Biztosítók kockázatdiverzifikációja (Risk diversification of insurers)

A biztosítók működését általában több homogén részállományból összetevődő heterogén biztosítási állomány jellemzi. A részállományok alkotta biztosítási portfólió esetében a kockázatdiverzifikáció vizsgálható a teljes állományra, illetve a részállományokra összesített kockázatok különbségeként, és elemezhető a kockázat és hozam kapcsolata alapján is. A biztosítók működésének főbb sajátosságait tartalmazó modellben azt mutatjuk meg, hogy a biztosítási portfólió esetében tapasztalható kockázatdiverzifikációs hatások milyen mértékben hasonlítanak a klasszikusnak számító, befektetésekkel foglalkozó Markowitz-féle portfólióelmélet által leírtakra. Modellünk alapján megállapítható: számos hasonlóságon túl a biztosító működési sajátosságai következtében a hatékony biztosítási portfóliók, illetve az optimális befektetési arányok meghatározása egyedi tulajdonságokkal jellemezhető. / === / Insurance is generally characterized by a heterogeneous insurance population made up of several (homogeneous) sub-populations. Risk diversification in the "insurance portfolio" containing these sub-populations can appear as a difference between the risk of the total population and the sum of the risks of the separate sub-populations, and it can also be analysed based on the relation of risk and return. Examining these aspects of risk diversification with a model covering the main features of insurance activity, the study analyses how far the risk diversification effects of the insurance portfolio resemble the results of classical Markowitz portfolio theory. Based on the results from the study's theoretical model, it appears that alongside several similarities, there are some individual features in the determination of "efficient insurance portfolios" and optimal investment weights.

Effect of Hydrologic Restoration on the Habitat of The Cape Sable Seaside Sparrow, Annual Report of 2002-2003

After developing field sampling protocols and making a series of consultations with investigators involved in research in CSSS habitat, we determined that vegetationhydrology interactions within this landscape are best sampled at a combination of scales. At the finer scale, we decided to sample at 100 m intervals along transects that cross the range of habitats present, and at the coarser scale, to conduct an extensive survey of vegetation at sites of known sparrow density dispersed throughout the range of the CSSS. We initiated sampling in the first week of January 2003 and continued it through the last week of May. During this period, we established 6 transects, one in each CSSS subpopulation, completed topographic survey along the Transects A, C, D, and F, and sampled herb and shrub stratum vegetation, soil depth and periphyton along Transects A, and at 179 census points. We also conducted topographic surveys and completed vegetation and soil depth sampling along two of five transects used by ENP researchers for monitoring long-term vegetation change in Taylor Slough. We analyzed the data by summarizing the compositional and structural measures and by using cluster analysis, ordination, weighted averaging regression, and weighted averaging calibration. The mean elevation of transects decreased from north to south, and Transect F had greater variation than other transects. We identified eight vegetation assemblages that can be grouped into two broad categories, ‘wet prairie’ and ‘marsh’. In the 2003 survey, wet prairies were most dominant in the northeastern sub-populations, and had shorter inferred-hydroperiod, higher species richness and shallower soils than marshes, which were common in Subpopulations A, D, and the southernmost regions of Sub-population B. Most of the sites at which birds were observed during 2001 or 2002 had an inferred-hydroperiod of 120-150 days, while no birds were observed at sites with an inferred-hydroperiod less than 120 days or more than 300 days. Management-induced water level changes in Taylor Slought during the 1980’s and 1990’s appeared to elicit parallel changes in vegetation. The results described in detail in the following pages serve as a basis for evaluating and modifying, if necessary, the sampling design and analytical techniques to be used in the next three years of the project.

An investigation of sugar-sweetened beverage consumption among Canadian youth

Background: Consumption of sugar-sweetened beverages (SSBs) is an important public health problem in Canada, especially among adolescents. Estimates show that rates of SSB consumption are particularly high in the northern territories, especially in Nunavut. This is concerning given that regular SSB consumption is associated with obesity, diabetes and tooth decay, among other health concerns. Objectives: This thesis has two objectives. The first is to describe SSB consumption patterns among adolescents from Nunavut specifically, all three territories combined and the provinces.The second is to determine the association between individual and cumulative school food programs and SSB consumption. Methods: Data were obtained from the Health Behaviour in School-aged Children study (HBSC); a cross-sectional survey of Canadian youth in grades 6-10. All frequencies for food and beverage consumption were obtained from a 7-day food frequency questionnaire. SSB consumption consisted of a composite measure including soft drinks, sports drinks and energy drinks. The types of school food programs were obtained from an administrative questionnaire filled out by each school’s Principal or delegate. Multilevel multivariate Poisson regression models were used to examine the associations between school food programs and SSB consumption. Results: Youth from Nunavut consumed the most SSBs (53.1% in 2010 and 55.0% in 2014 were daily consumers), followed by youth from the territories (31.1% in 2010 and 27.0% in 2014), then youth from the provinces (24.3% in 2010 and 19.1% in 2014). No significant relationships were found between school food programs and daily SSB consumption. Two school food programs were weakly associated with weekly SSB consumption: nutrition month activities (RR=0.93,CI=0.89, 0.98) and healthy options in the snack bar (RR=1.07, CI=1.01, 1.14). Conclusions:Rates of SSB consumption were highest among Nunavummiut youth followed by youth from all three territories combined and then the provinces. Little association was found between school food programs and SSB consumption among Canadian youth in grades 6-10. These findings point to the need for examining other determinants and potential areas for intervention, for reducing SSB consumption among Canadian youth, particularly in high consumer sub-populations.

A Pyramidal Genetic Algorithm for Multiple-Choice Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence, higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

Partnering Strategies for Fitness Evaluation in a Pyramidal Evolutionary Algorithm

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes for (sub-)fitness evaluation purposes are examined for two multiple-choice optimisation problems. It is shown that random partnering strategies perform best by providing better sampling and more diversity.

'Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem'

There is considerable interest in the use of genetic algorithms to solve problems arising in the areas of scheduling and timetabling. However, the classical genetic algorithm paradigm is not well equipped to handle the conflict between objectives and constraints that typically occurs in such problems. In order to overcome this, successful implementations frequently make use of problem specific knowledge. This paper is concerned with the development of a GA for a nurse rostering problem at a major UK hospital. The structure of the constraints is used as the basis for a co-evolutionary strategy using co-operating sub-populations. Problem specific knowledge is also used to define a system of incentives and disincentives, and a complementary mutation operator. Empirical results based on 52 weeks of live data show how these features are able to improve an unsuccessful canonical GA to the point where it is able to provide a practical solution to the problem.

'On the Application of Hierarchical Coevolutionary Genetic Algorithms: Recombination and Evaluation Partners'

This paper examines the use of a hierarchical coevolutionary genetic algorithm under different partnering strategies. Cascading clusters of sub-populations are built from the bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations potentially search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the sub-populations on solution quality are examined for two constrained optimisation problems. We examine a number of recombination partnering strategies in the construction of higher-level individuals and a number of related schemes for evaluating sub-solutions. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

A Pyramidal Evolutionary Algorithm with Different Inter-Agent Partnering Strategies for Scheduling Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem

There is considerable interest in the use of genetic algorithms to solve problems arising in the areas of scheduling and timetabling. However, the classical genetic algorithm paradigm is not well equipped to handle the conflict between objectives and constraints that typically occurs in such problems. In order to overcome this, successful implementations frequently make use of problem specific knowledge. This paper is concerned with the development of a GA for a nurse rostering problem at a major UK hospital. The structure of the constraints is used as the basis for a co-evolutionary strategy using co-operating sub-populations. Problem specific knowledge is also used to define a system of incentives and disincentives, and a complementary mutation operator. Empirical results based on 52 weeks of live data show how these features are able to improve an unsuccessful canonical GA to the point where it is able to provide a practical solution to the problem.

Partnering Strategies for Fitness Evaluation in a Pyramidal Evolutionary Algorithm

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes for (sub-)fitness evaluation purposes are examined for two multiple-choice optimisation problems. It is shown that random partnering strategies perform best by providing better sampling and more diversity.

A Pyramidal Evolutionary Algorithm with Different Inter-Agent Partnering Strategies for Scheduling Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

A Pyramidal Genetic Algorithm for Multiple-Choice Problems

This paper combines the idea of a hierarchical distributed genetic algorithm with different inter-agent partnering strategies. Cascading clusters of sub-populations are built from bottom up, with higher-level sub-populations optimising larger parts of the problem. Hence, higher-level sub-populations search a larger search space with a lower resolution whilst lower-level sub-populations search a smaller search space with a higher resolution. The effects of different partner selection schemes amongst the agents on solution quality are examined for two multiple-choice optimisation problems. It is shown that partnering strategies that exploit problem-specific knowledge are superior and can counter inappropriate (sub-) fitness measurements.

'Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem'

There is considerable interest in the use of genetic algorithms to solve problems arising in the areas of scheduling and timetabling. However, the classical genetic algorithm paradigm is not well equipped to handle the conflict between objectives and constraints that typically occurs in such problems. In order to overcome this, successful implementations frequently make use of problem specific knowledge. This paper is concerned with the development of a GA for a nurse rostering problem at a major UK hospital. The structure of the constraints is used as the basis for a co-evolutionary strategy using co-operating sub-populations. Problem specific knowledge is also used to define a system of incentives and disincentives, and a complementary mutation operator. Empirical results based on 52 weeks of live data show how these features are able to improve an unsuccessful canonical GA to the point where it is able to provide a practical solution to the problem.

Etude électrophorétique des protéines solubles du cristallin de la sardine (Clupea pilchardus Walb.) du Golfe du Lion

The eye lens proteins electrophoresis of pilchard of the Gulf of Lion (Clupea pilchardus Walb.) shows the existence of 2 sub-populations. The hypothesis of an hereditary control by two co-dominant allels is in agreement with the expected Hardy-Weinberg distribution.

Morphometric characteristics of Prochilodus lineatus (Valenciennes 1847), of the migratory and resident stocks of the river Mogí-Guaçu, São Paulo State, Brazil

A espécie Prochilodus lineatus é de grande importância comercial na região dos rios Grande, Pardo e Mogi-Guaçu e tem como característica a formação de grandes cardumes, apta a desenvolver amplos deslocamentos migratórios. O presente trabalho objetivou avaliar, por meio das características morfométricas e etária, se os curimbatás (P. lineatus) dos diferentes estoques migradores e residentes constituem uma única população, havendo interação entre as sub-populações no período de piracema (migração reprodutiva). Utilizou-se um delineamento inteiramente casualizado em esquema fatorial 4 x 2, com quatro tipos de estoques (um residente e três migradores) e dois sexos (macho e fêmea) com trinta repetições, considerando cada peixe como unidade experimental. Foi observada variação de 80,19% para o primeiro componente principal e 8,09% do segundo componente principal fornecida pelas dez variáveis morfométricas dos estoques residentes e migradores. O estoque residente correspondeu aos maiores valores para todas as variáveis morfométricas. Houve sobreposição dos escores individuais das mesmas características entre os estoques migradores. Observou-se predominância de machos entre os estoques residentes e migrador I e II. As semelhanças morfométricas verificadas entre os estoques migradores indicam tratar-se de uma única população, com pequenas variações interpopulacional.