National Repository of Grey Literature 41 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
Fundamental analysis of a share of BHP Billiton
Lapčík, Filip ; Veselá, Jitka (advisor) ; Fičura, Milan (referee)
This thesis deals with a fundamental analysis of BHP Billiton company, whose shares are listed on exchanges in Johannesburg, London, New York and Sydney. The thesis in its three chapters aims to assess the impact of global, sector, and company factors on the stock price. The first chapter focuses on macro factors that affect the stock price, the second chapter focuses on the state of the sector, regulations, and innovations in the sector, and the third chapter includes calculations of the intrinsic value. An assessment of these factors will result in a recommendation whether the company's shares should be bought or sold.
Application of Monte Carlo simulations in banking
Slanina, Šimon ; Teplý, Petr (advisor) ; Fičura, Milan (referee)
A vigorous advancement in the field of information technologies allows practical use of sophisticated, computing power consuming methods. One of these is the Monte Carlo simulations method, which relies on generating an immense number of stochastic scenarios and can effectively solve problems in areas such as physics or mathematics. Entities in the banking sector are constantly exposed to many kinds of risks, for instance the occurrence of negative interest rates. These risks need to be taken into account, monitored, measured and managed. Even the Monte Carlo method, usable in banking for risk measurement, has its weaknesses that need to be considered, and requires certain conditions to be met. It is crucial to correctly approximate the probability distribution and to create a sufficient number of random scenarios, to use a reliable random number generator and to bear in mind any possible sequential dependencies amongst the input data. In the practical part of this work, I analyzed the development of the London Interbank Offered Rate with a three-month maturity based on the US dollar during the years 2000 to 2016 and, using the Monte Carlo method, I tried to predict its future development as well. I came to the conclusion that the method should be used for forecasting in shorter time horizons, considering it provides significantly wider ranges of the rate's possible values at all probability levels while forecasting for longer time horizons. Via stress test, I also found that the method I applied doesn't really reflect rare short-term shocks in the resulting predictions. Neither the Monte Carlo method nor the TRADING ECONOMICS website anticipate the LIBOR USD 3M rate to fall below zero during the time horizon ending in 2020.
Testing of successfulness of technical analysis' trading and trending indicators
Točevová, Radka ; Veselá, Jitka (advisor) ; Fičura, Milan (referee)
The goal of this master's thesis is to evaluate the successfulness of the strategies' portfolio and of trading and trending indicators, which are parts of the portfolio, through this evaluation. The theoretical part concerns with the key principles of the foreign exchange market which the portfolio is created for. After that, the individual technical indicators, which are used in the analytical part of the thesis, are analyzed in detail. Then in the following part, the development process of automated trading systems in case of the genetic algorithms' application is defined. Individual generated trading systems are described in the next segment separately. Their descriptions are followed by evaluation of outcomes of testing on historical data and of robustness' tests. Afterwards, the correlations between individual strategies are mentioned. The thesis concludes by efficiency evaluation of strategies' portfolio via backtest results and paper testing.
The success rate of candlestick patterns in technical analysis
Vašíček, Marek ; Veselá, Jitka (advisor) ; Fičura, Milan (referee)
This diploma thesis deals with the testing of the success of individual candlestick patterns of technical analysis. In the first part the theoretical basis of technical analysis and candlestick patterns will be presented. The second part will define basic candlestick patterns and their program definition. Backtesting on historical data will verify the success of individual candlestick patterns on EURUSD currency pair. In the third part, a trading system will be built based on the results of the testing of the candlestick patterns. An optimal setting of the trading system will be proposed. The aim of the thesis is to test success rate of candlestick patterns and find out if the candlestick pattern trading system is able to generate profits.
Analysis and Influences of Fundamental news on Gold Prices
Kubaštová, Magdaléna ; Fičura, Milan (advisor) ; Galuška, Jiří (referee)
This master thesis, Analysis and Influences of Fundamental news on Gold Prices deals with macroeconomic variables that drive the price of gold. This paper is divided into three chapters: Possible investment forms in gold, Fundamental analysis of commodities, and lastly Analysis of impact of strong economies and their influence on gold prices. In the first chapter, emphasis is put on the Efficient Market Theory that plays an important role in success or failure of investment strategies such as technical and fundamental analysis. The second chapter illustrates the Commitment of Traders (COT) report and how it is used as a tool to predict the movement of gold prices. This chapter also discusses other large drivers effecting gold prices such as financial and geopolitical stability, inflation, interest rates, Central Banking operations, the value of the US dollar, and other influences. The final chapter analyzes the impact of announced fundamental news in the United States, China, and Europe on the price of gold. The empirical part of this paper analysis the impact of announced fundamental news in United States, China and Europe on gold prices. With the use of the linear regression method, we can test whether the macroeconomic variables significantly influence the return on gold investments immediately after their announcement, or over long periods of time. If this new public data was calculated into gold prices directly, investors would not be able to achieve additional returns by using fundamental analysis. The major findings are summed up at the end of the last chapter.
Asset Pricing in Emerging Markets
Ajrapetova, Tamara ; Witzany, Jiří (advisor) ; Fičura, Milan (referee)
General content: Current methods of estimation of cost of capital in the emerging markets are often neglecting various contradictions with the essentials of the model structure and assumptions. As the result of such imprecisions, the cost of equity is often understated (overstated). This thesis will attempt to assess current level of emerging market integration, liquidity and concentration. This will be followed by evaluation of traditional and alternative models for estimation of cost of equity. The author will address several currently available models such as Credit Rating Model, D-CAPM model, various versions of traditional CAPM models. Furthermore, she will compare and contrast their limitations taking into account the context of emerging markets. The testing of the models will be performed on country basis through the means of index data. In the last chapter, discussion of the results and possible improvements of the valuation approaches will take place.
Analysis of the Impact of Media Important Events on Financial Markets
Siuda, Vojtěch ; Witzany, Jiří (advisor) ; Fičura, Milan (referee)
This thesis analyses the impact of announcements of macroeconomic indicators in United States on price development of the VIX Futures, S&P500 Futures and EUR/USD FX rate. Theoretical part contains construction and description of individual markets. Empirical part investigates the reaction of market prices after 1, 10 and 30 minutes after announcement of an individual indicator value on a market surprise demonstrated as a difference between reported value and analysts' expectations. We tried to find a systematic reaction of market participants and the pace of absorption of new information into the market price. There have been found minimum of situations, where we explained the market move as a linear combination of market surprise. However, there was a several cases, where the market did not adjust to announced information quickly and was inefficient in a short period. In the second part of empirical research we tested all significant models on an out-sample data. The goal was to determine whether the market inefficiencies persisted and stable profit could be achieved. We analysed the brutto performance, then netto performance including all transaction costs. Finally, we defined a simple trading rules with a purpose of profit stabilization and lowering the riskiness of trades. For VIX Futures and EUR/USD markets we achieved a low loss, respectively negligible profit. For S&P 500 Futures we obtained a profit strategies for all selected indicators, total profit was high with a very low volatility of invested capital.
Portfólio Value at Risk a Expected Shortfall s použitím vysoko frekvenčních dat
Zváč, Marek ; Fičura, Milan (advisor) ; Janda, Karel (referee)
The main objective of this thesis is to investigate whether multivariate models using Highfrequency data provide significantly more accurate forecasts of Value at Risk and Expected Shortfall than multivariate models using only daily data. Our objective is very topical since the Basel Committee announced in 2013 that is going to change the risk measure used for calculation of capital requirement from Value at Risk to Expected Shortfall. The further improvement of accuracy of both risk measures can be also achieved by incorporation of high-frequency data that are rapidly more available due to significant technological progress. Therefore, we employed parsimonious Heterogeneous Autoregression and its asymmetric version that uses high-frequency data for the modeling of realized covariance matrix. The benchmark models are chosen well established DCC-GARCH and EWMA. The computation of Value at Risk (VaR) and Expected Shortfall (ES) is done through parametric, semi-parametric and Monte Carlo simulations. The loss distributions are represented by multivariate Gaussian, Student t, multivariate distributions simulated by Copula functions and multivariate filtered historical simulations. There are used univariate loss distributions: Generalized Pareto Distribution from EVT, empirical and standard parametric distributions. The main finding is that Heterogeneous Autoregression model using high-frequency data delivered superior or at least the same accuracy of forecasts of VaR to benchmark models based on daily data. Finally, the backtesting of ES remains still very challenging and applied Test I. and II. did not provide credible validation of the forecasts.
Methods of volatility estimation
Hrbek, Filip ; Witzany, Jiří (advisor) ; Fičura, Milan (referee)
In this masterthesis I have rewied basic approaches to volatility estimating. These approaches are based on classical and Bayesian statistics. I have applied the volatility models for the purpose of volatility forecasting of a different foreign exchange (EURUSD, GBPUSD and CZKEUR) in the different period (from a second period to a day period). I formulate the models EWMA, GARCH, EGARCH, IGARCH, GJRGARCH, jump diffuison with constant volatility and jump diffusion model with stochastic volatility. I also proposed an MCMC algorithm in order to estimate the Bayesian models. All the models we estimated as univariate models. I compared the models according to Mincer Zarnowitz regression. The most successfull model is the jump diffusion model with a stochastic volatility. On the second place they were the GJR- GARCH model and the jump diffusion model with a constant volatility. But the jump diffusion model with a constat volatilit provided much more overvalued results.The rest of the models were even worse. From the rest the IGARCH model is the best but provided undervalued results. All these findings correspond with R squared coefficient.
Coffee Trading on Commodity Markets
Kašička, Jan ; Málek, Jiří (advisor) ; Fičura, Milan (referee)
This thesis offers a comprehensive view of coffee trading on commodity markets. To describe the behavior of prices and their volatility, ARCH and GARCH models are used. These models analyse coffee prices of selected regions in Ethiopia, the birth place of coffee. The thesis connects the characteristics of soft commodity with current knowledge of financial econometrics. It also describes the effects of changes in exchange rates and oil prices on the price of coffee. Price volatility is examined with regard to deregulation and reforms on this market within the last three decades. Developments in the developing world caused a significant need for the progression and identification with the hedging instruments. These are closely linked to the globalized market with coffee, so it is conversely possible to absorb the shocks on small growers, who are significantly impacted by the globalized world.

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