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.

Forestry activities play a crucial role in climate change mitigation. To make carbon credits generated from such activities a tradable commodity, it is important to analyze the price dynamics of carbon markets. This dissertation contains three essays that examine various issues confronting world’s carbon markets. The first essay investigates cointegration of carbon markets using Johansen maximum likelihood procedure. All carbon markets of the world are not integrated. North American carbon markets show integration and so do the CDM markets. For future, the possibilities of arbitrage across world’s markets are expected to be limited, and carbon trading in these markets will be globally inefficient. There is a strong need of a global agreement that allows carbon trade to prevent climate change at the least cost options. The second essay evaluates various econometric models for predicting price volatility in the carbon markets. Voluntary carbon market of Chicago is relatively more volatile; and like other financial markets, its volatility is forecasted best by a complex non-linear GARCH model. The compliance market of Europe, on the other hand, is less volatile and its volatility is forecasted best by simple econometric models like Historical Averages and GARCH and hence is different from other markets. Findings could be useful for investment decision making, and for making choice between various policy instruments. The last essay focuses on agent based models that incorporate interactions of heterogeneous entities. Artificial carbon markets obtained from such models have statistical properties - lack of autocorrelations, volatility clustering, heavy tails, conditional heavy tails, and non-Gaussianity; which are similar to the actual carbon markets. These models possess considerably higher forecasting capabilities than the traditional econometric models. Forecast accuracy is further improved considerably through experimentation, when agent characteristics like wealth distribution, proportion of allowances and number of agents are set close to the real market situations.

Forestry activities play a crucial role in climate change mitigation. To make carbon credits generated from such activities a tradable commodity, it is important to analyze the price dynamics of carbon markets. This dissertation contains three essays that examine various issues confronting world’s carbon markets. The first essay investigates cointegration of carbon markets using Johansen maximum likelihood procedure. All carbon markets of the world are not integrated. North American carbon markets show integration and so do the CDM markets. For future, the possibilities of arbitrage across world’s markets are expected to be limited, and carbon trading in these markets will be globally inefficient. There is a strong need of a global agreement that allows carbon trade to prevent climate change at the least cost options. The second essay evaluates various econometric models for predicting price volatility in the carbon markets. Voluntary carbon market of Chicago is relatively more volatile; and like other financial markets, its volatility is forecasted best by a complex non-linear GARCH model. The compliance market of Europe, on the other hand, is less volatile and its volatility is forecasted best by simple econometric models like Historical Averages and GARCH and hence is different from other markets. Findings could be useful for investment decision making, and for making choice between various policy instruments. The last essay focuses on agent based models that incorporate interactions of heterogeneous entities. Artificial carbon markets obtained from such models have statistical properties - lack of autocorrelations, volatility clustering, heavy tails, conditional heavy tails, and non-Gaussianity; which are similar to the actual carbon markets. These models possess considerably higher forecasting capabilities than the traditional econometric models. Forecast accuracy is further improved considerably through experimentation, when agent characteristics like wealth distribution, proportion of allowances and number of agents are set close to the real market situations.

<p>In recent years, government aid agencies and international organizations have increased their financial commitments to controlling and eliminating malaria from the planet. This renewed emphasis on elimination is reminiscent of a previous worldwide campaign to eradicate malaria in the 1960s, a campaign which ultimately failed. To avoid a repeat of the past, mechanisms must be developed to sustain effective malaria control programs.</p><p>A number of sociobehavioral, economic, and biophysical challenges exist for sustainable malaria control, particularly in high-burden areas such as sub-Saharan Africa. Sociobehavioral challenges include maintaining high long-term levels of support for and participation in malaria control programs, at all levels of society. Reasons for the failure of the previous eradication campaign included a decline in donor, governmental, community, and household-level support for control programs, as malaria prevalence ebbed due in part to early successes of these programs.</p><p>Biophysical challenges for the sustainability of national malaria control programs (NMCPs) encompass evolutionary challenges in controlling the protozoan parasite and the mosquito vector, as well as volatile transmission dynamics which can lead to epidemics. Evolutionary challenges are particularly daunting due to the rapid generational turnover of both the parasites and the vectors: The reliance on a handful of insecticides and antimalarial drugs in NMCPs has placed significant selection pressures on vectors and parasites respectively, leading to a high prevalence of genetic mutations conferring resistance to these biocides.</p><p>The renewed global financing of malaria control makes research into how to effectively surmount these challenges arguably more salient now than ever. Economics has proven useful for addressing the sociobehavioral and biophysical challenges for malaria control. A necessary next step is the careful, detailed, and timely integration of economics with the natural sciences to maximize and sustain the impact of this financing.</p><p>In this dissertation, I focus on 4 of the challenges identified above: In the first chapter, I use optimal control and dynamic programming techniques to focus on the problem of insecticide resistance in malaria control, and to understand how different models of mosquito evolution can affect our policy prescriptions for dealing with the problem of insecticide resistance. I identify specific details of the biological model--the mechanisms for so-called "fitness costs" in insecticide-resistant mosquitoes--that affect the qualitative properties of the optimal control path. These qualitative differences carry over to large impacts on the economic costs of a given control plan.</p><p>In the 2nd chapter, I consider the interaction of parasite resistance to drugs and mosquito resistance to insecticides, and analyze cost-effective malaria control portfolios that balance these 2 dynamics. I construct a mathematical model of malaria transmission and evolutionary dynamics, and calibrate the model to baseline data from a rural Tanzanian district. Four interventions are jointly considered in the model: Insecticide-spraying, insecticide-treated net distribution, and the distribution of 2 antimalarial drugs--sulfadoxine pyramethamine (SP) and artemisinin-based combination therapies (ACTs). Strategies which coordinate vector controls and treatment protocols should provide significant gains, in part due to the issues of insecticide and drug resistance. In particular, conventional vector control and ACT use should be highly complementary, economically and in terms of disease reductions. The ongoing debate concerning the cost-effectiveness of ACTs should thus consider prevailing (and future) levels of conventional vector control methods, such as ITN and IRS: If the cost-effectiveness of widespread ACT distribution is called into question in a given locale, scaling up IRS and/or ITNs probably tilts the scale in favor of distributing ACTs. </p><p>In the 3rd chapter, I analyze results from a survey of northern Ugandan households I oversaw in November 2009. The aim of this survey was to assess respondents' perceptions about malaria risks, and mass indoor residual spraying (IRS) of insecticides that had been done there by government-sponsored health workers. Using stated preference methods--specifically, a discrete choice experiment (DCE)--I evaluate: (a) the elasticity of household participation levels in IRS programs with respect to malaria risk, and (b) households' perceived value of programs aimed at reducing malaria risk, such as IRS. Econometric results imply that the average respondent in the survey would be willing to forego a $10 increase in her assets for a permanent 1% reduction in malaria risk. Participation in previous IRS significantly increased the stated willingness to participate in future IRS programs. However, I also find that at least 20% of households in the region perceive significant transactions costs from IRS. One implication of this finding is that compensation for these transactions costs may be necessary to correct theorized public good aspects of malaria prevention via vector control.</p><p>In the 4th chapter, I further study these public goods aspects. To do so, I estimate a welfare-maximizing system of cash incentives. Using the econometric models estimated in the 3rd chapter, in conjunction with a modified version of the malaria transmission models developed and utilized in the first 2 chapters, I calculate village-specific incentives aimed at correcting under-provision of a public good--namely, malaria prevention. This under-provision arises from incentives for individual malaria prevention behavior--in this case the decision whether or not to participate in a given IRS round. The magnitude of this inefficiency is determined by the epidemiological model, which dictates the extent to which households' prevention decisions have spillover effects on neighbors. </p><p>I therefore compute the efficient incentives in a number of epidemiological contexts. I find that non-negligible monetary incentives for participating in IRS programs are warranted in situations where policymakers are confident that IRS can effectively reduce the incidence of malaria cases, and not just exposure rates. In these cases, I conclude that the use of economic incentives could reduce the incidence of malaria episodes by 5%--10%. Depending on the costs of implementing a system of incentives for IRS participation, such a system could provide an additional tool in the arsenal of malaria controls.</p> / Dissertation

This paper studies the dynamics of an asset pricing model based on simple deterministic agents. Traders are heterogeneous with respect to their time horizon, prediction function and trade interval. Concerning the trade interval we distinguish between intraday traders and end-of-day traders. Intraday traders update their portfolio every period, whereas end-of-day traders adjust their positions only at the closing price of each trading day. The parameter values of the model were partially determined by an adapted Markov chain Monte Carlo sampling method. We analyse the properties of the time series and find that they exhibit low autocorrelation of the returns, volatility clustering and fat tails. Particularly heterogeneous trade intervals seem to be an important factor for generating time series showing "stylized facts". (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

A generalização de modelos de crescimento por meio de um parâmetro de controle foi primeiramente proposta por Richards, em 1959. Em nosso trabalho, propomos uma forma alternativa de generalização obtendo uma interpretação emp rica e outra microscopica do parâmetro de controle. Mais especificamente, quando consideramos a proliferacão de c elulas, o parâmetro est a relacionado ao alcance da interação e a dimensão fractal da estrutura celular. Obtemos a solucão anal ítica para esta equação diferencial. Mostramos que, atrav és da escolha apropriada da escala conseguimos o colapso de dados representando a independência em relacão aos parâmetros e as condições iniciais. Al ém disso, ao considerarmos a taxa de esforco como a retirada de indiví duos de uma população, podemos associ á-la ao tratamento visando extinguir uma populacãoo de c élulas cancerosas. Em modelos epidemiol ogicos, propomos modelar a dinâmica de transmissão da dengue utilizando equacões diferenciais ordin árias. Em nosso modelo, levamos em conta tanto a dinâmica do hospedeiro quanto a do vetor, assim temos o controle da dinâmica de ambas as populações. Inclu ímos tamb ém no modelo o efeito \"enhancing\" com intuito de verificar sua influência na dinâmica de disseminacão da doença. O efeito \"enhancing\" é considerado uma das principais hipóteses para explicar a dengue hemorr ágica que pode levar a morte. Fizemos o estudo de um modelo epidemiol ógico da dengue com o objetivo de revelar quais são os fatores que levam a disseminação desse caso mais severo da doenca e, possivelmente, sugerir polí ticas p úblicas de sa úde para evit á-lo. Implementamos tamb ém um modelo de transmissão da tuberculose fazendo uso da modelagem computacional baseada em agentes, que oferece a possibilidade de representar explicitamente heterogeneidades em nível individual. / The generalization of growth models by means of a control parameter was first proposed by Richards in 1959. In our work, we propose an alternative way to obtainin an empirical and microscopic interpretation of control parameter. More specically, when considering the proliferation of cells, the parameter is related to the range of interaction and the fractal dimension of the cell structure. We obtain the analytical solution for this dierential equation. We show that, by appropriate choice of scale we have data collapse, representing the independence on parameters and initial conditions. Furthermore, when considering the e ffort as rate the removal of individuals from a population, we can associate it with the treatment to extinguish cancer cells population. In epidemiological models, we propose to model the dynamics of dengue transmission using ordinary dierential equations. In our model, we take into account both the dynamics of the host and the vector, so we have control of the dynamics of both populations. We also included in the model the effect of enhancing in order to verify their inuence on the dynamics of disease spread. The effect of enhancing is considered one of the main hypotheses to explain the hemorrhagic fever that can lead to death. We study a model of epidemiology of dengue in order to reveal what are the factors that lead to the dissemination of this more severe case of the disease and, possibly suggesting public health policies to prevent it. We also implemented a model of tuberculosis transmission making use of agent-based computational modeling, which o ffers the possibility to explicitly represent heterogeneity at the individual level. This approach allows us to deal with each individual in particular, unlike the model of dierential equations, in which all individuals are in the same compartment interact in a similar way as in a mean field interaction.

O objetivo da presente pesquisa foi verificar se a flexibilidade característica dos modelos baseados em agentes (Agent Based Models ABM) representa adequadamente mercados em concorrência imperfeita, identificando novos elementos referentes ao comportamento e adaptabilidade dos agentes econômicos não identificados em pesquisas anteriores. Para tal, foram propostos dois modelos distintos aplicados aos mercados de passagens aéreas e sucroalcoleiro. A complexidade dos mercados analisados deve-se à forma não trivial com que é descrita a estrutura de disposição dos agentes e a maneira como estes se relacionam e tomam suas decisões, tornando infactível a aplicação de soluções analíticas. Tal fato justifica o emprego dos modelos baseados em agentes devido a sua alta flexibilidade para adequação ao ambiente simulado. O fator comum aos dois modelos propostos foi a incorporação de incertezas e expectativas nos cenários avaliados pelos agentes para sua tomada de decisão. Ao considerar as incertezas dos cenários prospectivos, os modelos simulados mostraram-se aderentes à natureza probabilística encontrada nos mercados reais, permitindo obter resultados com tendências semelhantes aos mercados estudados. A complexidade dos mercados em concorrência imperfeita analisados foi, dessa maneira, bem representada pelos modelos sugeridos. O processo adaptativo dos agentes às mudanças de mercado mostrou que os modelos baseados em agentes são ferramentas adequadas para o estudo dos mesmos e permitem captar peculiaridades dos mercados não incorporadas em outras pesquisas, revelando, inclusive características não aparentes e não incluídas em estudos anteriores. / The objective of this research was to investigate if imperfect competitive markets are well represented by the flexibility of the Agent Based Models (ABM). Therefore, it is expected that the ABM allows identifying agents new behaviour element, as well as incorporating agents adaptability processes not previously described by the other researches. Two distinct models were developed. The first one refers to the airfare prices, while the second one aims to simulate the ethanol market. The high complexity of the studied markets due to their non-trivial structure regarding the way the agents relate to each other and take their decisions justifies the employment of ABM, since ABMs are remarkably characterized by their flexibility. The common factor among the models is the incorporation of uncertainties and expectations in the models when the economic scenarios are considered by the agents for decision making. The results showed that the simulated models reached the same tendency of prices and production observed by the real data, respectively to the airfare and ethanol models. The adaptive process of the agents to the market conditions showed that ABMs are adequate tools for the study of imperfect markets, since for both models non-apparent characteristics have emerged.

The diploma thesis describes design and creation of agent-based model of cooperative games and its subsequent analysis. The created model combines assumptions of game the-ory with other findings; it examines the dynamics of coalition formation and the influence of external and internal factors on this formation. The first theoretical part introduces the game theory and clarifies basic principles and con-cepts of N - player cooperative games. It evaluates the benefits and disadvantages of solu-tions introduced by this theory. The thesis further deals with multi-agent systems focused on agent-based models as an analytical and computational method for analyzing complex systems. There are also explained basic principles of agent-based modeling, including ap-proaches of their creation. Furthermore, there are presented distinctions between different types of agents, environments and models. The second practical part specifies assumptions and principles that are essential for the created multi-agent model. The diploma thesis describes the development of agent-based model of cooperative games by itself, including its characteristics and behavior. Final analysis of the created model clarifies impact of individual variables on the coalition for-mation process and confirms its ability to investigate given area.

How can we model global phenomenon based on local interactions? Agent-Based (AB) models are local rule-based discrete method that can be used to simulate complex interactions of many agents. Unfortunately, the relative ease of implementing the computational model is often counter-balanced by the difficulty of performing rigorous analysis to determine emergent behaviors. Calculating existence of fixed points and their stability is not tractable from an analytical perspective and can become computationally expensive, involving potentially millions of simulations. To construct meaningful analysis, we need to create a framework to approximate the emergent, global behavior. Our research has been devoted to developing a framework for approximating AB models that move via random walks and undergo state transitions. First, we developed a general method to estimate the density of agents in each state for AB models whose state transitions are caused by neighborhood interactions between agents. Second, we extended previous random walk models of instantaneous state changes by adding a cumulative memory effect. In this way, our research seeks to answer how memory properties can also be incorporated into continuum models, especially when the memory properties effect state changes on the agents. The state transitions in this type of AB model is primarily from the agents’ interaction with their environment. These modeling frameworks will be generally applicable to many areas and can be easily extended.

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