Portfolio Value at Risk and Expected Shortfall using High-frequency data

Informace o vysokoškolské kvalifikační práci

Název práce:
Portfolio Value at Risk and Expected Shortfall using High-frequency data
Autor práce:
Zváč, Marek
Typ práce:
Diplomová práce / info:eu-repo/semantics/masterThesis
Vedoucí práce:
Fičura, Milan
Osoba oponující práci:
Janda, Karel
Jazyk práce:
English
Abstrakt:
The main objective of this thesis is to investigate whether multivariate models using Highfrequency data provide significantly more accurate forecasts of Value at Risk and Expected Shortfall than multivariate models using only daily data. Our objective is very topical since the Basel Committee announced in 2013 that is going to change the risk measure used for calculation of capital requirement from Value at Risk to Expected Shortfall. The further improvement of accuracy of both risk measures can be also achieved by incorporation of high-frequency data that are rapidly more available due to significant technological progress. Therefore, we employed parsimonious Heterogeneous Autoregression and its asymmetric version that uses high-frequency data for the modeling of realized covariance matrix. The benchmark models are chosen well established DCC-GARCH and EWMA. The computation of Value at Risk (VaR) and Expected Shortfall (ES) is done through parametric, semi-parametric and Monte Carlo simulations. The loss distributions are represented by multivariate Gaussian, Student t, multivariate distributions simulated by Copula functions and multivariate filtered historical simulations. There are used univariate loss distributions: Generalized Pareto Distribution from EVT, empirical and standard parametric distributions. The main finding is that Heterogeneous Autoregression model using high-frequency data delivered superior or at least the same accuracy of forecasts of VaR to benchmark models based on daily data. Finally, the backtesting of ES remains still very challenging and applied Test I. and II. did not provide credible validation of the forecasts.
Klíčová slova:
HAR; Realized covariance; Expected Shortfall; Value at Risk; Portfolio; Copula; EVT; High-frequency data

Informace o studiu

Studijní program a Studijní obor:
Finance a účetnictví/Finanční inženýrství
Typ studijního programu:
Magisterský navazující studijní program
Jméno přidělované hodnosti:
Ing.
Instituce přidělující hodnost:
University of Economics, Prague
Název fakulty:
Faculty of Finance and Accounting
Název katedry:
Department of Banking and Insurance
Instituce archivující a zpřístupňující VŠKP:
University of Economics, Prague

Informace o odevzdání a obhajobě

Datum zadání práce:
1. 12. 2015
Datum podání práce:
15. 6. 2016
Datum obhajoby:
23.03.2017

Soubory ke stažení

Hlavní práce:
55453_xzvam00.pdf [5,08 MB]
Oponentura:
51075_janda.pdf [316,59 kB]
Hodnocení vedoucího:
55453_xficm03.pdf [1,08 MB]

Údaje ze systému InSIS

Identifikátor:
https://insis.vse.cz/zp/55453/podrobnosti