Global ETD Search

1	Modely vícerozměrných finančních časových řad v úloze optimalizace portfolia / Multivariate financial time series models in portfolio optimization Bureček, Tomáš January 2020 (has links) This master thesis deals with the modeling of multivariate volatility in finan- cial time series. The aim of this work is to describe in detail selected approaches to modeling multivariate financial volatility, including verification of models, and then apply them in an empirical study of asset portfolio optimization. The results are compared with the classical approach of portfolio optimization theory based on unconditional moment estimates. The evaluation was based on four known op- timization problems, namely minimization of variance, Markowitz's model, ma- ximization of the Sharpe ratio and minimization of CVaR. The output portfolios were compared by using four metrics that reflect the returns and risks of the port- folios. The results demonstrated that employing the multivariate volatility models one obtains higher expected returns with less expected risk when comparing with the classical approach. 1
2	Modelování ve finanční analýze / Modelování ve finanční analýze Maďar, Milan January 2012 (has links) In this thesis we study the regional and global linkages as evidence of markets integration of the stock markets in Frankfurt, Amsterdam, Prague the U.S. and the dynamics of volatility transmission of related foreign exchange rates using multivariate GARCH approach. For each of the model classes, a theoretical review, basic properties and estimation procedure are provided. We illustrate approach by applying the models to daily market data. Our two main aims are discussing and report the existence of regional and global stock markets linkages and provide comparison of such multivariate GARCH models on the data sample. We find out that the estimated time-varying conditional correlations indicate limited integration among the markets which implies that investors can benefit from the risk reduction by investigating in the different stock markets especially during the crisis.
3	Mnohorozměrné modely zobecněné autoregresní podmíněné heteroskedasticity / Multivariate generalized autoregressive conditional heteroscedasticity models Nováková, Martina January 2021 (has links) This master thesis deals with extension of the univariate GARCH model to multivari- ate models. We present individual models and deal with methods of their estimation. Then we describe some statistical tests for diagnosting the models. We have programmed in the statistical software R one of them - the Ling-Li test. Afterwards we apply selected models to real data of stock market index S&P 500, stock market index Russell 2000 and stocks of crude oil. For the GO-GARCH model, we compare all available estimation methods and show their differences. Then we compare the results of all models with each other and also with univariate models in terms of estimates of conditional variances, estimates of conditional correlations and also in terms of computational complexity. 1
4	Swedish Equity Sectors Risk Management with Commodities : Revisiting dynamic conditional correlations and hedge ratios Engström, Daniel, Gustafsson, Niklas January 2017 (has links) The purpose of this study is to investigate changes in dynamic conditional correlations between Swedish equity sector indices and commodities using oil, gold, copper and a general commodity index. Additionally the purpose is to evaluate which of the two methods, DCC- GARCH or GO-GARCH that is more efficient in estimating correlation for hedge ratio calculation. Daily data on the FTSE30 index of Sweden and its sector indices have been studied between the years 1994 and 2017. A DCC-GARCH (1,1) and GO-GARCH (1,1) model with one autoregressive term AR(1) using multivariate Student t- and Multivariate Affine Negative Inverse Gaussian distribution were used to estimate conditional correlations. Correlations between Swedish FTSE30, its sector indices and commodities are considerably lower than previous research has found American or emerging markets correlation with commodities to be. This suggests better diversification opportunities with commodities for the Swedish market. Optimal hedge ratios (OHR) was calculated and back tested using a rolling window analysis with 1000 days forecast length and 20 days re-estimation window and evaluated using a calculated hedge effectiveness index (HE). Determined by HE, copper is the best hedge for the Swedish composite FTSE30 and sector indices using conditional correlation from the GO-GARCH during the data period. Gold is considered as a semi-strong safe haven due to its negative correlation with all sectors. Additionally, this study identifies a temporarily large increase in the correlation between the Swedish equities sectors and composite index with commodities around the years 2015/2016. This study also emphasizes the difference between stressful and calm periods in the market. Hedging hedge commodities futures hedge ratio conditional correlation DCC GO-GARCH DCC-GARCH GARCH Dynamic conditional correlation oil GSCI copper gold safe haven optimal hedge ratio finance economics markets risk risk management hedge effectiveness Risk riskhantering råvaror terminer futures hedging hedge GARCH Economics Nationalekonomi

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