<p>There is evidence that globalization, economic assimilation and integration among countries and their financial markets have increased correlation among stock markets and the correlation may in turn impact investors’ allocation of their assets and economic policies. We have conducted a quantitative study with daily stock index quotes for the period January 2000 and December 2009 in order to measure the eventual correlation between the markets of ASEAN+3. This economic integration consists of; Indonesia, Malaysia, Philippines, Singapore, Thailand, China, Japan and South Korea. Our problem formulation is:Are the stock markets of ASEAN+3 correlated?Does the eventual correlation change under turbulent market conditions?In terms of the eventual correlation, discuss: is it possible to diversify an investment portfolio within this area?The purpose of the study is to conduct a research that will provide investors with information about stock market correlation within the chosen market. We have conducted the study with a positivistic view and a deductive approach with some theories as our starting point. The main theories discussed are; market efficiency, risk and return, Modern Portfolio Theory, correlation and international investments. By using the financial datatbase, DataStream, we have been able to collect the necessary data for our study. The data has been processed in the statistical program SPSS by using Pearson correlation.From the empirical findings and our analysis we were able to draw some main conclusions about our study. We found that most of the ASEAN+3 countries were strongly correlated with each other. Japan showed lower correlation with all of the other countries. Based on this we concluded that economic integration seems to increase correlation between stock markets. When looking at the economic downturn in 2007-2009, we found that the correlation between ASEAN+3 became stronger and positive for all of the countries. The results also showed that the correlation varies over time. We concluded that it is, to a small extent, possible to diversify an investment portfolio across these markets.</p>

There is evidence that globalization, economic assimilation and integration among countries and their financial markets have increased correlation among stock markets and the correlation may in turn impact investors’ allocation of their assets and economic policies. We have conducted a quantitative study with daily stock index quotes for the period January 2000 and December 2009 in order to measure the eventual correlation between the markets of ASEAN+3. This economic integration consists of; Indonesia, Malaysia, Philippines, Singapore, Thailand, China, Japan and South Korea. Our problem formulation is:Are the stock markets of ASEAN+3 correlated?Does the eventual correlation change under turbulent market conditions?In terms of the eventual correlation, discuss: is it possible to diversify an investment portfolio within this area?The purpose of the study is to conduct a research that will provide investors with information about stock market correlation within the chosen market. We have conducted the study with a positivistic view and a deductive approach with some theories as our starting point. The main theories discussed are; market efficiency, risk and return, Modern Portfolio Theory, correlation and international investments. By using the financial datatbase, DataStream, we have been able to collect the necessary data for our study. The data has been processed in the statistical program SPSS by using Pearson correlation.From the empirical findings and our analysis we were able to draw some main conclusions about our study. We found that most of the ASEAN+3 countries were strongly correlated with each other. Japan showed lower correlation with all of the other countries. Based on this we concluded that economic integration seems to increase correlation between stock markets. When looking at the economic downturn in 2007-2009, we found that the correlation between ASEAN+3 became stronger and positive for all of the countries. The results also showed that the correlation varies over time. We concluded that it is, to a small extent, possible to diversify an investment portfolio across these markets.

The paper deals with stock market indices. It reveals the flaws inherent in traditional market capitalization weighted indices, that causes a return drag. At the same time it shows how you can get rid of these flaws by using fundamental indices, and gives proofs about their superiority. The practical part focuses on building fundamental indices of czech stocks traded on the Prague Stock Exchange, dealing with historical data. It empirically demonstrates their outperformance of a benchmark market capitalization weighted index.

Purpose The purpose of this study is to investigate whether abnormal return patterns can occur on different share indices, as a result of the outcome in national team matches. The subordinary aim is to investigate whether there are differences between the three share indices, (small-, mid- and large cap) depending on the match category and how it relates regarding the five countries in the study. Method This study has a positivistic and deductive approach, using a modified event study methodology. The event period is one day after the event. For each nation, year and share index, different estimation periods have been created. The study comprises 760 national team football matches and is investigating how each different share index is affected by match outcomes in championship matches, qualifying matches and friendlies. Results Upon compilation of all 760 matches, the result of this study shows a statistically significant impact on two of the three possible match outcomes, regarding small cap index. Furthermore the result also shows a connection between friendly matches and small cap index. The match categories championship matches and qualifying matches demonstrates no connection to the three diffrent kind of share indices. Regarding the different nations, Spain and their small- and large cap index shows the most significant connection between the match outcome and abnormal return. Conclusions The small cap share index is basically the only index that is affected by the all the matches that is involved in this study (after a victory or a loss). The magnitude of a match does not seem to have a greater influence on investor rationality. Over all, the match outcome draw does not lead to negative abnormal return. Of this studys five surveyed countries (England, France, Spain, Sweden and Germany), the english and german share indicies seems to be least likley to be affected by the outcome in national team football matches.

nÃo hà / This work analyzes the level of financial integration of an economic bloc entitled, on an ad hoc way, BRIC, composed by emerging economies with common and growth patterns, where more than 40% of the population live in one quarter of the worldâs territory. Following methodologically Vahid and Engle (1993), the results suggest that financial markets are determined by domestic economic fundamentals in periods of global economic stability, while in crisis periods, the cycles have greater importance in the composition of the returns of the indices analyzed, indicating a higher influence of financial risk. The individual cycles, as well as the individual trends are robustly correlated. These evidences are not trivial since Brazil is a market economy, with high level of inequality, poverty, democracy and urbanization, Russia is a an exsuperpower socialist, with high per capita income and human capital levels, India is a rural society with strong cultural and religious aspects, while China is a communist dictatorship with a high degree of trade openness and high levels of international reserves. The Indian financial market, which has been undergoing reforms since 1991, is such that the SENSEX-30 index plays important role in terms of predictability of others, as well as its tendency is the only individual to be significant in the exercise of causality Granger in the first common trend, the unique related to a promising scenario. / Este trabalho analisa o nÃvel de integraÃÃo financeira de um bloco econÃmico intitulado, de forma ad hoc, BRIC, composto por emergentes com padrÃes comuns e potenciais de crescimento, os quais dispÃem de um quarto do territÃrio mundial, onde residem mais de 40% da populaÃÃo. Seguindo metodologicamente Vahid e Engle (1993), os resultados sugerem que estes mercados financeiros sejam determinados por fundamentos econÃmicos domÃsticos em perÃodos de estabilidade econÃmica global, enquanto em perÃodos turbulentos, hà uma maior relevÃncia dos ciclos na composiÃÃo dos retornos dos Ãndices analisados, sinalizando uma maior influÃncia de fatores de risco financeiros. Em termos individuais, os ciclos, assim como as tendÃncias dos quatro emergentes sÃo robustamente correlacionados entre si. Estas evidÃncias nÃo sÃo triviais tratando-se se o Brasil de uma economia de mercado desigual, pobre, democrÃtica, fortemente urbanizada, a RÃssia de uma antiga superpotÃncia, exâadepta do socialismo que se destaca pela renda per capita e pelo capital humano, a Ãndia de uma sociedade rural, com forte traÃo cultural e religioso e a China de um comunismo ditatorial com elevado grau de abertura comercial e elevados nÃveis de reservas internacionais. O mercado financeiro indiano, o qual tem passado por reformas na desde 1991, à tal que, o Ãndice SENSEX-30 exerce relevante papel em termos de previsibilidade dos demais, assim como sua tendÃncia individual, a qual à a Ãnica a ser significativa no exercÃcio de causalidade de Granger na primeira tendÃncia comum, a Ãnica que està associada a um cenÃrio promissor.

This thesis focuses on fractal analysis of economic time series. Chapter One introduces fractal analysis as a method of exploring time series and gathers information about progress and current state of understanding in this field. Chapter Two focuses on design and development of computer software, which will calculate selected fractal indices. Chapter Three is experimental and shows the results and discussion of economic time series (popular stock market indexes and currency exchange rate) analysis that have been obtained from the software developed in Chapter Two.