Made available in DSpace on 2016-04-26T20:52:40Z (GMT). No. of bitstreams: 1 Renato Moraes Rocha.pdf: 671679 bytes, checksum: d1040e471942081fc9d367a8d20e1d8d (MD5) Previous issue date: 2015-03-31 / This paper made a comparative analysis of the impact of the financial system in economic growth in the major economies of Latin America (Argentina, Brazil, Chile, Colombia, Mexico and Peru) and members of the G7 (Germany, Canada, France, Italy developed countries, Japan, UK and USA) from the 1970s. The purpose of this analysis was to prove the existence of a non-monotonic relationship between the two main variables, while demonstrating what level the financial system cause negative impact in growth rate in each group of countries / Esta dissertação fez uma análise comparativa entre o impacto do sistema financeiro no crescimento econômico das maiores economias da América Latina (Argentina, Brasil, Chile, Colômbia, México e Peru) e dos países desenvolvidos e integrantes do G7 (Alemanha, Canadá, França, Itália, Japão, Reino Unido e EUA) a partir da década de 1970. A finalidade desta análise foi comprovar a existência de uma relação não-monotônica entre as variáveis crédito e PIB per capita, e ao mesmo tempo demonstrar a partir de que nível o sistema financeiro causa impactos negativos na taxa de crescimento em cada grupo de países

Neste trabalho foi analisada a influência de um evento sobre o mercado de ações brasileiro a partir das redes, e suas árvores geradoras mínimas, obtidas de medidas de dependência baseadas nas correlações de Pearson, de Spearman e de Kendall. O evento considerado foi a notícia da noite de 17 de maio de 2017 em que o dono da empresa brasileira JBS, Joesley Batista, gravou o então Presidente da República Michel Temer autorizando a compra do silêncio de um Deputado Federal. O dia seguinte a notícia, 18 de maio de 2017, foi definido como o dia do evento. Foram coletados dados de alta frequência de 58 ações do Ibovespa no período de 11 a 25 de maio de 2017. As alterações nas redes das ações do mercado foram analisadas comparando-se o período anterior e posterior ao evento em duas escalas de tempo: (1) Redes diárias: cinco pregões antes do evento, o dia do evento e, cinco pregões depois do evento, com cotações a cada 15 minutos; (2) Agrupadas em antes e depois: agrupando os dados dos 5 dias antes e dos 5 dias depois do evento. O estudo das redes diárias indicou mudança de tendência nas suas propriedades no decorrer do período que contém o evento, com cotações a cada 15 minutos. Isto sugeriu que análise do efeito médio contido nos dados agrupados antes de depois do evento poderiam tornar mais evidente as mudanças na estrutura de rede das ações. As redes antes e depois do evento apresentaram mudanças significativas nas suas métricas que ficaram mais evidenciadas nas árvores geradoras mínimas. As redes geradas pelas correlações de Kendall e Spearman apresentaram um número maior de agrupamentos antes e depois do evento e, após o evento, as árvores geradoras mínimas apresentaram uma redução do número de agrupamentos de ações para todos os tipos de correlação. As distribuições de grau ponderado após o evento indicam uma probabilidade maior de vértices com graus distante da média. As métricas das árvores geradoras mínimas por correlação de Spearman sofreram a maior variação, seguidas pelas de Kendall e Pearson, e também, indicaram que as redes após o evento ficaram mais robustas, ou seja, mais rígidas. A maior robustez das redes após o evento indica maior conectividade do mercado, tornando-o, como um todo, mais suscetível ao impacto de novos acontecimentos. / In this work the influence of an event on the Brazilian stock market was analyzed from networks and its minimum spanning trees obtained from measures of dependence based on the Pearson, Spearman, and Kendall\'s correlations. The event considered was the news in the evening of May 17, 2017 in which the owner of the Brazilian company JBS, Joesley Batista, recorded the Brazilian President Michel Temer authorizing the purchase of the silence of a congress member. The day just after the news, May 18, 2017, was defined as the event day. High-frequency data from 58 Ibovespa shares were collected from 11 to 25 May 2017. Changes in the stocks networks were analyzed comparing the period before and after the event in two time scales: (1) Daily networks: five trade sections before the event, the day of the event and, five trade sections after the event, with price every 15 minutes; (2) Grouped before and after do evento: grouping data from 5 days before and 5 days after event. The study of the daily networks indicated a change of trend in their properties during the period that contains the event, with quotations every 15 minutes. The study of daily networks indicated a change of trend in their properties during the period containing the event. This suggested that analysis of the mean effect of grouped data before and after the event could highlight the changes in the network structure. The networks before and after the event showed significant changes in their metrics, which became more evident from the minimum spanning trees. After the event, the minimum spanning trees for grouped data got a smaller number of clusters in the networks for all kind of correlations. The networks generated by Kendall and Spearman correlations presented a larger number of clusters before and after the event. The weighted degree distributions after the event suggest a power law decay tail for all the correlations considered and indicates a higher probability of vertices with weighted degrees far away from the mean weighted degree. The minimum spanning tree metrics generated by Spearman correlation suffered the greatest variation, followed by those of Kendall and Pearson; and their values indicates that after the event the networks became more robust, that is, more rigid. The increase in the networks robustness after the event indicates a higher market connectivity, making it as a whole, more susceptible to the impact of new events.

Submitted by Maicon Juliano Schmidt (maicons) on 2015-04-18T15:50:59Z No. of bitstreams: 1 Leonardo Berteli Piveta.pdf: 645229 bytes, checksum: 4c3ca61960531dc468ad5d71e7966d32 (MD5) / Made available in DSpace on 2015-04-18T15:50:59Z (GMT). No. of bitstreams: 1 Leonardo Berteli Piveta.pdf: 645229 bytes, checksum: 4c3ca61960531dc468ad5d71e7966d32 (MD5) Previous issue date: 2014-01-31 / Nenhuma / Esta dissertação investiga a existência de integração no mercado de ações e mensura as modificações que a crise do subprime pode ter causado entre as relações de mercados emergentes da América Latina e Centro e Leste Europeu. Para isso, são selecionados onze índices de bolsas de valores destes mercados e utilizados os modelos GARCH e de volatilidade estocástica. Os resultados indicaram a presença de integração financeira entre os países e sugerem ainda que a crise intensificou essas relações. / This dissertation investigates the existence of integration in the stock Exchange market as well as it measures the changes that the subprime crisis may have caused in the relations between the emerging markets of Latin America and Central and Eastern Europe. In order to carry out this study, eleven stock exchange indexes of these markets were selected and the GARCH models and stochastic volatility were used. The results indicated the existence of financial integration between countries; furthermore, they suggested that the crisis has intensified these relationships.

This work is mainly focused on the environment of stock markets. It aims to identify some psychological and sociological factors relating to investors' behaviour which may help to justify occurrence of excessive movements in stock market prices resulting in price "bubbles" and stock market crashes. It emphasizes that the assumptions for the validity of the Efficient Markets Hypothesis based on dominant position of rational investors in stock markets have been empirically undermined by number of experiments and observations. As one of the most vigorous alternative challenging the Efficient Market Hypothesis is now considered the theory of behavioural finance stressing some imperfections of human behaviour which may substantially influence dynamics of stock market prices in both directions.

The Chinese stock market has experienced tremendous growth and development over the past years. It is now the second largest stock market in Asia (after Japan). The increasing numbers of stock investors and the generally upward trend of the local stock indexes transform the Chinese stock market into one of the most actively traded stock market. This study examined the “pricing errors” of the Chinese stock market. The intrinsic values of equities, which can be compared to actual index prices, were estimated using the dividend discount model. Using a database of daily dividend based index prices of Shanghai composite index 180 and Shenzhen composite index 100 from July 2002 to June 2005, our study shows the stocks were undervalued during the sample period, on average, by approximately 0.09% and 1% for Shanghai and Shenzhen composite indexes respectively. The result reveals during July 2002- June 2005, the Chinese stock markets were close to the real value. Another objective of this study is to examine the impact of the economic conditions on the “pricing errors” of Chinese stock market. We find that the Chinese stock markets are much price momentum driven. The relationships of the economic factors and the deviation between the estimated cost of equity (based on CAPM) and the implied cost of equity (based on the actual index prices) showed similar results. We conclude that the Chinese stock markets do not sufficiently reveal local economic conditions.

This paper attempts to assess the impact of price fluctuations in oil resulting from worldwide oil supply shocks on the real returns of the U.S. stock market, specifically the S&P 500, during the period of 1986 to 2011. While much past research has found an inverse relationship to exist between simply oil price increases and stock market returns, not many studies have been conducted that focus on the effects of shifts in oil supply. The model utilized, a variation of that used by Hamilton (2008), determines that changes in oil prices arising from oil supply shocks one quarter prior (t-1) and one year prior (t-4) have an effect on real stock returns. However, an F-test assessing the joint impact of the explanatory variables is unable to reject the null hypothesis that the joint effects of changes in oil prices arising from supply shocks have zero effect on the returns of the stock market.

This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provide negative answers. Phase space reconstruction is achieved by time delay embedding resulting in multiple embedded vectors. The cognitive approach suggested, is inspired by the capability of some chartists to predict the direction of an index by looking at the price time series. Thus, in this work, the calculation of the embedding dimension and the separation, in Takens‘ embedding theorem for phase space reconstruction, is not limited to False Nearest Neighbor, Differential Entropy or other specific method, rather, this work is interested in all embedding dimensions and separations that are regarded as different ways of looking at a time series by different chartists, based on their expectations. Prior to the prediction, the embedded vectors of the phase space are classified with Fuzzy-ART, then, for each class a back propagation Neural Network is trained to predict the last element of each vector, whereas all previous elements of a vector are used as features.

Over the Counter Exchange of India (OTCEI) was established in 1992 mainly to provide a platform for small and medium sized companies to raise money for their capital requirements. It is a well defined dealer market with market makers giving bid and ask quotes. It was established with state-of-the art technology with ringless, scripless trading. In this study, we develop a theoretical model to decompose spread into its three components in a dealer market. This model is further empirically examined by using OTCEI data. We find that Inventory holding cost to be the highest on OTCEI followed by Adverse Information cost and Order Processing cost. The result reflects market microstructure which is peculiar to OTCEI. The methodology developed in this study is basically a generalization of S toll's (1989) methodology. . Roll(1984) shows that in a pure order processing world, spread equals the square root of negative of serial covariances of successive differences of transaction prices. Stoll (1989) relates spread to the covariance of successive difference of transaction prices and that of the quotes. Stoll introduces two parameters, 5, which is a measure of magnitude of price change and JI, the probability of reversal of type of transaction, that is, from Bid to Ask or vice-versa, to model the Bid/Ask price movements from one transaction to the next. Thus Stoll, from this model, establishes a theoretical relationship between serial covariances of successive differences of transaction and quote returns and spread. 5 and n are estimated via regression of serial covariances of transaction and quote, returns on average proportional spread square. With these two parameters, Stoll finally decomposes spread into three components. δ, is the amount of price change between transactions for two reasons- Inventory holding reason and adverse information reason. Stoll explains these price changes due to two reasons with just one parameter, 5. This forms the main motivation of this study. In our study, we let 8 assume two different values, 5i and 82 which attempts to capture the price changes due to the two different causes viz inventory holding and adverse information. It is convenient to think of these two S's being associated with two different states of transactions. However, these states themselves are indeterminate . In other words, the price change could be due to inventory reasons, or due to trading with an informed trader, or due to both. Thus, while Stoll assumes only one 8, in our study, we have two different values of 8. Thus, with three parameters, 81, 82 and n, this study attempts to estimate the relevant parameters and realistically decompose the three components of spread in a dealer market. Just like Stoll, the developed theoretical model also relates serial covariances of transaction price changes and quoted price changes to spread square. However, unlike Stoll, now there are 3 parameters, namely, 5j, 82 and n. As it is impossible to solve three unknowns with just two equations, it becomes necessary to introduce one more equation relating the three parameters to the spread. It is here that we introduce, for the first time, the serial covariance of the second order differences of the transaction price changes, which is related to spread via an equation. Intuitively, we can explain this relationship using Roll's result. Roll(1984) has shown that spread equals square root of the negative serial covariances of transaction price changes in a pure order processing world. Since the second order difference is nothing but the rate of price changes, it also must be related to spread, since the price change themselves are related to it, empirically, we find that spread square significantly affects the serial covariance of second order difference of price changes as well. Besides explaining the price changes with just one 5, Stoll's method of decomposition is not realistic. Though his method of decomposition does yield three components of spread, in reality, it lumps Adverse information cost and Inventory holding cost together. In our study, we make use of the state-of-the art Huang and Stoll's (1997) methodology of decomposition of spread. We first embed the developed theoretical price-movement model into that of Huang and S toll's this yields a functional relationship between 5i and 52 and a and |3 of Huang and Stoll, which directly refers to the adverse information and inventory holding components respectively. Thus, in our study, we realistically decompose the components of spread and OTCEI and empirically too, we find that the components estimated from our methodology does reflect the market microstructure of OTCEI. Apart from developing and empirically testing the theoretical model, we also see if it fits the observed data on OTCEI. We find that the theoretical model does not exactly conform to the observed data in OTCEI, necessitating some empirical fine-tuning. We build an empirical model which is again used to get the three components of spread. We also estimate components of spread in OTCEI using Stoll's and Huang and Stoll's methodology and we compare them with the estimates obtained using our methodology. We find that Stoll's methodology overstates the Adverse information component of spread and understates the inventory holding component of spread and Huang and Stoll's methodology and Our methodology and model yields estimates of components of spread which is more in tune with the market micros tructure of OTCEI. The estimates obtained from empirical model too conforms to the market microstructure of OTCEI.

Financial Derivatives are one of the most popular and emerging innovations in the field of financial engineering. Since their inception, there has been a phenomenal growth in the volumes of derivatives traded all over the world. Financial markets are known to be extremely volatile and derivatives provide a way of eliminating or reducing the risks involved in these markets. Since these instruments derive their value from some underlying asset, trading in these instruments is bound to affect the underlying assets. Thus it becomes important to examine what these effects are and whether they have been favourable or detrimental to the underlying stock markets specially when there has been an explosive growth of these financial derivatives all over the world. This issue gains more importance in the case of emerging markets like India as they try to be more competitive and efficient as the developed Western markets. This thesis mainly deals with looking at this impact on the Indian stock markets. The Indian markets still being very new in this area, not many studies have been reported here related to this issue. The main focus of this thesis is to provide some more evidence on the impact of one kind of derivative instrument, namely options on different characteristics of underlying stocks in the Indian stock market. The thesis has the following objectives: • To examine the impact of option introduction on the price of underlying stocks in National Stock Exchange (NSE). • To examine the impact of option introduction on the volatility of underlying stocks in NSE • To examine the impact of option introduction on liquidity of underlying stocks in NSE NSE introduced derivatives beginning with index futures on June 12, 2000, followed by index options on June 4, 2001, options on individual securities on July 2, 2001 and finally futures on individual securities on November 9, 2001. Due to the temporal proximity of the introduction of index options and individual options, there exists a possibility of an interaction of these two effects. This problem is solved by a judiciously chosen sampling design. In particular, three groups of stocks are considered. The first group consists of stocks on which options were first introduced on 2nd July 2001 and thus would exhibit a combined effect of the two events if any. The second group consists of stocks on which options were introduced much later and therefore would show effects of individual option introduction if any. The third group comprises of nonoptioned stocks whose returns are considered around the date of index option introduction and thus would show effects of index option alone if any. To separate the two effects an ANOVA/ Logistic Regression model is used. An objective selection of the event and estimation windows is done using a Bayesian Change Point Analysis. The first part of the thesis looks at the effect of option introduction on the price of underlying stocks. A standard event study methodology as has been used in the literature is employed for this purpose. The study does not find any significant effect of option introduction on the prices. The second part of the thesis deals with the effect on volatility. Volatility is measured as the risk of a stock and as is done in the literature, three kinds of risk are looked at: total risk, systematic risk and the unsystematic risk. In case of the total risk, an F-test and an Ansari Bradley test is used to check for changes in the variance and scale parameters of market-adjusted continuously compounded returns of the stocks before and after option introduction. The results of these tests are recorded as a categorical variable taking on the value 0 for no change and 1 for a change and a Binomial Logistic Regression is used to separate the effects of the two events. Furthermore, after recording the results of the above mentioned tests as a categorical variable with three categories (0, 1, -1), a Multinomial Logistic Regression is also used in order to estimate the direction of the change (increase, decrease or no change). The ratios of after to before total risks are also analyzed using an ANOVA model. The systematic risk is measured using three kinds of betas – OLS betas, Scholes-Williams betas and Fowler-Rorke betas. The differences in the before and after betas of every stock are modelled using an ANOVA model in order to separate the two effects as well as the interaction effect. The unsystematic risk is estimated by the conditional variances and the unconditional variances of ARMA and ARMA-GARCH models fitted to market model excess returns. The ANOVA model is used here as well. In addition to this, the before and after ARCH and GARCH coefficients of GARCH (1, 1) models fitted to the excess returns are also compared using the ANOVA model. The results indicate that individual options are leading to a decline in total risk however index options are causing an increase in total risk. The interaction effect is significant in this case thereby causing an increase in total risk in the Group I stocks. The OLS betas indicate that individual option introduction seems to have increased the systematic risk. The Scholes-Williams betas indicate that index option introduction seems to have increased the systematic risk. The Fowler Rorke betas on the other hand, do not show any significant impact of individual option or index option introduction. For all the three betas index options introduction seems to have no effect on the systematic risk. Though the interaction effect seems to be significant in all the three cases, it however does not significantly affect the systematic risk in Group I stocks. As regards the unsystematic risk, both the conditional and unconditional variances of ARMA models show a significant reduction for individual option introduction but index options do not have any significant impact on either one of these measures. In case of unconditional variances of ARMA-GARCH models, none of the effects come out as significant. While comparing the news and persistence coefficients of GARCH (1, 1) models, the news coefficients indicate that the due to index option introduction, stocks are becoming more efficient in terms of absorbing the news more rapidly. No significant effect of either event is found on the persistence coefficients. The last part of the thesis deals with the liquidity issue. Liquidity has been measured using two measures – relative volume (based on daily data) and implicit bid-ask spread given by Roll (1984) (calculated from intra-day data). In case of the liquidity measures, the Logistic Regression models are used i.e. a categorical variable with two or three categories obtained from the results of a Wilcoxon Rank Sum test for comparing the median volume and spread before and after option introduction, is used. It is found that for the relative volume, individual option introduction has led to a favourable effect in terms of increasing the volume post introduction of options; however index options seem to have had a negative effect. As for the spread, index options seem to have had a stabilizing influence on the underlying stocks than the individual options.

[pt] O presente trabalho objetiva identificar de que forma os fundos de pensão podem se tornar instrumentos financeiros essenciais ao financiamento da economia brasileira, levando-se em consideração o acentuado desenvolvimento e internacionalização dos mercados mundiais. Para isso, faz- se necessário avaliar seu desempenho nos mercados de capitais, bem como de que forma podem se tornar eficientes, através da otimização de sua estratégia de risco. Nesse sentido, fez-se uso de diversos modelos conhecidos na teoria de finanças, como o Modelo de Markowitz, o modelo do Índice Único de Sharpe, modelo CAPM, e as técnicas para a determinação de fronteiras eficientes de Elton e Gruber, bem como das diversas medidas de desempenho de nvestimentos existentes como: taxa de retorno ponderado pelo tempo, desvio padrão, coeficiente beta, Índice de Sharpe, Índice de Modigliani,Índice de Jensen, Índice de Treynor, Apprasial Ratio e Índice de Modigliani, para que se pudesse analisar e comparar o resultado dos 20 maiores fundos de pensão existentes no Brasil. / [en] The present objective work intend to identify the forms that the pension funds can become financial instruments essential to financing the Brazilian economy, taking in consideration the accented development and internationalization of the world-wide markets. For this one becomes necessary to evaluate its performance in the stock markets, as well as of that it forms can become efficient, through the optimization of its risk strategy. In this direction, use of diverse models known in the theory of finances became, as the Markowitz s Model, the Sharpe s Single Index Model, the Capital Asset Pricing Model - CAPM, and the techniques for the determination the efficient borders of Elton and Gruber, as well as of the diverse measures of performance of existing investments as: Return tax, standard deviation, beta coefficient, Sharpe s Index, Modigliani s Index, Jensen s Index, Treynor s Index, Appraisal Ratio and Modigliani s Index, so that if it could analyze and compare the result of the 20 existing greater pension funds in Brazil.