7 resultados para fund attributes

em Helda - Digital Repository of University of Helsinki


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This study investigates the relationship between fund attributes and performance. The focus is on funds available in the Swedish Premium Pension system (PPM-funds). The aim has been to investigate whether administration fees, manager tenure or past performance are of importance for pension savers when they pick their PPM-funds. The results indicate that high fees are a disadvantage to pension savers investing in bond funds but not to those investing in stock funds. Manager tenure has no relationship with performance. There is evidence of performance persistency in most of the investigated fund categories.

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This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.

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Remote sensing provides methods to infer land cover information over large geographical areas at a variety of spatial and temporal resolutions. Land cover is input data for a range of environmental models and information on land cover dynamics is required for monitoring the implications of global change. Such data are also essential in support of environmental management and policymaking. Boreal forests are a key component of the global climate and a major sink of carbon. The northern latitudes are expected to experience a disproportionate and rapid warming, which can have a major impact on vegetation at forest limits. This thesis examines the use of optical remote sensing for estimating aboveground biomass, leaf area index (LAI), tree cover and tree height in the boreal forests and tundra taiga transition zone in Finland. The continuous fields of forest attributes are required, for example, to improve the mapping of forest extent. The thesis focus on studying the feasibility of satellite data at multiple spatial resolutions, assessing the potential of multispectral, -angular and -temporal information, and provides regional evaluation for global land cover data. Preprocessed ASTER, MISR and MODIS products are the principal satellite data. The reference data consist of field measurements, forest inventory data and fine resolution land cover maps. Fine resolution studies demonstrate how statistical relationships between biomass and satellite data are relatively strong in single species and low biomass mountain birch forests in comparison to higher biomass coniferous stands. The combination of forest stand data and fine resolution ASTER images provides a method for biomass estimation using medium resolution MODIS data. The multiangular data improve the accuracy of land cover mapping in the sparsely forested tundra taiga transition zone, particularly in mires. Similarly, multitemporal data improve the accuracy of coarse resolution tree cover estimates in comparison to single date data. Furthermore, the peak of the growing season is not necessarily the optimal time for land cover mapping in the northern boreal regions. The evaluated coarse resolution land cover data sets have considerable shortcomings in northernmost Finland and should be used with caution in similar regions. The quantitative reference data and upscaling methods for integrating multiresolution data are required for calibration of statistical models and evaluation of land cover data sets. The preprocessed image products have potential for wider use as they can considerably reduce the time and effort used for data processing.

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The benefits and drawbacks of homogeneity and heterogeneity have been debated at length. Whereas some researchers assert that heterogeneity is beneficial for groups that are engaged in complex problem solving, the other researchers emphasize the potential costs associated with diversity. The inconsistency is a result of the incomplete measurement of diversity and focus one or two types of diversity. Most research concentrates on the readily detected/visible characteristics, making the assumption that such characteristics are related to underlying attributes (e.g., attitudes and values). In many cases, the demographic characteristics do not covary perfectly with the psychological attributes. Thus both types of attributes need to be utilized to fully understand the impact of diversity. The present research with four essays takes into account both types of attributes and tests their impact on social integration in cross-cultural settings. The results indicate that: (1) readily detectable- and underlying attributes are not related; (2) diversity has overall a negative impact on social integration; (3) socio-cultural context potentially influences the salience of diversity; and (4) diversity and social integration influences the formation of social cognition in form of transactive memory directories. The limits of research and managerial implications are discussed.

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This study contributes to the mutual fund literature by looking at performance persistence on a fund family level, allowing for individual equity, bond and balanced funds to be included under single family umbrellas. The study is conducted on the emerging Finnish mutual fund market, an environment in which the importance of superior fund family teams is likely to be accentuated. Using both non–parametric and parametric tests we find robust evidence of performance persistence for the fund families. Persistence is particularly strong in the first half of the investigation period, which highlights the importance of fund families at early stages of market development.