O presente trabalho busca identificar bull e bear markets para o mercado financeiro brasileiro, especificamente para o índice Ibovespa, através das principais metodologias existentes na literatura: regras não paramétricas e modelos de mudança de regime markoviano. A primeira abordagem foi utilizada como benchmark para comparação com melhor modelo econométrico estimado pela segunda abordagem, visto que trata-se de um método ex-post de identificação. No tange aos modelos de mudança de regime markoviano, constatou-se que permitir regimes distintos também para a variância da série contribui para a identificação dos mesmos. Desta forma, o melhor modelo obtido fora o MSARMA(2,1)-2 para a série de retornos semanais do índice Ibovespa. O modelo foi capaz de identificar os principais eventos que impactaram a economia e o mercado financeiro brasileiro no período. Além disto, o modelo se mostrou útil para a tomada de decisão, visto que a estratégia de investimento, baseada na previsão um passo à frente do estado do mercado, foi capaz de preservar o capital do investidor, gerando um melhor desempenho do que na estratégia buy-and-hold de longo prazo. / This paper seeks to identify bull and bear markets in the brazilian stock market, specifically to the time series of the Ibovespa index, through the main methodologies present in literature: identification based on rules and Markov switching models. The first method was used as a benchmark to compare with the best regime switching model, since it is an ex-post method of identification. Modelling a Markov switching model with two regimes also for the variance of the process resulted in a better identification of the markets. Thus, the best Markov switching model estimated was theMSARMA(2,1)-2 to the time series of the Ibovespa weekly returns. The model was able to identify the main events that have impacted the brazilian economy and also the stock market in the period. Furthermore, the model proved its value in decision making, since in a investment strategy, based on the models one step ahead forecast about the regime of the market, it was able to preserve investor capital, generating a better performance than the buy-and-hold strategy.

O presente trabalho busca identificar bull e bear markets para o mercado financeiro brasileiro, especificamente para o índice Ibovespa, através das principais metodologias existentes na literatura: regras não paramétricas e modelos de mudança de regime markoviano. A primeira abordagem foi utilizada como benchmark para comparação com melhor modelo econométrico estimado pela segunda abordagem, visto que trata-se de um método ex-post de identificação. No tange aos modelos de mudança de regime markoviano, constatou-se que permitir regimes distintos também para a variância da série contribui para a identificação dos mesmos. Desta forma, o melhor modelo obtido fora o MSARMA(2,1)-2 para a série de retornos semanais do índice Ibovespa. O modelo foi capaz de identificar os principais eventos que impactaram a economia e o mercado financeiro brasileiro no período. Além disto, o modelo se mostrou útil para a tomada de decisão, visto que a estratégia de investimento, baseada na previsão um passo à frente do estado do mercado, foi capaz de preservar o capital do investidor, gerando um melhor desempenho do que na estratégia buy-and-hold de longo prazo. / This paper seeks to identify bull and bear markets in the brazilian stock market, specifically to the time series of the Ibovespa index, through the main methodologies present in literature: identification based on rules and Markov switching models. The first method was used as a benchmark to compare with the best regime switching model, since it is an ex-post method of identification. Modelling a Markov switching model with two regimes also for the variance of the process resulted in a better identification of the markets. Thus, the best Markov switching model estimated was theMSARMA(2,1)-2 to the time series of the Ibovespa weekly returns. The model was able to identify the main events that have impacted the brazilian economy and also the stock market in the period. Furthermore, the model proved its value in decision making, since in a investment strategy, based on the models one step ahead forecast about the regime of the market, it was able to preserve investor capital, generating a better performance than the buy-and-hold strategy.

Contemporary children’s books, particularly picture books, show an increasing tendency towards complexity and sophistication. There is, however, some resistance to this tendency in the children’s book world. This thesis therefore critically analyses complexity and sophistication in three picture books - chosen because they represent particularly high numbers of the most common complexities and sophistications - in order to determine whether or not such resistance is appropriate. The study defines picture books as fictional, illustrated books in which pictures and design are vehicles for meaning, where text and art are integral aspects of an interdependent relationship. It thus examines words, the roles of words and pictures and their interactions, linear progression, time and page-breaks, rhythm, design, colour, medium, style, line, regularity, balance, framing, shot, point of view, gaze, visual weight, position, shape, size, light, background, symbol, pictorial analogy, visual games, nonsense, intervisuality, intravisuality, leitmotif and counterpoint. The sophisticated structure, polyphony, visual nonsense and allusion of Anthony Browne’s Voices in the Park allow deep, complex examinations of its characters’ psychologies, making marginalized groups visible and critiquing stereotypes of class, gender, family structure and unemployment. Its sophistications and complexities thus enable Browne’s book to satisfy significant priorities in the children’s book world, because it avoids overt didacticism, respects “literary” values and is socially aware. The sophisticated structure, visual nonsense, multidimensionality and multivoicedness of David McKee’s I Hate My Teddy Bear raise problems of narrative and focalizer, overtly inscribe inconsistency, vagueness and uncertainty, and determinedly resist resolution. McKee’s book thus refuses to imply a clear reader role, and situates readers firmly outside itself, where subjection to any one interaction with, response to or idea within it becomes impossible. This stimulates child readers’ creative thought, and distributes power between adult writers and child readers unusually equitably, thus offering children the respect and power of literary and ideological self-determination in a safe, restricted area of fiction. John Burningham’s Granpa neglects many of the conventions of writing and storytelling, so that readers face the multiplexity of its form and structure, the emergence of its linear narrative from apparent stasis into irresolution and ambiguity, and its difficult themes and psychological content, with very little guidance in their reading beyond frequently confusing formal signals. This is difficult for adult readers, who have learnt to expect certain conventions from stories, and to use them to interpret and predict what they read. It may, however, be particularly easy for child readers, because it does not force them to read in ways that are still foreign to and thus possibly difficult for them. It may even be less threatening to children and antagonistic to children’s culture than most children’s books, because it does not socialize children into the alien adult culture concomitant with conventional reading. Together, these analyses reveal that complex, sophisticated children’s books may function in a variety of ways. The children’s book world should thus rather evaluate them individually than reject the entire genre. / Dissertation (MA (English))--University of Pretoria, 2005. / English / unrestricted

The diploma thesis deals with takeover techniques and regulation of takeovers in the Czech law system. In the theoretical part of the paper there are explained key definitions and general facts concerning with takeovers. The main theme of the theoretical part analyzes the most frequent takeover techniques. The paper studies how particular techniques work. It also takes into account expert discussions about the takeover theme. The takeover laws of the Czech Republic are analyzed in the second part of the diploma thesis. The paper contains a synthesis of theoretical findings and regulation of corresponding laws. It reveals practical use of particular takeover techniques in the Czech Republic.

The purpose of this project is to apply the theories of John Dewey's experiential learning, providing the foundation of place-based curriculum incorporating community investigation, outdoor education, and project-based learning into an EFL curriculum.

Bakgrund: Människor tenderar att i större grad investera i bekanta företag i närområden, detta psykologiska fenomen kallas för home bias. Det kan bli problematiskt då det kan medföra att investerare inte optimerar sina portföljer utifrån risk, avkastning och korrelation mellan tillgångarna i portföljen. Tidigare forskning kring home bias har indikerat på att fenomenet kan drivas av olika förklaringsmekanismer, exempelvis marknadsförhållanden, volatilitet och transaktionskostnader. Forskningen kring home bias har i mindre skala fokuserat på hur home bias förändras i olika marknadsförhållanden dessutom finns endast begränsad forskning om detta för svenska fonder vilket är varför det var intressant att undersöka denna kunskapslucka. Syfte: Syftet var att undersöka och analysera potentiell exponering och förändring av home bias i svenskregistrerade fonder vid marknadsförändringar i ekonomin mellan år 1994–2018. För att definiera olika marknadsförhållanden används termerna bear-marknad vilket är en kontraherande marknad och bull-marknad som är motsatsen. Detta har sedan undersökts och analyserats tillsammans med de två valda förklaringsmekanismerna volatilitet och transaktionskostnader. Metod: Studien var kvantitativ med en deduktiv ansats. Den primära datan har bestod av den totala svenska fondförmögenheten mellan 1994–2018 och den totala världsmarknadsportföljen. Dessutom har indexdata använts för att fånga marknadsförändringar och svenska genomsnittliga fondavgifter för att beskriva transaktionskostnader. Att inkludera volatilitet och transaktionskostnader grundade sig på den tidigare forskningens tyngdpunkt på dessa två mekanismer. Analysmetoden har främst utgått från hypotestest för dessa variabler. Slutsats: Resultatet av studien hittade signifikanta samband för home bias för svenskregistrerade fonder både för bear-och bull-marknad, vilket ligger i linje med tidigare forskning som har sett att bear-marknader leder till ökning av home bias på grund av att osäkerheten i omvärlden gör investerare i större grad villiga att placera i det bekanta. Dessutom har tidigare forskning visat att home bias minskar under säkrare perioder vilket denna studies resultat av sambandet mellan bull-marknaden och home bias indikerat. Vidare visade båda förklaringsmekanismerna att de har ett signifikant samband med home bias. Resultatet har därmed bidragit till kunskap om home bias i marknadsförhållanden för den svenska fondmarknaden och kan i större grad motverka investerare att hamna i psykologiska fällor som leder till sämre investeringsbeslut. / Background: People tend to invest a large portion of their investments in familiar companies near their home area, this psychological phenomenon is called home bias. This can become problematic thus it means that investors do not optimize their portfolios based on risk, return and correlation between assets in the portfolio. In addition, there are studies that indicate that home bias is driven by various explanatory mechanisms, for example market conditions, volatility and transaction costs. Research about home bias has in a smaller scale focused on how home bias changes in different market conditions, especially in Sweden and for funds, therefore it would be interesting to investigate this knowledge gap. Purpose: The purpose of this study was to examine and analyze the relationship between funds registered in Sweden and their potential exposure to home bias in various market conditions in the economy between 1994-2018. To define market conditions, the concepts bear market is used when the market is in a contracting phase and bull market is used when the opposite conditions occur. This has been examined and analyzed together with the two selected explanatory mechanisms volatility and transaction costs. Method: The method for this research is quantitative with a deductive approach. The primary data used to investigate home bias comes from statistics of total Swedish fund assets between 1994-2018 and the total world market portfolio. Furthermore, index data is used to capture market changes and data of average fund fees are used to examine transaction costs. The choice to include volatility and transaction costs is based on the previous research emphasis on these two mechanisms. The method of analysis is based primarily on hypothesis testing for the mentioned variables. Conclusion: The result of the study shows that the relationship between bear and bull markets and home bias for funds registered in Sweden are significant. Which is in line with previous research that states that bear markets lead to an increase in home bias because the uncertainty around the world makes investors to a greater extent willing to invest in the familiar. In addition, previous research has shown that home bias decreases during safer periods, which the results of the relationship between the bull market and home bias indicate in this study. Furthermore, both explanatory mechanisms showed that they are significantly associated with home bias. The result has contributed to the knowledge of home bias for the Swedish fund market in various market conditions and can in a larger scale counteract investors to fall in to psychological traps and go through with badly made investment decisions.

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The convergence of three young scientific disciplines (ecology, geospatial sciences, and remote sensing) has generated unique advancements in wildlife research by connecting ecological data with remote sensing data through the application of geospatial techniques. Ecological datasets may contain spatial and sampling biases. By using geospatial techniques, datasets may be useful in revealing landscape scale (e.g., statewide) trends for wildlife populations, such as population recovery and human-wildlife interactions. Specifically, black bear populations across North America vary greatly in their degree of distribution stability. The black bear population in Michigan may be considered stable or secure, whereas the population in Missouri is currently recolonizing. The focus of the research in this dissertation is to examine the ecological and anthropogenic impacts 1) on human-black bear interactions in Michigan (see Chapter 2) and 2) on black bear presence in Missouri (see Chapter 3), through the use of black bear reports provided by the public to the state wildlife agencies. By using generalized linear modeling (GLM) and maximum entropy (MaxEnt), I developed spatial distribution models of probability of occurrence/presence for the 2 study areas (Michigan and Missouri). For the Missouri study, I quantified the spatiotemporal shifts in the probability of bear presence statewide. The results from my statewide studies corroborate previous local-scale research based on rigorous data collection. Overall, human-black bear interactions (e.g., wildlife sightings, conflicts), while very dynamic, appear greatest in forested and rural areas where the preferred habitat for black bears (i.e., forest) intersects with low density anthropogenic activities. As both human and black bear populations continue to expand, it is reasonable to expect human-black bear interactions to spatiotemporally increase across both study areas. The results from my studies provide wildlife managers with information critical to management decisions such as harvest regulations and habitat conservation actions across the landscape and through time. The ability to detect and monitor ecological changes through the use of geospatial techniques can lead to insights about the stressors and drivers of population-level change, further facilitating the development of proactive causeocused management strategies.

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