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Title: Robust Monitoring Procedures for Dependent Data Author: Ondřej Chochola Department: Department of Probability and Mathematical Statistics Supervisor: Prof. RNDr. Marie Hušková, DrSc. Supervisor's e-mail address: huskova@karlin.mff.cuni.cz Abstract: In the thesis we focus on sequential monitoring procedures. We extend some known results towards more robust methods. The robustness of the procedures with respect to outliers and heavy-tailed observations is introduced via use of M-estimation instead of classical least squares estimation. Another extension is towards dependent and multivariate data. It is assumed that the observations are weakly dependent, more specifically they fulfil strong mixing condition. For several models, the appropriate test statistics are proposed and their asymptotic properties are studied both under the null hypothesis of no change as well as under the alternatives, in order to derive proper critical values and show consistency of the tests. We also introduce retrospective change-point procedures, that allow one to verify in a robust way the stability of the historical data, which is needed for the sequential monitoring. Finite sample properties of the tests need to be also examined. This is done in a simulation study and by application on some real data in the capital asset...

Made available in DSpace on 2010-04-20T20:08:22Z (GMT). No. of bitstreams: 0 Previous issue date: 1995-03-27T00:00:00Z / Trata da determinação das taxas de desconto ajustadas ao risco para avaliação, pelo método do fluxo de caixa descontado, do valor econômico de estatais brasileiras privatizadas no período 1991-1992. Utiliza conceitos financeiros como valor presente líquido, eficiência de mercado, capital asset pricing model e risco sistemático, que são aplicados a dados do mercado de capitais e demonstrativos financeiros das empresas. Com as metodologias de regressão linear simples múltipla, desenvolve uma equação que relaciona índices fundamentais com os coeficientes de risco sistemático (betas) das empresas de uma amostra, que por sua vez serve para estimar os coeficientes de risco das estatais.

Investors and fund managers have, since the start of financial markets, always been on the lookout for new ways of beating the market. However, researchers of the Efficient Market Hypothesis have shown that markets are usually highly efficient, implying that there are few possibilities of earning returns that are higher than the market returns, on a risk adjusted basis. Prevailing theories, such as the Capital Asset Pricing Model, has shown that increased return must stem from taking on higher risk. Though, this model’s explanatory power has been challenged by numerous researchers who propose different factors, other than market risk, which could hold explanatory power when it comes to returns in the stock market. This area of research is called factor investing, and has shown that factors such as momentum, size, and value, all can lead to outperforming the market.This study examines how a model based on two common factors, quality and value, would have performed on the Swedish stock market. The study is based on five portfolios chosen by the quality and value factors, each one held for 5 years, examined over a 25-year time span and uses the capital asset pricing model as a tool to measure whether or not the selected factors outperform the market. The study has taken a quantitative approach to examining the research question, using a positivistic and objectivistic view.The results of the study show evidence that the quality and value factors can lead to significant outperformance relative to the market index. Both total returns and risk adjusted returns were higher than the market index for some of the portfolios created using the quality and value factors. Furthermore, statistical evidence was found of that CAPM not fully explains all returns, and thus, that the returns are in part explained by the quality and value factors. The findings led to the conclusion that the quality and value factors does, in fact, hold explanatory power beyond that of CAPM. Purchasing quality companies at a reasonable price is shown to be a sound investment strategy, and that a portfolio created using the quality and value factors has good chances of outperforming the market index.

This paper examines the capital - asset pricing model (CAPM) which has been extended with a factor for geo-political risk. I use monthly stock return data for all stocks listed on a major US exchange from January 1990 to December 2016 and utilize a Fama-Macbeth Regression with Newey-West standard errors to test the geo-political augmented Sharpe-Lintner CAPM. The paper first determines if increased sensitivity to geopolitical risk lead s to lower average returns and second assesses if geo-political risk as an explanatory variable is a significant enough to expose a failure of the CAPM to capture expected returns fully through beta. The results of our regressions do not confirm the hypothesis that firms with high sensitivities to geo-political risk have expressly different returns in the long run. Furthermore, our Fama-Macbeth regression does not find expressly significant average slopes for geo-political risk as a variable.