Diploma thesis analyzes factors affecting stock prices of selected insurance companies. The first part focuses on development trends in the insurance industry. Goal of the second part is to introduce selected insurance companies Allianz and American International Group to the reader. The third section focuses on the individual factors and their relationship to stock prices with regard to specific features of insurance companies. Analysis is divided into four levels. First level monitors the impact of global factors, second analyzes macroeconomic indicators of national economy, followed by analysis industry specific factors and company level analyzes factors of individual firms.

The diploma thesis focuses on a fundamental analysis of shares of European multinational food companies. The theoretical part describes methods of fundamental analysis. The analytical part includes testing of stock valuation models, selection of companies, their analysis and comparison. The last part includes proposal of portfolio of the hedge fund.

This diploma thesis deals with the fundamental analysis of selected metals as commodities, for use in the production of batteries for electric vehicles, to hedge against changes in the price of physical raw materials. Selected metals are analyzed based on the fundamental parameters, historical price development and the current situation on the commodity market. Based on these fundamental data, a recommendation is formulated for the method of hedging the prices of selected commodities.

This master's thesis contains an analysis of the Maxprogres, s.r.o. company based on account statements and information given by the firm. It is focusing on an overall review of the firm standing and tries to assess it's internal situation and the environment as well. The theoretical base, which antecedes the whole analysis, clarifies the significance of the particular analysis and describes the way of their completion.

The purpose of this paper is to develop a new and practical technique for improving the art of forecasting security price movements. The desire to forecast stock market fluctuations have led many analysts to employ different predicting tools.

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Determining the locations of devices in mobile ad-hoc networks (MANETs), wireless sensor networks (WSNs), and cellular networks has many important applications. In MANETs, which are useful in disaster recovery, rescue operations, and military communications, location information is used to enable location-aided routing and geodesic packet forwarding. In WSNs, whose applications include environmental monitoring (e.g., for precision agriculture) and asset tracking in warehouses, not only is location information useful for the self-organization of the network, but in addition, tying locations to the sensor observations is crucial for adding meaning to the sensed data. In cellular networks, location information is used to provide subscribers with location-based services in addition to providing public service answering points with potentially life-saving location information during emergency calls. These applications are largely not new, which is evidenced by the fact that the literature is quite rich with localization studies presented over the span of many years. Because of this, it may be surprising to learn that there is a lack of analyses concerning the fundamental factors impacting localization performance. Fundamentally, localization performance depends upon three factors: (i) the number of devices participating in the localization procedure, (ii) the locations of the participating devices, and (iii) the quality of the positioning observations gathered from the participating devices. For the most part, these factors cannot reasonably be considered deterministic. Instead, at any point in time, random effects within a network and its surroundings will determine these factors for individual positioning scenarios. Unfortunately, there are currently no analytical approaches for characterizing localization performance over these random factors. Instead, researchers either provide analytical results for a deterministic set of factors or use complex system-level simulations to obtain general performance insights. While the latter certainly averages over the random factors, the validity of the results is limited by the simulation assumptions. Any change in a network parameter requires running a new time-consuming simulation. In this dissertation, we address current deficiencies in several ways. We present a new model for tractably analyzing network localization fundamentals. This is demonstrated through fundamental analyses of hearability and geometry. Further, collaboration among non-reference devices has recently garnered increasing interest from the research community as a means to (i) improve positioning accuracy and (ii) improve positioning availability. We present fundamental analyses of both of these potential benefits. As a result of our work, we not only characterize several key performance metrics, we also demonstrate that there exist new tractable ways to analyze localization performance. / Ph. D.

Using the Student Investment Fund at Claremont McKenna College as a proxy for inexperienced investors, I demonstrate that inexperienced investors using fundamental analysis produce momentum-like buying patterns. The results show that the Student Investment Fund is on average buying stocks that outperform Carhart’s four-factor asset pricing model in the year before purchase. As a result, the Student Investment Fund has, on average, underperformed the S&P500 by .48% per year since 1996. My thesis explores why the Student Investment Fund may have adopted momentum-like purchasing patterns and what steps can be taken to remedy it.

The aim of this thesis is to examine the dependence of the exchange rate movement on the core fundamentals of the economy in the long term, as well as to test the validity of selected indicators of technical analysis in the short term. The dependence of the exchange rate will be examined using correlation and the discussed fundamentals are the main macroeconomic indicators, such as GDP, short-term interest rates and money base M2. In the part, which deals with the technical analysis, I will test the two groups of indicators, namely trend indicators and oscillators. From the first group it will be simple moving average (SMA), Exponential Moving Average (EMA), the weighted moving average (WMA), the triangular moving average (TMA) and MACD. From the group of oscillators I will test the relative strength index (RSI). All these indicators will be first described in the theoretical part of this thesis. The thesis is divided into two parts - theoretical and practical. The theoretical part includes two chapters which deals with the analysis of the Forex market. The first chapter deals with fundamental analysis. The second chapter deals with technical analysis. In the third chapter I will discuss both methods in practice, with emphasis on technical analysis.

The aim of this thesis is empirical verification of the fundamental theory of exchange rate determination in the case of the currency pair EUR/USD. The theoretical part is devoted to the issue of exchange rate theory, with emphasis on the importance of the currency pair EUR/USD, and major characteristics of the fundamental theory of exchange rate determination. Attention is also paid to methods of analysis of time series, which will be used in the analytical part. The analytical part is devoted to an empirical verification of the underlying theories. On the basis of these theories are developed econometric models, which are then tested using the methods of linear regression and cointegration. The results of the models and their relevance are discussed in conclusion.