Este trabalho possui um duplo objetivo: i) estudar os fatos estilizados do livro de ofertas dos papéis negociados na Bolsa de Valores de São Paulo (BOVESPA), assim como dos retornos engendrados pela dinâmica do livro de ofertas e ii) desenvolver um modelo de livro de ofertas baseado em agentes com o propósito de reproduzir tais fatos estilizados. Trabalhou-se com dados de junho/2006 a janeiro/2009 de uma amostra formada pelos vinte papéis mais negociados da BOVESPA. Os resultados empíricos corroboraram alguns fatos estilizados observados no estudo de papéis de outros países, mas refutaram outros. O modelo baseado em agentes conseguiu emular satisfatoriamente os fatos estilizados relacionados aos retornos, mas em se tratando da reprodução dos fatos estilizados do livro de ofertas o modelo foi menos eficaz. / This study has two aims: i) analyze the stylized facts of the order book of stocks traded in the São Paulo Stock Exchange (BOVESPA), as well as of the returns engendered by the order book dynamics and ii) develop an order book agent-based model able to reproduce such stylized facts. It was used data from June 2006 to January 2009 regarding a sample composed by the twenty most traded stocks in BOVESPA. The empirical results corroborated some stylized facts observed in stocks of other countries, but refuted others. The agent-based model successfully emulated the stylized facts concerning the returns; however, the model was less efficient in reproducing the stylized facts of the order book.

Este trabalho possui um duplo objetivo: i) estudar os fatos estilizados do livro de ofertas dos papéis negociados na Bolsa de Valores de São Paulo (BOVESPA), assim como dos retornos engendrados pela dinâmica do livro de ofertas e ii) desenvolver um modelo de livro de ofertas baseado em agentes com o propósito de reproduzir tais fatos estilizados. Trabalhou-se com dados de junho/2006 a janeiro/2009 de uma amostra formada pelos vinte papéis mais negociados da BOVESPA. Os resultados empíricos corroboraram alguns fatos estilizados observados no estudo de papéis de outros países, mas refutaram outros. O modelo baseado em agentes conseguiu emular satisfatoriamente os fatos estilizados relacionados aos retornos, mas em se tratando da reprodução dos fatos estilizados do livro de ofertas o modelo foi menos eficaz. / This study has two aims: i) analyze the stylized facts of the order book of stocks traded in the São Paulo Stock Exchange (BOVESPA), as well as of the returns engendered by the order book dynamics and ii) develop an order book agent-based model able to reproduce such stylized facts. It was used data from June 2006 to January 2009 regarding a sample composed by the twenty most traded stocks in BOVESPA. The empirical results corroborated some stylized facts observed in stocks of other countries, but refuted others. The agent-based model successfully emulated the stylized facts concerning the returns; however, the model was less efficient in reproducing the stylized facts of the order book.

Nesta dissertação é explorado o comportamento emergente de uma população heterogênea de jogadores negociando segundo o jogo do ultimato: dois jogadores recebem uma oferta; um deles (o proponente) propõe a sua divisão, enquanto o outro jogador (o aceitador) pode aceitar ou rejeitar a proposta. A rejeição é prejudicial a ambos jogadores, pois nenhum deles recebe sua parcela dos possíveis ganhos. Neste contexto, o ganho e seus momentos são calculados a partir de métodos analíticos simples e várias simulações computacionais corroboram os resultados obtidos. Também são analisadas as flutuações estatísticas da distribuição do ganho. Além disso, é apresentada uma abordagem simples evolucionária que considera mudanças em estratégias baseadas em ganhos anteriores. Para este caso, é demonstrado que o tempo médio de permanência (idade) de uma estratégia de uma população de "justos" convergepara um valor constante enquanto t se aproxima do ∞ e o cutoff médio decai segundouma lei de potência em tempos altos, após uma queda inicial. Também foram observadas transições entre comportamentos de alto e baixo ganho. Adicionalmente foi estudadauma versão espacial desse modelo. Para tanto são consideradosjogadores interagindo com seus primeiros vizinhos em reticulados 2D de acordo com duas dinâmicas estocáticas: (1) morte e nascimento com amostragem seletiva (MNAS), (2) Gibbs sampling sobre a vizinhança (GS). Estes resultados trazem importantes considerações sobre o projeto de simulaçõesno contexto da teoria dos jogos evolucionários, em particular na simulação dos aspectos relevantes quando modelando grandes populações. / Weexplore the emergent behavior of a heterogeneous population of players negotiating via an ultimatum game: two players are offered a gift; one of them (the proposer) suggestshow to divide the offer while the other player (the responder) can either agree or reject the deal. Rejection is detrimental to both players as it results in no eamings. In this context, the payoff and its moments are calculated from simple analytical methods and several computer simulations corroborate the obtained results. Wealso analyze statistical fluctuationson payoff distribution. In addition,we present a simple evolutionaryapproach that considers changes in strategies based on previous eamings. For this case, we show that average permanence time (age) in a strategy of a fair population converges to a constant value when t approaches ∞ and the cutoff average decays as a power law for large times after a initial deterministic slip. We have also observed transitions between highlow payoffbehaviors. Additionallywe studied a spatial version ofthis model. For this we consider players interacting with their nearest neighbors in 2D lattices according to two different stochastic dynamics: (1) Death and birth with selective sampling (MNAS), (2) Gibbs sampling on neighborhood (GS) Webelieve that these results can bring important considerationsto the design of simulations in the context ofthe evolutionary game theory, in particular in the simulation of relevant features when modeling large populations.

The understanding of the emergent behaviour of complex systems is probably one of the most intriguing challenges in modern theoretical physics. In the present Thesis we use novel data analysis techniques and numerical simulations in order to shed some light on the fundamental mechanisms involved in their dynamics. We divide the main core of the research into three parts, each of which address a specific, and formally well defined, issue. In the first part, we study the processes of self - organization and herding in the evolution of the stock market. The data analysis, carried out over the fluctuations of several international indices, shows an avalanche - like dynamics characterized by power laws and indicative of a critical state. Further evidence of criticality relates to the behaviour of the price index itself. In this case we observe a power law decline with superimposed embedded log - periodic oscillations which are possibly due to an intrinsic discrete scale invariance. A stochastic cellular automata, instead, is used to mimic an open stock market and reproduce the herding behaviour responsible for the large fluctuations observed in the price. The results underline the importance of the largest clusters of traders which, alone, can induce a large displacement between demand and supply and lead to a crash. The second part of the Thesis focuses on the role played by the complex network of interactions that is created among the elementary parts of the system itself. We consider, in particular, the influence of the so - called " scale - free " networks, where the distribution of connectivity follows a power law, on the antiferromagnetic Ising model and on a model of stochastic opinion formation. Novel features, not encountered on regular lattices, have been pointed out. In the former case a spin glass transition at low temperatures is present while, in the latter, the turbulent - like behaviour emerging from the model is found to be particularly robust against the indecision of the agents. The last part is left for a numerical investigation of an extremal dynamical model for evolution / extinction of species. We demonstrate how the mutual cooperation between them comes to play a fundamental role in the survival probability : a healthy environment can support even less fitted species. / Thesis (Ph.D.)--School of Chemistry and Physics, 2006.

This paper offers empirical evidence on the power of Sornette et al's [2001] model of bubbles and crashes regarding the German stock market between 1960 and 2009. We identify relevant time periods and describe them with the function given by Sornette et al's model. Our results show some evidence in predicting crashes with the understanding of logarithmic periodic structures that are hidden in the stock price trajectories. It was shown that for the DAX most of the relevant parameters determining the shape of the logarithmic periodic structures are lying in the expected interval researched by Sornette et al. Further more the paper implicitly shows that the point of time of former crashes can be predicted with the presented formula. We conclude that the concept of financial time series conceived as purely random objects should be generalised as to admit complexity.

Purpose The main purpose of this paper is to investigate overconfidence and over-optimism in the market. This leads the reader to the question, are the analysts “right” concerning their forecasts? The reader will also get to understand various and sometimes forgotten factors that affect we human beings in our decision making when it comes to investing and analysing which is also known as the behavioural finance theory. Conclusion According to the results from my tests it seems that analysts of the S&P500 are exaggerated by the problem of overconfidence and the over-optimistic biases. The analysis part of this study is confirming the discussed theory of anchoring and herding. Analysts tend to “follow the stream”, by evaluate the standard deviations between forecasts and the realized outcome, as well as the indexed analysts’ consensus estimations for twenty-four months of EPS.

The understanding of the emergent behaviour of complex systems is probably one of the most intriguing challenges in modern theoretical physics. In the present Thesis we use novel data analysis techniques and numerical simulations in order to shed some light on the fundamental mechanisms involved in their dynamics. We divide the main core of the research into three parts, each of which address a specific, and formally well defined, issue. In the first part, we study the processes of self - organization and herding in the evolution of the stock market. The data analysis, carried out over the fluctuations of several international indices, shows an avalanche - like dynamics characterized by power laws and indicative of a critical state. Further evidence of criticality relates to the behaviour of the price index itself. In this case we observe a power law decline with superimposed embedded log - periodic oscillations which are possibly due to an intrinsic discrete scale invariance. A stochastic cellular automata, instead, is used to mimic an open stock market and reproduce the herding behaviour responsible for the large fluctuations observed in the price. The results underline the importance of the largest clusters of traders which, alone, can induce a large displacement between demand and supply and lead to a crash. The second part of the Thesis focuses on the role played by the complex network of interactions that is created among the elementary parts of the system itself. We consider, in particular, the influence of the so - called " scale - free " networks, where the distribution of connectivity follows a power law, on the antiferromagnetic Ising model and on a model of stochastic opinion formation. Novel features, not encountered on regular lattices, have been pointed out. In the former case a spin glass transition at low temperatures is present while, in the latter, the turbulent - like behaviour emerging from the model is found to be particularly robust against the indecision of the agents. The last part is left for a numerical investigation of an extremal dynamical model for evolution / extinction of species. We demonstrate how the mutual cooperation between them comes to play a fundamental role in the survival probability : a healthy environment can support even less fitted species. / Thesis (Ph.D.)--School of Chemistry and Physics, 2006.

<p>Purpose</p><p>The main purpose of this paper is to investigate overconfidence and over-optimism in the market. This leads the reader to the question, are the analysts “right” concerning their forecasts? The reader will also get to understand various and sometimes forgotten factors that affect we human beings in our decision making when it comes to investing and analysing which is also known as the behavioural finance theory.</p><p>Conclusion</p><p>According to the results from my tests it seems that analysts of the S&P500 are exaggerated by the problem of overconfidence and the over-optimistic biases. The analysis part of this study is confirming the discussed theory of anchoring and herding. Analysts tend to “follow the stream”, by evaluate the standard deviations between forecasts and the realized outcome, as well as the indexed analysts’ consensus estimations for twenty-four months of EPS.</p>

Nesta dissertação é explorado o comportamento emergente de uma população heterogênea de jogadores negociando segundo o jogo do ultimato: dois jogadores recebem uma oferta; um deles (o proponente) propõe a sua divisão, enquanto o outro jogador (o aceitador) pode aceitar ou rejeitar a proposta. A rejeição é prejudicial a ambos jogadores, pois nenhum deles recebe sua parcela dos possíveis ganhos. Neste contexto, o ganho e seus momentos são calculados a partir de métodos analíticos simples e várias simulações computacionais corroboram os resultados obtidos. Também são analisadas as flutuações estatísticas da distribuição do ganho. Além disso, é apresentada uma abordagem simples evolucionária que considera mudanças em estratégias baseadas em ganhos anteriores. Para este caso, é demonstrado que o tempo médio de permanência (idade) de uma estratégia de uma população de "justos" convergepara um valor constante enquanto t se aproxima do ∞ e o cutoff médio decai segundouma lei de potência em tempos altos, após uma queda inicial. Também foram observadas transições entre comportamentos de alto e baixo ganho. Adicionalmente foi estudadauma versão espacial desse modelo. Para tanto são consideradosjogadores interagindo com seus primeiros vizinhos em reticulados 2D de acordo com duas dinâmicas estocáticas: (1) morte e nascimento com amostragem seletiva (MNAS), (2) Gibbs sampling sobre a vizinhança (GS). Estes resultados trazem importantes considerações sobre o projeto de simulaçõesno contexto da teoria dos jogos evolucionários, em particular na simulação dos aspectos relevantes quando modelando grandes populações. / Weexplore the emergent behavior of a heterogeneous population of players negotiating via an ultimatum game: two players are offered a gift; one of them (the proposer) suggestshow to divide the offer while the other player (the responder) can either agree or reject the deal. Rejection is detrimental to both players as it results in no eamings. In this context, the payoff and its moments are calculated from simple analytical methods and several computer simulations corroborate the obtained results. Wealso analyze statistical fluctuationson payoff distribution. In addition,we present a simple evolutionaryapproach that considers changes in strategies based on previous eamings. For this case, we show that average permanence time (age) in a strategy of a fair population converges to a constant value when t approaches ∞ and the cutoff average decays as a power law for large times after a initial deterministic slip. We have also observed transitions between highlow payoffbehaviors. Additionallywe studied a spatial version ofthis model. For this we consider players interacting with their nearest neighbors in 2D lattices according to two different stochastic dynamics: (1) Death and birth with selective sampling (MNAS), (2) Gibbs sampling on neighborhood (GS) Webelieve that these results can bring important considerationsto the design of simulations in the context ofthe evolutionary game theory, in particular in the simulation of relevant features when modeling large populations.

Submitted by Jamil Civitarese (jamil@rankings.watch) on 2015-09-08T17:16:54Z No. of bitstreams: 1 ebape_v2_completa.pdf: 1545221 bytes, checksum: 26ed0880a075cf3930258d1d3b4b769f (MD5) / Approved for entry into archive by ÁUREA CORRÊA DA FONSECA CORRÊA DA FONSECA (aurea.fonseca@fgv.br) on 2016-01-25T14:30:06Z (GMT) No. of bitstreams: 1 ebape_v2_completa.pdf: 1545221 bytes, checksum: 26ed0880a075cf3930258d1d3b4b769f (MD5) / Approved for entry into archive by Maria Almeida (maria.socorro@fgv.br) on 2016-01-26T19:19:59Z (GMT) No. of bitstreams: 1 ebape_v2_completa.pdf: 1545221 bytes, checksum: 26ed0880a075cf3930258d1d3b4b769f (MD5) / Made available in DSpace on 2016-01-26T19:20:11Z (GMT). No. of bitstreams: 1 ebape_v2_completa.pdf: 1545221 bytes, checksum: 26ed0880a075cf3930258d1d3b4b769f (MD5) Previous issue date: 2015-08-08 / This dissertation presents two papers on how to deal with simple systemic risk measures to assess portfolio risk characteristics. The first paper deals with the Granger-causation of systemic risk indicators based in correlation matrices in stock returns. Special focus is devoted to the Eigenvalue Entropy as some previous literature indicated strong re- sults, but not considering different macroeconomic scenarios; the Index Cohesion Force and the Absorption Ratio are also considered. Considering the S&P500, there is not ev- idence of Granger-causation from Eigenvalue Entropies and the Index Cohesion Force. The Absorption Ratio Granger-caused both the S&P500 and the VIX index, being the only simple measure that passed this test. The second paper develops this measure to capture the regimes underlying the American stock market. New indicators are built using filtering and random matrix theory. The returns of the S&P500 is modelled as a mixture of normal distributions. The activation of each normal distribution is governed by a Markov chain with the transition probabilities being a function of the indicators. The model shows that using a Herfindahl-Hirschman Index of the normalized eigenval- ues exhibits best fit to the returns from 1998-2013.