In recent times the emergence of the property cycle and the effects that it has on the property market has caused the relevant parties involved in the market to start placing more emphasis on how these cycle works. The overall objective of this study is to try establish if the interpretation of market related data affects at what position these parties are relative to one another on the property curve. The study concentrates on the use of market indicators, indices and variables in trying to determine an individual’s position on the property market curve. It also concentrates on how this market data is retrieved and what effect it has on how they interpret the data. The methodology adopted for this study involves the collecting and interpretation of market related indices and indicators relevant to the property market over a ten year period from 1996 through to 2006. This data was then used to establish the key indicators used. A questionnaire was sent out to the relevant parties involved in the property market to ascertain the extent of what the main sources of market information are and how this data is collected and interpreted. This was limited to individuals in the Gauteng region. The data was examined and collected in the form of line graphs, histograms and pie charts. The data was then examined and presented in four areas: the major sources of information used by parties for market related data, to try and establish where these parties are relative to one another on the property curve, the effect that the different types of sources of information has on each party and finally to try determine by how much these parties lag or lead one another on the curve.

The topic of this thesis is "An Analysis of the Czech Insurance Market." This thesis is divided into three parts. The individual areas of the insurance market and its indicators, which are used for a description and comparison of insurance markets in general, are described within the theoretical part of this thesis. In the second part, the development of the Czech insurance market is discussed with a focus on changes in the legislative framework of the insurance industry and the events that had significant impact on the development of the Czech insurance market. In the final part, an analysis of the Czech insurance market is conducted, which is based on an evaluation of indicators defined in the theoretical part and the various developments in the life and non-life insurance markets during the examined period are discussed.

The diploma thesis deals with the analysis of Dexia bank Slovakia during the years 2000 and 2011. It Gradually analyses the balance sheet, income statement and chosen indicators of financial analysis: indebtedness, profitability, liquidity, productivity, capital adequacy and capital market indicators, which are accompanied by the course of share prices and rating of the bank. Within every indicator is discussed their change in time, impact of financial crisis and changes caused by the entry of a new majority shareholder of the bank in 2011.

O coeficiente beta, definido no contexto do modelo de avaliação de ativos denominado Capital Asset Pricing Model, tem sido amplamente utilizado no Setor Elétrico Brasileiro. Sua aplicação tem sido importante não apenas no âmbito das revisões tarifárias conduzidas pelo órgão regulador, mas também para análise das empresas do setor pelos investidores em mercado de capitais. Embora a aplicação do modelo CAPM seja simples, ele é construído sobre hipóteses rigorosas, que nem sempre são observáveis no mercado real, principalmente em países emergentes. Inserido no referencial teórico deste Modelo, o presente trabalho tem como o objetivo analisar a utilização do coeficiente beta no setor elétrico brasileiro, identificando potenciais distorções que decorram de sua aplicação. Adicionalmente, este trabalho busca analisar o comportamento desse coeficiente de mercado ao longo do período de 1999 a 2007, identificando possíveis tendências. Para isso, lança-se mão de dados que são amplamente utilizados pelos agentes do mercado de capitais, oriundos de uma amostra de empresas que, por possuírem dados disponibilizados em bolsa de valores tornam viável gerar este coeficiente. Das análises realizadas é possível concluir que o coeficiente beta obtido com dados do mercado brasileiro apresentou valores bem próximos aos coeficientes obtidos em mercados desenvolvidos. Também foi possível constatar que os segmentos de distribuição e geração apresentam, no mercado brasileiro, betas desalavancados de mesma ordem de grandeza entre si, embora o segmento de geração seja mais concorrencial e, no de distribuição, predomine um contexto de monopólio natural. / The coefficient beta, defined in the context of the Capital Asset Pricing Model, has been widely applied within the Brazilian electricity industry. Its application has been conducted not only by the regulatory authority regarding tariff review of regulated electricity concessionaires, but also largely used by investors in Brazilian the capital market. Although the CAPM tool is a straight forward one, the Model itself was built under strict assumptions which are not often found in the real world, mainly in developing countries. Departing from this theoretical framework, this master thesis analyses the coefficient beta within the Brazilian electricity industry, identifying potential distortions derived from its application. Additionally, this work examines the coefficient beta behavior throughout 1999 up to 2007, pointing possible trends. For generating the beta coefficient, it is used the same sort of data usually selected by market investors, applied to a set of select companies belonging to the Brazilian electricity industry that have their information publicly disclosed in the financial and stock markets. The result of the analysis pointed that the coefficient beta generated for the Brazilian companies analyzed did not differ much form those of companies belonging to the electricity industry of developed countries. It was also perceived that the segments of electricity distribution and electricity generation presented unlevered betas of the same magnitude although generating companies operates in a competitive market and distribution concessionaires face predominantly a natural monopoly context.

O coeficiente beta, definido no contexto do modelo de avaliação de ativos denominado Capital Asset Pricing Model, tem sido amplamente utilizado no Setor Elétrico Brasileiro. Sua aplicação tem sido importante não apenas no âmbito das revisões tarifárias conduzidas pelo órgão regulador, mas também para análise das empresas do setor pelos investidores em mercado de capitais. Embora a aplicação do modelo CAPM seja simples, ele é construído sobre hipóteses rigorosas, que nem sempre são observáveis no mercado real, principalmente em países emergentes. Inserido no referencial teórico deste Modelo, o presente trabalho tem como o objetivo analisar a utilização do coeficiente beta no setor elétrico brasileiro, identificando potenciais distorções que decorram de sua aplicação. Adicionalmente, este trabalho busca analisar o comportamento desse coeficiente de mercado ao longo do período de 1999 a 2007, identificando possíveis tendências. Para isso, lança-se mão de dados que são amplamente utilizados pelos agentes do mercado de capitais, oriundos de uma amostra de empresas que, por possuírem dados disponibilizados em bolsa de valores tornam viável gerar este coeficiente. Das análises realizadas é possível concluir que o coeficiente beta obtido com dados do mercado brasileiro apresentou valores bem próximos aos coeficientes obtidos em mercados desenvolvidos. Também foi possível constatar que os segmentos de distribuição e geração apresentam, no mercado brasileiro, betas desalavancados de mesma ordem de grandeza entre si, embora o segmento de geração seja mais concorrencial e, no de distribuição, predomine um contexto de monopólio natural. / The coefficient beta, defined in the context of the Capital Asset Pricing Model, has been widely applied within the Brazilian electricity industry. Its application has been conducted not only by the regulatory authority regarding tariff review of regulated electricity concessionaires, but also largely used by investors in Brazilian the capital market. Although the CAPM tool is a straight forward one, the Model itself was built under strict assumptions which are not often found in the real world, mainly in developing countries. Departing from this theoretical framework, this master thesis analyses the coefficient beta within the Brazilian electricity industry, identifying potential distortions derived from its application. Additionally, this work examines the coefficient beta behavior throughout 1999 up to 2007, pointing possible trends. For generating the beta coefficient, it is used the same sort of data usually selected by market investors, applied to a set of select companies belonging to the Brazilian electricity industry that have their information publicly disclosed in the financial and stock markets. The result of the analysis pointed that the coefficient beta generated for the Brazilian companies analyzed did not differ much form those of companies belonging to the electricity industry of developed countries. It was also perceived that the segments of electricity distribution and electricity generation presented unlevered betas of the same magnitude although generating companies operates in a competitive market and distribution concessionaires face predominantly a natural monopoly context.

Computational Intelligence has found a challenging testbed for various paradigms in the financial sector. Extensive research has resulted in numerous financial applications using neural networks and evolutionary computation, mainly genetic algorithms and genetic programming. More recent advances in the field of computational intelligence have not yet been applied as extensively or have not become available in the public domain, due to the confidentiality requirements of financial institutions. This study investigates how co-evolution together with the combination of par- ticle swarm optimisation and neural networks could be used to discover competitive security trading agents that could enable the timing of buying and selling securities to maximise net profit and minimise risk over time. The investigated model attempts to identify security trend reversals with the help of technical analysis methodologies. Technical market indicators provide the necessary market data to the agents and reflect information such as supply, demand, momentum, volatility, trend, sentiment and retracement. All this is derived from the security price alone, which is one of the strengths of technical analysis and the reason for its use in this study. The model proposed in this thesis evolves trading strategies within a single pop- ulation of competing agents, where each agent is represented by a neural network. The population is governed by a competitive co-evolutionary particle swarm optimi- sation algorithm, with the objective of optimising the weights of the neural networks. A standard feed forward neural network architecture is used, which functions as a market trend reversal confidence. Ultimately, the neural network becomes an amal- gamation of the technical market indicators used as inputs, and hence is capable of detecting trend reversals. Timely trading actions are derived from the confidence output, by buying and short selling securities when the price is expected to rise or fall respectively. No expert trading knowledge is presented to the model, only the technical market indicator data. The co-evolutionary particle swarm optimisation model facilitates the discovery of favourable technical market indicator interpretations, starting with zero knowledge. A competitive fitness function is defined that allows the evaluation of each solution relative to other solutions, based on predefined performance metric objectives. The relative fitness function in this study considers net profit and the Sharpe ratio as a risk measure. For the purposes of this study, the stock prices of eight large market capitalisation companies were chosen. Two benchmarks were used to evaluate the discovered trading agents, consisting of a Bollinger Bands/Relative Strength Index rule-based strategy and the popular buy-and-hold strategy. The agents that were discovered from the proposed hybrid computational intelligence model outperformed both benchmarks by producing higher returns for in-sample and out-sample data at a low risk. This indicates that the introduced model is effective in finding favourable strategies, based on observed historical security price data. Transaction costs were considered in the evaluation of the computational intelligent agents, making this a feasible model for a real-world application. Copyright / Dissertation (MSc)--University of Pretoria, 2010. / Computer Science / unrestricted

The main aim of this dissertation thesis is to present a new system of statistical information concerning the labour market in the Czech Republic with respect to the theoretical background as well as to latest trends in the labour market statistics. The structure of the thesis is as follows. In the first chapter, there is a theoretical framework of the labour market introduced. This framework interlinks relations among employees and employers and is neutral with respect to all the economic schools of thought. Besides, I describe an actual state of the labour market statistics in the Czech Republic and evaluate its compliance with the theoretical research. The second chapter is focused on the state of the art concerning labour market statistics from the point of view of both data integration and comprehensive systems of labour market indicators. In the first part of the third chapter, there is a proposal of the new system of statistical information concerning the labour market that complies with both the economic theory and latest trends in the labour market statistics. The most likely advantage of the new system is the fact that all the key aspects of the labour market (i.e. employment as well as remuneration) are surveyed and evaluated together. In addition to the generally known indicators of both economic activity and remuneration, I propose new indicators of job creation, job destruction, hires, separations, job reallocation and worker reallocation. In the second part of the third chapter, there is a proposal of the integrated data source that will allow us to quantify all indicators provided that there are no legal restrictions concerning data integration in the Czech Republic. In last two parts of the third chapter, there are discussed both the main issues concerning the implementation of the system and the pros and cons of the system. There have never been quantified the indicators concerning job and employee flows using the linked employer-employee data in the Czech Republic, so the pilot results are introduced in the fourth chapter. It is obvious that using the new system, we could prove some hypotheses that were impossible to prove using standard set of indicators. In the last part of the fourth chapter, there are worker and job flows balanced with respect to the stock information concerning labour market in the Czech Republic. In the fifth chapter, I investigate the possibility of a wider use of the new system in order to be able to identify and analyse an array of labour market phenomena in more detail. The thesis brings a new insight to the dynamics of the labour market compared to the generally known basic set of labour market indicators. The systematic approach, based on a wider use of linked employer-employee microdata combined with new indicators, has the advantages of a higher information capability as well as of complying with the requirements of the academics.