951 resultados para vector auto-regressive model
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Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubblelike deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the nonfundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.
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Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.
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Dengue is an important vector-borne virus that infects on the order of 400 million individuals per year. Infection with one of the virus's four serotypes (denoted DENV-1 to 4) may be silent, result in symptomatic dengue 'breakbone' fever, or develop into the more severe dengue hemorrhagic fever/dengue shock syndrome (DHF/DSS). Extensive research has therefore focused on identifying factors that influence dengue infection outcomes. It has been well-documented through epidemiological studies that DHF is most likely to result from a secondary heterologous infection, and that individuals experiencing a DENV-2 or DENV-3 infection typically are more likely to present with more severe dengue disease than those individuals experiencing a DENV-1 or DENV-4 infection. However, a mechanistic understanding of how these risk factors affect disease outcomes, and further, how the virus's ability to evolve these mechanisms will affect disease severity patterns over time, is lacking. In the second chapter of my dissertation, I formulate mechanistic mathematical models of primary and secondary dengue infections that describe how the dengue virus interacts with the immune response and the results of this interaction on the risk of developing severe dengue disease. I show that only the innate immune response is needed to reproduce characteristic features of a primary infection whereas the adaptive immune response is needed to reproduce characteristic features of a secondary dengue infection. I then add to these models a quantitative measure of disease severity that assumes immunopathology, and analyze the effectiveness of virological indicators of disease severity. In the third chapter of my dissertation, I then statistically fit these mathematical models to viral load data of dengue patients to understand the mechanisms that drive variation in viral load. I specifically consider the roles that immune status, clinical disease manifestation, and serotype may play in explaining viral load variation observed across the patients. With this analysis, I show that there is statistical support for the theory of antibody dependent enhancement in the development of severe disease in secondary dengue infections and that there is statistical support for serotype-specific differences in viral infectivity rates, with infectivity rates of DENV-2 and DENV-3 exceeding those of DENV-1. In the fourth chapter of my dissertation, I integrate these within-host models with a vector-borne epidemiological model to understand the potential for virulence evolution in dengue. Critically, I show that dengue is expected to evolve towards intermediate virulence, and that the optimal virulence of the virus depends strongly on the number of serotypes that co-circulate. Together, these dissertation chapters show that dengue viral load dynamics provide insight into the within-host mechanisms driving differences in dengue disease patterns and that these mechanisms have important implications for dengue virulence evolution.
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This paper analyzes the dynamics ofthe American Depositary Receipt (ADR) of a Colombian bank (Bancolombia) in relation to its pricing factors (underlying (preferred) shares price, exchange rate and the US market index). The aim is to test if there is a long-term relation among these variables that would imply predictability. One cointegrating relation is found allowing the use of a vector error correction model to examine the transmission of shocks to the underlying prices, the exchange rate, and the US market index. The main finding of this paper is that in the short run, the underlying share price seems to adjust after changes in the ADR price, pointing to the fact that the NYSE (trading market for the ADR) leads the Colombian market. However, in the long run, both, the underlying share price and the ADR price, adjust to changes in one another.
An empirical investigation of the impact of global energy transition on Nigerian oil and gas exports
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18 months embargo on the thesis and check appendix for copy right materials
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The reaction of nine vector species of Chagas' disease to infection by seven different Trypanosoma cruzi strains; Berenice, Y, FL, CL, S. Felipe, Colombiana and Gávea, are examined and compared. On the basis of the insects' ability to establish and maintain the infection, vector species could be divided into two distinct groups which differ in their reaction to an acute infection by T. cruzi. While the proportion of positive bugs was found to be low in Triatoma infestans and Triatoma dimidiata it was high, ranging from 96.9% to 100% in the group of wild (Rhodnius neglectus, Triatoma rubrovaria)and essentially sylvatic vectors in process of adaptation to human dwellings, maintained under control following successful insecticidal elimination of Triatoma infestans (Panstrongylus megistus, Triatoma sordida and Triatoma pseudomaculata). An intermediate position is held by Triatoma brasiliensis and Rhodnius prolixus. This latter has been found to interchange between domestic and sylvatic environments. The most important finding is the strikingly good reaction between each species of the sylvatic bugs and practically all T. cruzi strains herein studied, thus indicating that the factors responsible for the excellent reaction of P.megistus to infection by Y strain, as previously reported also come into operation in the reaction of the same vector species to acute infections by five of the remaining T.cruzi strains. Comparison or data reported by other investigators with those herein described form the basis of the discussion of Dipetalogaster maximus as regards its superiority as a xenodiagnostic agent.
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Previous studies (1982,1987) have emphasized the superiority of sylvatic vector species over domestic species as xenodiagnostic agents in testing hosts with acute or chronic infections by T. cruzi "Y" stock. The present study, which is unique in that it contains data on both infectivity rates produced by the same stock in 11 different vector species and also the reaction of the same vector species to seven different parasite stocks, establishes the general validity of linking efficiency of xenodiagnosis to the biotope of its agent. For example, infectivity rates produced by "São Felipe" stock varied from 82.5% to 98.3% in sylvatic vectors but decreased to 42.5% to 71.3% in domestic species. "Colombiana" stock produced in the same sylvatic vectors infectivity rates ranging from 12.5% to 45%. These shrank to 5%-22.5% in domestic bugs. The functional role of the biotope in the vector-parasite interaction has not been eluddated. But since this phenomenon has been observed to be stable and easy to reproduce, it leads us to believe that the results obtained are valid. Data presented also provide increasing evidence that the infectivity rates exhibited by bugs from xenodiagnosis in chronic hosts, are parasite stock specific. For example, infectivity rates produced by "Berenice", "Y", "FL" and "CL" varied in R. neglectus from 26.3% to 75%; in P. megistus from 56.3% to 83.8%; in T. sordida from 28.8% to 58.8% in T. pseudomaculata from 41.3% to 66.3% and in T. rubrovaria from 48.8% to 85%. Data from xenodiagnosis in the same hosts, carrying acute infections by the same parasite stocks, gave the five sylvatic vectors a positive rating of approximately 100%, thus suggesting that the heavy loads of parasites circulating in the acute hosts obscured the characteristic interspecific differences for the parasite stock. Nonetheless these latter were revealed in the same hosts with chronic infections stimulated by very low numbers of the same parasite stocks. Certain observations here described lead us to speculate as to the possibility of further results from other parasite stocks, allowing the association of the infectivity rates produced in bugs by different parasite stocks with the isoenzymic patterns revealed by these stocks.
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OBJECTIVE: Describe the overall transmission of malaria through a compartmental model, considering the human host and mosquito vector. METHODS: A mathematical model was developed based on the following parameters: human host immunity, assuming the existence of acquired immunity and immunological memory, which boosts the protective response upon reinfection; mosquito vector, taking into account that the average period of development from egg to adult mosquito and the extrinsic incubation period of parasites (transformation of infected but non-infectious mosquitoes into infectious mosquitoes) are dependent on the ambient temperature. RESULTS: The steady state equilibrium values obtained with the model allowed the calculation of the basic reproduction ratio in terms of the model's parameters. CONCLUSIONS: The model allowed the calculation of the basic reproduction ratio, one of the most important epidemiological variables.
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This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.
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We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.
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We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.
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We tested experimentally the effects of the presence of non-susceptible hosts on the infection with Trypanosoma cruzi of the vector Triatoma infestans. The experiment consisted in two treatments: with chickens, including two chickens (non-susceptible hosts) and two infected guinea pigs (susceptible hosts), and without chickens, including only two infected guinea pigs. The hosts were held unrestrained in individual metal cages inside a closed tulle chamber. A total of 200 uninfected T. infestans third instar nymphs were liberated in each replica, collected on day 14, and examined for infection and blood meal sources on day 32-36. The additional presence of chickens relative to infected guinea pigs: (a) significantly modified the spatial distribution of bugs; (b) increased significantly the likelihoods of having a detectable blood meal on any host and molting to the next instar; (c) did not affect the bugs' probability of death by predation; and (d) decreased significantly the overall percentage of T. infestans infected with T. cruzi. The bugs collected from inside or close to the guinea pigs' cages showed a higher infection rate (71-88%) than those collected from the chickens' cages (22-32%). Mixed blood meals on chickens and guinea pigs were detected in 12-21% of bugs. Although the presence of chickens would decrease the overall percentage of infected bugs in short term experiments, the high rate of host change of T. infestans would make this difference fade out if longer exposure times had been provided.
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In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.