"It is the part of a wise man to keep himself today for tomorrow, and not venture all his eggs in one basket."                     - Don Quixote (Part I, Book III, Chapter 9) by Miguel de Cervantes Saavedra [1547-1616]     This research aimed to investigate whether it is possible for investors to diversify their investment and reduce the risk of investment by investing in the selected European countries.  Stock market cointegration and international diversification is a widely accepted topic among the scholars and academics in recent years.  This current study is motivated from the significant amount of interesting studies in this field. A combination of not perfectly positively correlated instruments gives the investor an opportunity to gain from portfolio diversification.  Similarly, Investors can attain diversification benefit if one country’s stock market is not cointegrated with other country’s stock market.  Six European countries and a time frame of ten years (January, 2001 to December, 2010) have been taken into consideration for the purpose of this research.  The countries are UK, Denmark, Germany, Spain, Poland, and Czech Republic.  The time period of the study is divided into two sub period to observe the recent crisis effect on these selected countries. A quantitative approach is adopted in the research.  We used an econometric model for this research which is Johansen and Juselius multivariate cointegration approach.  The evidence from the study suggest that although cointegration exists among the selected countries in some extent, investors can still get some diversification opportunity by investing in the emerging countries (Czech Republic and Poland).  This study is unique in the sense that in our research, we wanted to fill the research gap by combining new and old EU member countries with the latest time period of study and also considered the recent crisis effect.   This study has a number of implications on portfolio managers, policy makers, and academic scholars.

This thesis describes the design of portfolio for the small family business in the Czech capital market conditions. It works with data from the Prague Stock Exchange and specifically from the Prime Market. The proposed based on Markowitz's portfolio theory and the CAPM model. From the historical data is created several portfolios, which are then compared with each other and have selected the one best suited to profitability and risk. Finally, the selected portfolio is tested under the conditions of the Czech capital market.

Centralized power system planning covers time windows that range from ten to thirty years. Consequently, it is the longest and most uncertain part of power system economics. One of the challenges that power system planning faces is the inability to accurately predict random events; these random events introduce risk in the planning process. Another challenge stems from the fact that, despite having a centralized planning scheme, generation plans are set first and then transmission expansion plans are carried out. This thesis addresses these problems. A joint model for generation and transmission expansion for the vertically integrated industry is proposed. Randomness is considered in demand, equivalent availability factors of the generators, and transmission capacity factors of the transmission lines. The system expansion model is formulated as a two-stage stochastic program with fixed recourse and probabilistic constraints. The transmission network is included via a DC approximation. The mean variance Markowitz theory is used as a risk minimization technique in order to minimize the variance of the annualized estimated generating cost. This system expansion model is capable of considering the locations of new generation and transmission and also of choosing the right mixture of generating technologies. The global tendency is to move from regulated power systems to deregulated power systems. Power pool electricity markets, assuming that the independent system operator is concerned with the social cost minimization, face great uncertainties from supply and demand bids submitted by market participants. In power pool electricity markets, randomness in the cost and benefit functions through random demand and supply functions has never been considered before. This thesis considers as random all the coefficients of the quadratic cost and benefit functions and uses the mean variance Markowitz theory to minimize the social cost variance. The impacts that this risk minimization technique has on nodal prices and on the elasticities of the supply and demand curves are studied. All the mathematical models in this thesis are exemplified by the six-node network proposed by Garver in 1970, by the 21-node network proposed by the IEEE Reliability Test System Task Force in 1979, and by the IEEE 57- and 118-node systems.

Centralized power system planning covers time windows that range from ten to thirty years. Consequently, it is the longest and most uncertain part of power system economics. One of the challenges that power system planning faces is the inability to accurately predict random events; these random events introduce risk in the planning process. Another challenge stems from the fact that, despite having a centralized planning scheme, generation plans are set first and then transmission expansion plans are carried out. This thesis addresses these problems. A joint model for generation and transmission expansion for the vertically integrated industry is proposed. Randomness is considered in demand, equivalent availability factors of the generators, and transmission capacity factors of the transmission lines. The system expansion model is formulated as a two-stage stochastic program with fixed recourse and probabilistic constraints. The transmission network is included via a DC approximation. The mean variance Markowitz theory is used as a risk minimization technique in order to minimize the variance of the annualized estimated generating cost. This system expansion model is capable of considering the locations of new generation and transmission and also of choosing the right mixture of generating technologies. The global tendency is to move from regulated power systems to deregulated power systems. Power pool electricity markets, assuming that the independent system operator is concerned with the social cost minimization, face great uncertainties from supply and demand bids submitted by market participants. In power pool electricity markets, randomness in the cost and benefit functions through random demand and supply functions has never been considered before. This thesis considers as random all the coefficients of the quadratic cost and benefit functions and uses the mean variance Markowitz theory to minimize the social cost variance. The impacts that this risk minimization technique has on nodal prices and on the elasticities of the supply and demand curves are studied. All the mathematical models in this thesis are exemplified by the six-node network proposed by Garver in 1970, by the 21-node network proposed by the IEEE Reliability Test System Task Force in 1979, and by the IEEE 57- and 118-node systems.

The thesis provides a comparison of different portfolio models and tests their performance on the financial markets. Our analysis particularly focuses on comparison of the classical Markowitz modern portfolio theory and the downside risk models of the post-modern portfolio theory. In addition, we consider some alternative portfolio models ending with total eleven models that we test. If the performance of different portfolio models should be evaluated and compared correctly, we must use a measure that is unbiased to any portfolio theory. We suggest solving this issue via a new approach based on the utility theory and utility functions. We introduce the unbiased method for evaluation of the portfolio model performance using the expected utility efficient frontier. We use the asymmetric behavioural utility function to capture the behaviour of the real market investors. The Markowitz model is the leading market practice. We investigate whether there are any circumstances in which some other models might provide better performance than the Markowitz model. Our research is for three reasons unique. First, it provides a comprehensive comparison of broad classes of different portfolio models. Second, we focus on the developed markets in United States and Germany but also on the local emerging markets in Czech Republic and Poland. These local markets have never been tested in such extent before. Third, the empirical testing is based on the broad data set from 2003 to 2012 which enable us to test how different portfolio model perform in different macroeconomic conditions.