Background: The expansive monetary policy of the European Central Bank has been leading to all-time-low interest rates and to a strong move into real estate investment. Low interest rates can work in favor of the investor (due to low interest rate expenditures), but increasing interest rates can jeopardize real estate investments. Since changes in interest rates are unpredictable, an investor needs to deal with this volatility. The capital market offers several financial instruments (so-called “derivatives”) to overcome the above-mentioned obstacle. There is no “one-size-fits-all” strategy. The investor needs to decide which financing structure to combine with which form of derivative. Purpose: The investigation not only explains and shows how real estate financing and hedging strategies on a given project in Germany can work but also explains why it is crucial to link these segments. To achieve this purpose, the return on equity and return cash flows at risk are numerically estimated. The evaluative purpose will be served by using the above-mentioned ratios and cash flows to derive recommendations of action. In doing so, this study will illustrate the importance of hedging, particularly for real estate investors and investors in general. Method: Interest rates on a monthly basis for the period of June 1990 until March 2017 from Thomson Reuters Eikon and real life data from a German real estate investor and a German financial institution were collected. Thereafter, these numbers were used as a basis to perform interest rate and cash flow simulations (Monte Carlo). The simulations were used to determine superior financing and hedging strategies for the investor. Conclusion: The results of this study highlight the benefits from leveraged financing and the necessity of interest rate risk management (hedging) to obtain stabilized future cash flows and reduce volatility caused by fluctuating interest rates. Fixed rate loans offer protection against rising interest rates, but lack flexibility. Floating loans offer more flexibility but are riskier due to the unhedged interest rate exposure.

The thesis focuses on pricing complex options using Monte Carlo simulations. Due to the versatility of the Monte Carlo method, we are able to evaluate option prices with various underlying asset models: jump diffusion models, illiquidity models, stochastic volatility and so on. Both European options and Bermudan options are studied in this thesis.For the jump diffusion model in Merton (1973), we demonstrate European and Bermudan option pricing by the Monte Carlo scheme and extend this to multiple underlying assets; furthermore, we analyse the effect of stochastic volatility.For the illiquidity model in the spirit of Glover (2008), we model the illiquidity impact on option pricing in the simulation study. The four models considered are: the first order feedback model with constant illiquidity and stochastic illiquidity; the full feedback model with constant illiquidity and stochastic illiquidity. We provide detailed explanations for the present of path failures when simulating the underlying asset price movement and suggest some measures to overcome these difficulties.

There are some existing commonly used goodness-of-fit tests, such as the Kolmogorov-Smirnov test, the Cramer-Von Mises test, and the Anderson-Darling test. In addition, a new goodness-of-fit test named G test was proposed by Chen and Ye (2009). The purpose of this thesis is to compare the performance of some goodness-of-fit tests by comparing their power. A goodness-of-fit test is usually used when judging whether or not the underlying population distribution differs from a specific distribution. This research focus on testing whether the underlying population distribution is an exponential distribution. To conduct statistical simulation, SAS/IML is used in this research. Some alternative distributions such as the triangle distribution, V-shaped triangle distribution are used. By applying Monte Carlo simulation, it can be concluded that the performance of the Kolmogorov-Smirnov test is better than the G test in many cases, while the G test performs well in some cases.

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This thesis is focused on a theoretical explication of the basic methods of the calculation Value at Risk for the market and credit risk. For the market risk there is in detail developed the variance -- covariance method, historical simulation and Monte Carlo simulation, above all for the nonlinear portfolio. For all methods the assumptions of their applications are highlighted and the comparation of these methods is made too. For the credit risk there is made a theoretical description of CreditMetrics, CreditRisk+ and KMV models. Analytical part is concerned in the quantification of Value at Risk on two portfolios, namely nonlinear currency portfolio, which particular assumptions of the variance -- covariance method a Monte Carlo simulation are tested on. Then by these methods the calculation of Value at Risk is realized. The calculation of Credit Value at Risk is made on the portfolio of the US corporate bonds by the help of CreditMetrics model.

This master's thesis is dealing with the topic of employee stock options (ESOs), primarily with the valuation of ESOs in accordance with the accounting standard IFRS 2 at corresponding fair value basis. The goal of this thesis is a critical analysis of the standard mentioned, with respect to the conditions of the Czech Republic. The theoretical part comes with the basic characteristics of employee stock options and explains how the traditional option-valuation models can be modified for the purpose of ESOs valuation. It is also concerned with discussion about fundamental features of the fair value basis necessary for the valuation process. The essential part of this thesis is the critical analysis focusing on the rationality of accounting methods, disclosure requirements and also on a theoretically correct determination of model inputs. Critical analysis is followed by case study aimed on evaluation of an authentic option plan. The practical part also demonstrates advanced methods of valuation using the Black-Scholes and the binominal models as well as the Monte Carlo simulation. In the conclusion, I present proposals for changes of the IFRS 2. According to the results of the critical analysis, supported by case study, greatest shortcomings were identified in the disclosure requirements. Proposals for changes are aimed mainly on this problem.

The global financial crisis of 2008, which forced the central banks around the world to defend a financial stability by using non-standard instruments such as quantitative easing, has resulted in, among other things, the fall of the interest rates to zero, and even to negative values in some countries, which has become the new normal in banking field. In this thesis, we focused on the Czech financial market, and we used the method of Monte Carlo simulation in the Vasicek model for the prediction of the future development of interest rates, both short and long maturities. The model shows that in the short term the rates may fall to negative values, but the prediction shows rising interest rates up to their own equilibrium. The 3-months and 6-months rates show surprisingly uncharacteristic behavior, where their long-term decline and higher volatility caused calculation of the equilibrium as a negative value in the Vasicek model. Than we apply the results in the model for calculating changes in the prices of bonds, which are negatively correlated with the interest rates, and we explore the repricing costs for the bondholders. Also, we will show that commercial banks may control the impact of the interest rate risk on capital by composition of financial assets in various categories, where the accounting classification of the instrument is critical to revaluation of the capital.

The goal of this thesis is to compile a strategic business plan of the company Prestar and to identify and evaluate corresponding risks. A substantial part of the turnover is generated by business activities in Russia which recently exhibits unstable development. Strategic analysis is conducted based on the findings, key risk factors are identified and an estimate of the enterprise value based on discounted cash flow is calculated. Finally the influence of the identified risk factors on the enterprise value is simulated using the Monte Carlo method. The key risk factors include wage growth rate, development of sales generated in Russia and the exchange rate.

Orientador: Jorge de Lucas Junior / Resumo: As demandas por energia e alimento aumentarão com as projeções do crescimento populacional mundial. O Brasil está entre os países com o desafio de atender essas demandas. O tratamento dos resíduos gerados na agropecuária tem potencial para produção de biogás e biofertilizante por meio de biodigestores, insumos essenciais para alavancar a produção de alimentos e o desenvolvimento sustentável. Com isso, analisou-se a viabilidade técnica e econômica da codigestão de cama de frango com batata doce ou mandioca visando aumentar a produção de energia e reciclagem de nutrientes dos resíduos da produção de frangos. A utilização de culturas energéticas para codigestão anaeróbia é uma inovação para geração de energia renovável em propriedades rurais e tem ganhado atenção em economias emergentes, que tem como desafio suportar a produção de alimentos com sustentabilidade. O ensaio foi realizado com três tratamentos, cama de frango, cama de frango com batata doce e cama de frango com mandioca. A codigestão com as culturas energéticas foram mais eficientes que a monodigestão. A mandioca superou a batata doce em 17,09% no rendimento médio de biogás diário e reduziu 12 e 3,32% mais sólidos totais e voláteis, respectivamente. No entanto, o potencial de biogás da batata doce 0,449 m3 kg-1SVad e da mandioca 0,457 m3 kg-1SVad não apresentaram diferença significativa, assim como os teores de metano com 61,92 e 61,79%, respectivamente, demonstrando o potencial equivalente das duas culturas na geraç... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Demand for energy and food will increase with projections of world population growth. Brazil is among the countries with the challenge of meeting these demands. The treatment of waste generated in agriculture has the potential to produce biogas and biofertilizer through biodigesters, essential inputs to leverage food production and sustainable development. With this, the technical and economic feasibility of codigestion of chicken with sweet potatoes or manioc was analyzed in order to increase energy production and recycling nutrients from chicken production residues. The use of energy crops for anaerobic codigestion is an innovation for the generation of renewable energy in rural properties and has gained attention in emerging economies, which have the challenge of supporting sustainable food production. The trial was carried out with three treatments, chicken bed, chicken bed with sweet potato and chicken bed with cassava. Codigestion with energy crops was more efficient than monodigestion. Cassava exceeded sweet potatoes by 17.09% in the average daily biogas yield and reduced 12 and 3.32% more total and volatile solids, respectively. However, the biogas potential of sweet potato 0.449 m3 kg-1SVad and cassava 0.457 m3 kg-1SVad did not show any significant difference, as well as the methane contents with 61.92 and 61.79%, respectively, demonstrating the equivalent potential of both cultures in the generation of bioenergy. In addition to the generation of renewable energy, th... (Complete abstract click electronic access below) / Doutor

After the financial crisis of 2008 regulators found that the derivative market, where financial institutions traded OTC derivatives with each other, played a significantrole in triggering the crisis. This led to the emergence of Counterparty Credit Risk(CCR) which is used to measure the exposure banks have to their counterparties. In simple terms CCR is a mix of Market and Credit risk which defines the risk that your counter party will go into bankruptcy. CCR involves the risk factors used in market risk since all of the derivatives are based on underlying assets such as interest rate and currencies. The thesis will focus on how one can backtest individual risk factors driving the value of OTC derivatives. We will present different Monte Carlo simulation techniques that are being used to simulate and represent all possible future outcomes for the risk factors. In order to better understand the performance of a chosen model and how to adjust the calibration window for the ingoing parameters, two different approaches are presented,Quantitative Backtesting and Statistical Backtesting. As an extension to this, a portfolio of interest rate Swaps are backtested whose value are driven by the evolution of the underlying risk factors. The backtesting ofthe portfolio is done with netting. The time horizon for the backtesting procedureis 2010-2020 giving the user up to 261 independent observations with a forecast length of 14 days. Both of the backtesting methods provide the practitioner with a graphical results guiding the user to choose an appropriate model and calibration method for simulating the risk factors. We found that a combination of the two approaches provides the best result. Hence, no backtesting method is superior the other. Instead they complement each other and should be used simultaneously. Using the two backtesting methods one can find a model that perfectly fit the underlying distribution of risk factors, theoretically. However, one should be careful since there will always be uncertainty about the future and there is no guarantee that tomorrow will follow historical evolution exactly.