A análise de risco de mercado, o risco associado a perdas financeiras resultantes de utilizações de preços de mercado, é fundamental para instituições financeiras e gestores de carteiras. A alocação dos ativos nas carteiras envolve decisões risco/retorno eficientes, frequentemente limitadas por uma política de risco. Muitos modelos tradicionais simplificam a estimação do risco de mercado impondo muitas suposições, como distribuições simétricas, correlações lineares, normalidade, entre outras. A utilização de cópulas exibiliza a estimação da estrutura de dependência dessas séries de tempo, possibilitando a modelagem de séries de tempo multivariadas em dois passos: estimações marginais e da dependência entre as séries. Neste trabalho, utilizou-se um modelo de cópulas com dinâmica semiparamétrica para medição de risco de mercado. A estrutura dinâmica das cópulas conta com um parâmetro de dependência que varia ao longo do tempo, em que a proposta semiparamétrica possibilita a modelagem de qualquer tipo de forma funcional que a estrutura dinâmica venha a apresentar. O modelo proposto por Hafner e Reznikova (2010), de dinâmica semiparamétrica, é comparado com o modelo sugerido por Patton (2006), que apresenta dinâmica paramétrica. Todas as cópulas no trabalho são bivariadas. Os dados consistem em quatro séries de tempo do mercado brasileiro de ações. Para cada um desses pares, utilizou-se modelos ARMA-GARCH para a estimação das marginais, enquanto a dependência entre as séries foi estimada utilizando os dois modelos de cópulas dinâmicas mencionados. Para comparar as metodologias estimaram-se duas medidas de risco de mercado: Valor em Risco e Expected Shortfall. Testes de hipóteses foram implementados para verificar a qualidade das estimativas de risco. / Market risk management, i.e. managing the risk associated with nancial loss resulting from market price uctuations, is fundamental to nancial institutions and portfolio managers. Allocations involve e cient risk/return decisions, often restricted by an investment policy statement. Many traditional models simplify risk estimation imposing several assumptions, like symmetrical distributions, the existence of only linear correlations, normality, among others. The modelling of the dependence structure of these time series can be exibly achieved by using copulas. This approach can model a complex multivariate time series structure by analyzing the problem in two blocks: marginal distributions estimation and dependence estimation. The dynamic structure of these copulas can account for a dependence parameter that changes over time, whereas the semiparametric option makes it possible to model any kind of functional form in the dynamic structure. We compare the model suggested by Hafner and Reznikova (2010), which is a dynamic semiparametric one, with the model suggested by Patton (2006), which is also dynamic but fully parametric. The copulas in this work are all bivariate. The data consists of four Brazilian stock market time series. For each of these pairs, ARMA-GARCH models have been used to model the marginals, while the dependences between the series are modeled by using the two methods mentioned above. For the comparison between these methodologies, we estimate Value at Risk and Expected Shortfall of the portfolios built for each pair of assets. Hypothesis tests are implemented to verify the quality of the risk estimates.

Made available in DSpace on 2016-06-02T20:05:59Z (GMT). No. of bitstreams: 1 1642.pdf: 1151544 bytes, checksum: 8fe56d1fcfe5711823ed58e9184fead7 (MD5) Previous issue date: 2007-01-26 / The continuous development of new financial instruments brings more and more investment options for market participants. These investment options also bring a bigger necessity to evaluate the risk embedded in these new financial instruments. Risk Analysis can be defined as an attempt to measure the uncertainty degree in the attainment of the expected return in a financial application and the standard measure to evaluate financial risk is the Value at Risk. This work aims to develop a new approach to estimate the Value at Risk, considering both the market data and the specialists´ opinion. / O desenvolvimento contínuo de novos títulos financeiros possibilita cada vez mais opções de investimento para os participantes do mercado. Este leque de opções de investimentos também traz a necessidade cada vez maior de avaliar o risco que cada novo título financeiro carrega. A análise de riscos pode ser definida como como a tentativa de mensurar o grau de incerteza na obtenção do retorno esperado em uma determinada aplicação financeira. Este trabalho visa desenvolver uma nova abordagem para a estimação do Value at Risk, considerando tanto os dados de mercado quanto a opinião de especialistas

The aim of this master thesis is analyze the impact of new regulatory requirements for market risk in terms of internal approach of the selected portfolio. The first part deals with the definition and calculation methods of risk measures Value at Risk and Expected Shortfall. Furthermore, this part is dedicated to model backtesting and determination of the stress period. The second part describes the development of Basel I-III regulatory requirements for market risk with a focus on internal approaches. The third part focuses on the calculation and subsequent analysis of current and new regulatory reguirements for market risk using the historical simulation method, variance and covariance method and Monte Carlo simulation.

The aim of this diploma thesis is to analyze ways of Value at Risk calculation. Its core is to get a suitable model that could most appropriately reflect the probability distribution of returns of the Czech stock portfolio that we have generated. In this thesis we find out that the returns follow unbounded distribution which was first described by Johnson (1949). Since we detect that returns are correlated we have to apply appropriate autoregressive process that removes this dependency. In the empirical part we discover an inability of models based on assumptions of normality, to correctly predict the Value at Risk. Historical simulation methods, which have promising backtesting results, are rejected because of the slow adaptation to the recent changes in the market. However, we find a way how to implement Johnson SU distribution into the GARCH model. This model, which passes all the tests, is thus able to predict Value at Risks of the portfolio most accurately. JEL Classification: C16, C22, G11 Keywords: Market risk, Value at Risk, Risk management, Johnson SU distribution

This master thesis deals with the area of commercial bank's external audit in the Czech Republic. Its main goal is to highlight the different techniques and specific procedures which are used during statutory audit of commercial bank. Another goal of this master thesis is to investigate of a linear dependence between count of changes of auditors and selected commercial bank's performance indicators. In the first part we could find a general framework of the external audit with emphasis on legal aspects. The second part describes differences between bank and non-banking institution. The third part of this master thesis deals with a description of audit phases with emphasis on the interim audit phase at which the author of this master thesis was a part of audit providing team. The final part investigates the linear dependence between count of changes of auditors and selected commercial bank's performance indicators.

The priority of this work is to show the importance of risk management and the proper operation in electricity trading companies. In the theoretical part of the thesis are summarized basic information about the energy market in the Czech Republic and also a brief overview of the risks observed in the electricity trading. In recent years there have been several cases where a company did not observe their risks or even did not monitor these risks at all. This had a negative impact on the entire Czech energy market. In the practical part of this thesis are described the cases of companies Moravia Energo a.s. and Korlea Invest a.s., setting its risk management and also consequences of their falls. Furthermore, this work describes the different tools to support risk management, which are not the cheapest definitely. Also work contains an example of calculating the limits for credit exposure of the two companies that I calculated based on the analysis of the annual reports of these companies and I managed to get a lot of interesting information during writing this work that the reader will definitely appreciate.

Solvens II är ett nytt regelverk för försäkringsbolag inom EU som ska träda i kraft 2016. Tidigare forskning har diskuterat effekterna av det nya regelverket och förutspår att det kommer att påverka försäkringsbolagens tillgångsallokering. Syftet med denna studie är att studera optimala tillgångsallokeringar för livbolag, både med avseende på interna krav på risk och avkastning och externa kapitalkrav i Solvens II. En fallstudie utförs på ett svenskt livbolag för att ta fram en modell för optimala tillgångsallokeringar, som även tar hänsyn till livbolagets framtida utbetalningar. En optimal allokering tas fram med hjälp av kvadratisk optimering på risk och kapitalkrav givet en viss förväntad avkastning och den nuvarande allokeringen jämförs med olika optimala portföljer. Resultaten visar att det är möjligt att optimera allokeringen både ur ett risk- och avkastningsperspektiv samt  apitalkravsperspektiv, men att de optimala tillgångsportföljerna skiljer sig åt markant. Detta arbete påvisar att det finns en betydande skillnad på risk, mätt genom antingen historisk volatilitet eller kapitalkrav. Ett exempel är tillgångsklassen hedgefonder som har en låg historisk volatilitet men har ett högt kapitalkrav i Solvens II. Denna studie bidrar till befintlig forskning genom att utveckla ett ramverk för investeringar för ett livbolag i Solvens II som tar hänsyn till kapitalkrav för olika tillgångar. / Solvency II is a new regulatory framework concerning insurance companies in the European Union, to be introduced in 2016. The effects of the regulation have been discussed and previous literature believes it will have a significant effect on insurance companies’ asset allocation. The aim of this thesis is to investigate the optimal asset allocation for a life insurer with respect to internal risk-return requirements and external capital requirements imposed by Solvency II. The thesis performs a case study on a Swedish life insurer for the purpose of developing and evaluating an asset allocation model which incorporates future liabilities of the life insurer. Through quadratic optimization, the asset allocation is optimized for portfolios associated with a certain expected return and the current allocation is compared to optimal portfolios. The results show that it is possible to optimize the asset allocation from both a risk-return and capital requirement perspective. However, they are subject to large shifts in asset allocation. The thesis also shows that there is a large discrepancy of risk from a standard deviation standpoint and regulatory capital charges. One example are hedge funds which have shown a low historical volatility but are classified as an asset with high risk in Solvency II. This study contributes to theory by providing an investment decision framework for life insurers that includes capital charges for asset allocation.

When measuring market risk, credit institutions and Alternative Investment Fund Managers may deviate from equally weighting historical data in their Value-at-Risk calculation and instead use an exponential time series weighting. The use of expo-nential weighting in the Value-at-Risk calculation is very popular because it takes into account changes in market volatility (immediately) and can therefore quickly adapt to VaR. In less volatile market phases, this leads to a reduction in VaR and thus to lower own funds requirements for credit institutions. However, in the ex-ponential weighting a high volatility in the past is quickly forgotten and the VaR can be underestimated when using exponential weighting and the VaR may be un-derestimated. To prevent this, credit institutions or Alternative Investment Fund Managers are not completely free to choose a weighting (decay) factor. This article describes the legal requirements and deals with the calculation of the permissible weighting factor. As an example we use the exchange rate between Euro and Polish zloty to estimate the Value-at-Risk. We show the calculation of the weighting factor with two different approaches. This article also discusses exceptions to the general legal requirements.

With a background in EU regulations and an increased interest in Environmental, Social, and Governence (ESG) policies in companies when investing, this thesis considers the individual contributions to market risk in portfolios by different ESG parameters. It explores two different methods to examine if there are effects consistent across the whole Nordic markets, and the possibility to express any effects within portfolios in a clear way. It uses the OMXNORDIC index as the market index and two different fund portfolios as example portfolios, one of which is an article 9 fund. The quantile regression approach does not show any consistent effects across the whole Nordic market from any ESG parameter explored. It does however make for a clear way to present the effects on the portfolio level for each ESG parameter. The employed Copula approach does show some consistent difference between the ESG parameters for the market and in portfolios, as well as differences between the portfolios. Both of the explored methods should allow for comparisons between, and reports on, fund portfolios which would improve the ESG analyses of funds. / Mot bakgrund av EU-lagstiftning och ett ökat intresse i företags förhållning till Environmental, Social, och Governence (ESG) frågor, så utforskar den här uppsatsen ESG-faktorers bidrag till marknadsrisk i fondportföljer och på den nordiska marknaden. Uppsatsen använder två olika metoder för att undersöka om det finns potentiella konsekventa effekter på den Nordiska aktiemarknaden, och möjligheten att presentera resultat på portföljnivå på ett tydligt sätt. OMXNORDIC används som marknadsindex, och två olika fondportföljer används som exempelportföljer, varav en är en artikel 9 fondportfölj. Quantile regression-metoden visar inte på några konsekventa effekter över hela den nordiska marknaden, för någon av ESG-parametrarna. Däremot så resulterar metoden i ett tydligt sätt att presentera påverkan av ESG-parametrarna på portföljnivå. Copula-metoden som används visar på några konsekventa skillnader mellan ESG-parametrar, både för marknaden och i fondportföljerna, samt skillnader mellan portföljerna i sig. Båda metoderna lämpar sig till att jämföra och bygga rapporter på fondportföljer, vilket borde leda till bättre ESG-analyser av fonder.

We investigate various methods for generating a market-based proxy for climate related transition risk in financial markets, and use these to determine the sensitivities of various investments towards climate change policies. We find that assets tied to the energy and materials sector have consistently high sensitivity towards market factors which are likely to decline in response to climate regulations, and as such consequently face mark-to-market losses conditional on systemic climate events. For beta estimation we use both traditional linear regression and the dynamic conditional beta model developed by Engle, based on multivariate GARCH volatility models. We find suggestive evidence that our stylised climate factors, based on stranded assets, responds negatively to news of policies related to a move towards renewable energies. / Vi undersöker olika metoder för att skapa en marknadsbaserad proxy för klimatrisk inom finansmarknaden, och använder dessa för att bestämma känsligheter för olika investeringar mot klimatrelaterade händelser. Vi finner att tillgångar med koppling mot sektorer såsom energi eller material har konsekvent hög känslighet mot marknadsfaktorer som sannolikt kommer minska som svar till klimatbestämmelser, och således också tappa marknadsvärde vid en systemisk klimathändelse. Vi uppskattar ett klimatbeta genom både linjär regression, och Engles dynamic conditional beta modell baserad på en GARCH process i flera variabler. Vi finner suggestiva bevis för att våra klimatfaktorer, baserade på strandade tillgångar, svarar negativt till nyheter som hanterar omställningen till förnybar energi.