Field of examination is theoretical and empirical review of dynamic CAPM models that assume non constant volatility and correlation. In other words time evolution is considered in estimation process. As theoretical basement is recommended to be R. Engle's (Dynamic Conditional Beta) research and other sources.

This thesis describes statistical approaches of investment portfolio constructions. The theoretic part presents modern portfolio theory and specific statistical methods used to estimate expected revenue and risk of portfolio. These procedures are specifically selection method, modelling volatility using multivariate GARCH model, primarily DCC GARCH procedure and Bayes approach with Jeffrey's and conjugated density. The practical part of the thesis covers application of above mentioned statistical methods of investment portfolio constructions. The maximization of Sharp's ratio was chosen as optimization task. Researched portfolios are created from Austria Traded Index issues of shares where suitable time series of historical daily closed prices. Results attained within assembled portfolios in two year investment interval are later compared.

This paper investigates the impact of the European Union membership referendum in the UK on the correlations and volatility between three different broad stock market indices, utilizing an econometric time series model called DCC GARCH. Findings support the claim of higher volatility peaks on the stock market as an immediate response to the event. Evidence indicate higher shortrun correlations between the indices as a response to higher volatility. In addition, the study present evidence that the correlation between the UK stock index and the other two indices declines after the referendum in 2016. / Studien undersöker konsekvenserna av folkomröstningen om Storbritanniens medlemskap i EU. Korrelationen och volatiliteten mellan tre olika aktiemarknadsindex jämförs med hjälp av en ekonometrisk modell för tidsserier kallad DCC GARCH. Resultaten från studien visar på omedelbart högre nivåer av volatilitet på aktiemarknaden dagarna efter omröstningen. Analysen ger stöd för hypotesen om högre nivåer av kortsiktiga korrelationer mellan indexen som en konsekvens av högre nivåer av volatilitet. Resultat visar även på att korrelationen mellan det brittiska aktieindexet och de övriga två minskar efter det undersökta eventet.

When modelling more that one asset, it is desirable to apply multivariate modeling to capture the co-movements of the underlying assets. The GARCH models has been proven to be successful when it comes to volatility forecast- ing. Hence it is natural to extend from a univariate GARCH model to a multivariate GARCH model when examining portfolio volatility. This study aims to evaluate a specific multivariate GARCH model, the DCC-GARCH model, which was developed by Engle and Sheppard in 2001. In this pa- per different DCC-GARCH models have been implemented, assuming both Gaussian and multivariate Student’s t distribution. These distributions are compared by a set of tests as well as Value at Risk backtesting. / I portföljanalys så är det åtråvärt att applicera flerdimensionella modeller för att kunna fånga hur de olika tillgångarna rör sig tillsammans. GARCH-modeller har visat sig vara framgångsrika när det kommer till prognoser av volatilitet. Det är därför naturligt att gå från endimensionella till flerdimensionella GARCH-modeller när volatiliteten av en portfölj skall utvärderas. Den här studien ämnar att utvärdera tillvägagångssättet för prognoser av en viss typ av flerdimensionell GARCH-modell, DCC-GARCH-modellen, vilken utvecklades av Engle och Sheppard 2001. I den här uppsatsen har olika DCC-GARCH modeller blivit implementerade, som antar innovationer enligt både flerdimensionell normalfördelning samt flerdimensionell student's t-fördelning. Dessa jämförs med hjälp av en handfull tester samt Value-at-Risk backtesting.

The recent period of intensified electricity price volatility has challenged both private households and businesses, resulting in companies transitioning their strategies to address the uncertainties that follow. No previous study has analysed how electricity price volatility affects Swedish industries’ returns and electricity usage. Therefore, this essay aims to fill this knowledge gap and capture the impact of electricity price volatility on two different industries, one more electricity-intensive industry and one less electricity-intensive industry. By applying a DCC-GARCH model, the study examines the impact on the returns and electricity usage of two industries to analyse if electricity price volatility has affected businesses in terms of returns and electricity consumption.  The first DCC model was run on weekly electricity spot price data from Nord Pool and data constructed through a proxy of each industry’s average return. The results show that there is almost zero conditional correlation over time, ranging from 0.03 to 0.045, between the electricity price and each industry’s returns. There are no short-run spillover effects from electricity price volatility on the on the industries’ average returns. On the other hand, there is a long term spillover effect from electricity prices to the more electricity-intensive industry and no long term spillover for the less electricity-intensive industry.  The second DCC-GARCH modell is applied on monthly electricity spot prices from Nord Pool and data of monthly electricity usage of each industry. The industries are sorted by Swedish Standard Industrial Classification (SNI). SNI 17 stands for manufacture of paper and paper products and SNI 24 stands for manufacture of basic metals. The results from this part indicates that the dynamic conditional correlation between electricity price and the electricity usage in the paper industry is close to zero which differ from the basic metal industry which is positive. Beyond the dynamic conditional correlation, we find a short-term spillover effect from electricity price volatility to electricity usage in the basic metal industry, which is absent in the paper industry. On the other hand, there is a long-term spillover effect from electricity price volatility to electricity usage in the paper industry, which is absent for the electricity usage in basic metal industry.  Overall, our study shows that the businesses in the return proxy have preformed relatively well despite an uncertain period of volatile electricity prices. Simultaneously we find that the results for the industries electricity usage differ between the chosen industries.

Bibliographic Record JÍLEK, Jiří. European Real Estate Investment Trusts: Analyzing Correlation with a DCC- GARCH Model. Prague, 2012. 50 p. Master thesis (Mgr.) Charles University in Prague, Faculty of Social Sciences, Institute of Economic Studies. Supervisor: Tomáš Jandík MA MSc MRICS. Abstract The main goal of this thesis is to study the interdependencies between returns of European real estate investment trusts (REITs) and other investment asset classes such as European equities, government bonds and commodities. The thesis is divided into two parts: in the first part, we describe the necessary background that led to the emergence of first REIT structures and also provide an overview of the European REITs market. In the second part, we apply the Dynamic Conditional Correlation GARCH (DCC-GARCH) model to examine correlations between the above mentioned asset classes. The general understanding of real estate is that it provides diversification benefits to a diversified portfolio. However, our results suggest that returns of European REITs and stocks show a relatively high correlation and more importantly, the correlation increases in time. These findings have significant implications for investors and portfolio managers who seek protection for their portfolios in time of market downturns. Our results...

Real estate is commonly viewed as a good diversification tool since the real estate market cycle exhibit low correlations to other asset classes. Moreover, Real Estate Investment Trusts (REITs) have become increasingly popular in the past decades since this investment form offers private investors a convenient way of diversifying stock portfolios with real estate. Some studies investigating the within-country diversification potential of REITs and stocks have been performed. These studies generally suggest poor diversification potential. Hence, we investigate the international diversification potential of REITs from Europe, Asia Pacific and the US for private investors holding European stocks from 2007 to 2019. For Europe and Asia Pacific, REIT markets with different maturity levels are included since emerging and developed REIT markets might have different characteristics affecting the diversification potential. We also examine which market leads which in terms of changes in returns. Moreover, the diversification potential of REITs may depend on the investment horizon, hence the long- and short-run perspectives for private investors are examined. The lesson learned from the Global Financial Crises and European Debt Crisis is that abnormal market conditions may change the behavior of assets on the financial markets, and significantly affect portfolio behavior. Hence, diversification potential in relation to crises is also considered. The methods employed are Johansen’s cointegration, Granger non-causality and DCC-GARCH. Our findings suggest long- and short-run diversification potential of international REITs for European stocks. Cross-regional combinations of REITs and stocks generally offer better diversification potential than within-regional combinations, and emerging REIT markets are preferred over their developed counterparts due to lower conditional correlations. Moreover, changes in stock market returns lead changes in REIT market returns, indicating that stock markets react more quickly to new information on the market. Long- and short-run diversification potential still exists during the crises although increased conditional correlations suggest higher interdependence in this period. However, there is no trend of increasing conditional correlations over the whole sample, suggesting the abnormal market conditions during the financial turmoil did not permanently change the diversification potential of REITs in stock portfolios.

This paper uses multivariate DCC-GARCH model to investigate the volatility of dynamic correlation between MSCI Taiwan stock index and the USA, China, Japan , Asia and global stock market. The existence of stock market volatility asymmetry, volatility spread of infection and clustering effects also are analysed, while in case of the U.S. sub-prime mortgage crisis and triggered the global financial tsunami. It discusses the Taiwan stock market fluctuations and structural changes in the international markets and the market dynamics related to change of influence and change. The main findings are (1)The volatility of continuity between the spread of infection and the clustering effect between the Taiwan stock market and international market fluctuations, (2) During the global financial tsunami, the correlation between changes in the international market and the market Correlation of different dynamic fluctuations and structural changes occurring in different time point also show the impact of changes of individual markets (3)The correlation between MSCI Taiwan stock index and the USA, China , Japan, indicates that the impact of change of stock the Japanese stock market on the MSCI Taiwan stock index is low, while China and the MSCI Taiwan stock index-related enhances, (4) market structure changes, the MSCI Taiwan stock index and the global dynamic fluctuations in the market is still a significant, The visible impact of the shock oscillation is wide and return to equilibrium of adjustment is still ongoing.

Ce mémoire s'intéresse à la transmission de la volatilité des marchés financiers. Les marchés canadien et américain sont étudiés durant la crise financière de 2008. Afin d'analyser ces transmissions, nous utilisons le modèle d'hétéroscédasticité conditionnelle autorégressive généralisé à corrélations conditionnelles dynamiques d'Engle (2002). La période analysée est du 1er janvier 2005 au 31 juillet 2010. Cette période se divise en deux sous-périodes, soit une période de calme et une période de crise. La période de calme est du 1er janvier 2005 au 8 septembre 2008 et la période de crise est du 9 septembre 2008 au 31 juillet 2010. Les résultats obtenus indiquent qu'il y a eu une transmission de volatilité des États-Unis vers le Canada durant cette crise. Nous avons aussi trouvé une augmentation des corrélations conditionnelles dynamiques entre le Canada et les États-Unis en temps de crise. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : GARCH multivarié, DCC-GARCH, crise financière, volatilité.

This study examines to what extent how oil movements differently affect equity returns in general and sectoral levels of the GCC countries stock markets. Modeling the equity returns volatility requires using GARCH-type models. These models help to explore the pronounced differences of the conditional variance structures across sectors and markets. Chapter 1 compares the effects of changes in oil price return and its volatility on equity returns and volatility across sectors. The findings of this chapter show that despite the GCC states dependency on oil revenues, equity market performance at the sectoral level do not exactly associate with oil movements. Our results, in particular, show that the GCC stock markets do not always move hand-in-hand with oil market movements. In chapter 2, we explore the relationship within a specific sector, i.e. Banks sector in Saudi Arabia Stock market. We examine if oil price changes affect Islamic banks differently than conventional ones. The findings show a decrease in degree of co-movement between these two types of banking system and oil market, meaning that they are less integrated. Although the Islamic banks kept a higher degree of co-movement with oil, limitations of Shari'ah restrictions on Islamic banks have little impact on the relationship between oil and those banks. Chapter 3 examines whether the level of corruption influences how oil changes affect the GCC stock markets. The findings of chapter 3 show that dissimilar levels of corruption between GCC countries have inconsiderable differences on the oil return effects on the GCC stock markets. Oil returns affect both low and high level of corruption groups. The oil return innovation affects the equity volatility for Saudi Arabia and Kuwait more than other four GCC countries.