.00033700
ppn_swb: 1858195845
own_urn: urn:nbn:de:bsz:16-heidok-337006
date_accepted: 2023-06-01
advisor: HASH(0x559e37d8f568)
language: eng
bibsort: STOLLENWERMODELLINGA20230808
full_text_status: public
place_of_pub: Heidelberg
citation:   Stollenwerk, Michael  (2023) Modelling and Forecasting of Realized Covariance Matrices.  [Dissertation]     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/33700/1/Dissertation_Michael_Stollenwerk.pdf