The thesis deals with electoral and partisan cycles in stock returns of nine CEE countries and checks consistency of observed cycles with efficient market hypothesis. The evidence mostly supports possibility of political influence on stock markets, but the effects often have opposite sign than hypothesized. Electoral cycle has been found in Estonia and Hungary, while returns in four other countries are significantly lower before elections. Markets more often exhibit left-wing premium, it is significant in the Czech Republic, Lithuania and Romania. The results are similar between nominal and real returns. Both cycles are also considered significant for the panel of countries. Moreover, cycles are hardly explainable by macroeconomic conditions, which indicates market inefficiency. This is confirmed by analysis of volatility, which reveals that risk does not correspond to changes in returns induced by the cycles.

This thesis deals with the behaviour of stock markets during the period of election process. We focus on the influence of elections to the German Bundestag on stock market performance of the countries allied in Visegrad Group during the reference period 1994-2013 covering six Bundestag elections. Germany is a major export partner for all members of Visegrad Group - the Czech Republic, Hungary, Poland and Slovakia. We examine whether there are abnormal returns on stock markets in Visegrad Group countries around the date of German Bundestag elections. We thus examine if the fact that performance of German economy is important for performance of economies of countries allied in Visegrad Group means that Bundestag elections influences their stock markets. We also analyze the influence of elections to German Bundestag on domestic stock market during the reference period 1961-2013. To measure the effect of elections we employ event study methodology using the mean-adjusted return model to measure normal returns. Our event window consists of 65 trading days around the election day (-15,50). We use the estimation window of 100 days (-150,-51). We assess our main hypothesis for each country around every Bundestag elections in our reference period separately over three event windows and also over eight event...

This dissertation seeks to improve the current understanding of the ways in which institutional reform can promote the development of stock markets in Latin America. Over the past decade, policymakers sought to stimulate the growth of capital markets in the region through the promotion of a standardized set of formal institutions. An example of this approach in the field of company law was the introduction of modern corporate governance practices into nations without a solid enforcement infrastructure. By most accounts, these efforts did not deliver on their promise of stock market development. This work identifies areas for potential reform. As a means to better understand the operation of Latin American stock markets, this dissertation draws from different sources, including the historical experience of industrialized nations, the available literature on institutional reform, the documented shortcomings of legal reform programmes and hand-collected data from various Latin American countries. The resulting analysis suggests that the promotion of Latin American capital markets may require strategies different to those that were set in motion over the past decade. The main contribution of this work is twofold. First, this dissertation brings some nuance to the discussions concerning the challenges faced by Latin American capital markets. A proper understanding of these challenges is essential for policymakers in the region, particularly after the onset of the Latin American Integrated Market. Second, this dissertation explores the use of ‘transitional strategies’ to overcome some of the challenges identified here. The ultimate goal of this project is to inform future reform efforts in Latin America and to offer some insights for policymakers in other emerging countries.

Philosophiae Doctor - PhD (Economics) / The main objective of this thesis was to closely examine several nancial and economic aspects of the stock markets in Sub-Saharan Africa. Thus, the objectives of this thesis were to explore the interdependence, the time-varying conditional correlation and the volatility linkages among Sub-Saharan African and developed stock markets; to investigate the relationship between - nancial liberalization and the development of stock markets; and to examine the patterns of the aggregate market liquidity and the relevance of the mainstream determinants of market liquidity in the chosen Sub-Saharan African stock markets. The study was composed of three standalone essays. The rst essay, which investigated stock price co-movements and the volatility linkages between selected Sub-Saharan African markets and the key developed markets, used the Johansen cointegration test, the VECM and the GARCH models for the sample period 2 January 2009 { 31 December 2016. The second essay, examining the e ect of nancial liberalization on the development of stock markets in Sub-Saharan Africa, employed the Bayesian VAR for the sample period 1975Q1 { 2014Q4. Lastly, the third essay, which investigated the determinants of liquidity levels in Sub-Saharan African stock markets employed the Markov Switching Vector Autoregressive model for the sample period 2 January 2009 { 31 December 2016.This study aimed at contributing to the already existing literature by focusing on analysing four key stock markets in the region, namely the Nigerian Stock Exchange, the Kenyan Securities Exchange.

A previsão de séries temporais financeiras tem sido um tópico popular da literatura nos últimos anos. Contudo, embora muitos estudos de previsão de séries temporais foquem na previsão exata de valores futuros, defendemos que este tipo de previsão é de difícil aplicação em cenários reais, sendo mais vantajoso transformar este problema de previsão em um problema de classificação que indique se a série temporal irá subir ou descer no próximo período. Neste trabalho é proposto um método de compra e venda de ações baseado nas previsões feitas por dois ensembles de redes neurais adaptados para diferentes perfis de investimento: um para investidores moderados e outro para investidores mais agressivos. Os resultados desses ensembles preveem se determinada ação irá subir ou descer no próximo período ao invés de prever seus valores futuros, permitindo que se criem recomendações de operações de compra ou venda para o próximo período de tempo. A criação de tais ensembles, contudo, pode encontrar dificuldades no fato de que cada mercado se comporta de uma maneira diferente: fatores como a sazonalidade e a localidade da bolsa de valores são determinantes no desenvolvimento das redes neurais apropriadas. Para mostrar a eficiência do nosso método em diferentes situações, o mesmo é avaliado exaustivamente em dois conjuntos de dados diferentes: os mercados de ações norteamericano (S&P 500) e brasileiro (Bovespa). Operações reais foram simuladas nestes mercados e fomos capazes de lucrar em 89% dos casos avaliados, superando os resultados das abordagens comparativas na grande maioria dos casos. / Financial time series prediction has been a hot topic in the last years. However, although many time series prediction studies focus on the exact prediction for future values, we defend that this kind of prediction is hard to apply in real scenarios, being more profitable to transform the prediction problem into a classification problem that indicates if the time series is going to raise or fall in the next period. In this work we propose a stock buy and sell method based on predictions made by two neural network ensembles adjusted for different investment profiles: one for moderate investors and another for aggressive investors. The results of these ensembles predict if certain stock will raise of fall in the next time period instead of predicting its future values, allowing the creation of buy and sell operations recommendations for the next time period. The creation of such ensembles, however, can find difficulties in the fact that each market behaves in a different manner: factors as the seasonality and the location of the stock market are determinant in the development of the appropriate neural networks. To show the efficiency of our method in different situations, it is tested exhaustively in two differents datasets: the north american (S&P 500) and brazilian (Bovespa) stock markets. Real operations were simulated in these markets and we were able to profit in 89% of the tested cases, outperforming the results of the comparative approaches in most of the cases.

[pt] O objetivo inicial do presente trabalho é caracterizar a existência das tradicionais anomalias de apreçamento observadas em relação ao CAPM (efeitos Tamanho, Valor e Momento) para o mercado brasileiro de ações, para o período de junho de 1994 a dezembro de 2001. As evidências obtidas mostram a ocorrência do efeito Tamanho, bem como a existência de um forte poder explanatório do Risco de Mercado (Rm-Rf). Subseqüentemente, são realizados testes de apreçamento de ativos utilizando a abordagem de regressões de séries temporais, através da metodologia SUR (Seemingly Unrelated Regressions) e do teste de Gibbons, Ross e Shanken (1989). Os resultados demonstram superioridade do modelo trifatorial de Fama e French tanto quando comparado com o CAPM como em comparação com o modelo de quatro fatores. / [en] The initial aim of the present study is to characterize the existence of the traditional CAPM pricing anomalies (Size, Value and Momentum effects) for the Brazilian stock market for the period from June, 1994 to December, 2001. Evidences obtained show the occurrence of Size effect accompanied by the existence of a strong market-risk premium (Rm-Rf) explanatory power. Subsequently, asset pricing tests are carried out using the time-series regression framework, through SUR (Seemingly Unrelated Regressions) methodology and Gibbons, Ross e Shanken (1989) test. The results demonstrate the Fama and French three-factor pricing model superiority both when compared to the CAPM and to the four- factor pricing model.

This Paper empirically investigates the behavior of Africa’s stock price volatility over time in ten African equity markets. It also attempts to establish the existence of a relationship between volatility and expected returns in the chosen equity markets. The effect of volatility on the stock prices is also investigated, together with establishing variations in the stock return volatility risk premia. Lastly, an investigation of whether volatility is transmitted from international markets to African markets is also undertaken. The sample period starts from November 1998 until December 2016. The preliminary empirical results show a mixed finding in the mean-variance tradeoff theory. Based on the GARCH-type models, the empirical results show that volatility of stock returns show the characteristics of volatility clustering, leptokurtic distribution and leverage effects over time for all the Africa equity markets. A weak relationship between volatility and expected returns is also found in all the African equity markets studied. The results also showed that as volatility increases, the returns correspondingly decrease by a factor of the coefficient for most of the equity markets. These results negate the theory of a positive risk premium on stock indices. It was also observed that stock return volatility risk premia have variations over time. The study also established that there was volatility transmission from the international markets into Africa equity markets. / MT2017

The modelling of stock market volatility is considered to be important for practitioners and academics in finance due to its use in forecasting aspects of future returns. The GARCH class models have now firmly established themselves as one of the foremost techniques for modelling volatility in financial markets. The application of GARCH class models in developed and emerging markets (including the Egyptian Stock Market) provides evidence of GARCH effects in stock returns. However, most of the studies conducted on modelling the volatility of stock returns are based on the aggregated market index. This thesis argues that this will not reflect significant differences of variation in the pattern of volatility associated with different stocks. However, in order to examine the similarities and differences between the conditional variance structures of stocks from the same or different industries in the same equity market, this thesis estimates pooled-panel models. These novel models are used to test for similarities and differences in the conditional variance equation in panels of time series within a general to specific framework of nested tests. This is done using panel samples of sector indices and stocks from the Egyptian Stock Market covering the period from 1997 to 2002. The results suggest that there are similarities in the temporal volatility structures of stocks from the same sector or industry, but there are significant differences in the temporal volatility structures of stocks from different sectors or industries. This suggests that using indices alone for modelling the volatility of an equity market, which is the method used in the majority of studies cited in the literature, may not be appropriate. The thesis concludes with a discussion of some of the implications of these results and suggestions for further research. / Doctor of Philosophy (PhD)

<b>Background</b>: Oil is the most dominating source of energy of today, it constitutes for more than 40 per cent of the worlds total energy consumption. This together with the fact that stock in oil companies has soared on the stock exchanges around the world makes oil a very interesting topic to write within. In order to gain knowledge in how to value oil companies, the authors will collect information from theory and through a questionnaire. By applying the information gathered to three companies listed on the Stockholm Stock Exchange the authors will reach an objective picture of valuation of oil companies. <b>Purpose</b>: To investigate how shares of stock are valuated in the oil exploring and producing industry, and what specific measures and metrics that are used in the valuation of stocks in Exploring and Producing (E&amp;P) companies. <b>Method</b>: By using a qualitative approach for this thesis, the authors will investigate how the valuation of oil companies works and what measures that should be applied. The authors will use a part descriptive and part explorative study. This will fit the thesis as the authors will describe how the measures and metrics work and start from previous research on the topic and go from there to show if that theory and the empirical findings really works. <b>Conclusion</b>: The most recommended valuation method is net present value analysis. Hotelling Valuation Principle is a form of present value analysis for oil companies and is less complicated than a regular net present value analysis. Other than present value analysis, relative measures and ratios are used. Specific for the oil industry and exploring and producing companies are EV/DACF, ROACE, R/P, production cost, unit cost, tax rate and reserve replacement rate. / <b>Bakgrund</b>: Olja är den dominerande källan till energi idag och oljan står för mer än 40 procent av den totala energikonsumtionen i världen. Detta tillsammans med det faktum att aktier i oljeföretag har stigit kraftigt på börser runt om i världen gör olja till ett väldigt intressant ämne att skriva om. För att skaffa kunskap i hur man värderar oljeföretag kommer författarna av denna uppsats samla information från teori på ämnet och genom ett frågeformulär. Genom att applicera insamlad information på tre företag noterade på Stockholmsbörsen hoppas författarna att kunna nå en objektiv bild av hur man värderar oljeföretag. <b>Syfte</b>: Att undersöka hur aktier värderas i oljeindustrin och vilka specifika nyckeltal och metoder som används vid värderingen av aktier i prospekterings- och produktionsbolag. <b>Metod</b>: Genom att använda en kvalitativt tillvägagångssätt för uppsatsen hoppas författarna kunna undersöka hur värdering av oljeföretag fungerar och vilka nyckeltal och metoder som ska användas. Författarna kommer att att i huvudsak använda sig av en deskriptiv studie. Detta anses lägligt för uppsatsen eftersom författarna kommer att beskriva hur nyckeltal och formler fungerar samtidigt som de kommer att utgå från tidigare forskning inom ämnet och därifrån visa på om teorin och de inkomna svaren verkligen fungerar. <b>Slutsats</b>: Den mest rekommenderade värderingsmetoden är nuvärdesanalys. Hotelling Valuation Principle är form av nuvärdesanalys som riktar sig till oljeföretag och är lite mindre komplicerad än vanlig nuvärdesanalys. Förutom nuvärdesanalys används även relativa mått och nyckeltal. De specifika mått som används inom oljeindustrin och prospekterings- och produktionsbolag är EV/DACF, ROACE, R/P, produktionskostnad, kostnad per styck, skattesats, och återfyllnad av reserver.

This study explores the dynamics between stock price and exchange rates through the cointegration methodology proposed by Herwartz and Luetkepohl (2011). Moreover, it consider the vector error correction model (VECM) with conditional heteroscedastic variance. And we use a feasible generalized least squares (FGLS) estimator to estimate the cointegrating vector. This paper analysis some Asian countries' data from 1997 to 2010. The evidence result suggests that Malaysia and Singapor's stock price and exchange rate are positively related. But Hong Kong's stock price is negatively related to exchange rate.