Bakgrund och problemformulering: Trots att humankapital ofta ses som en tillgång, får den inte tas upp i balansräkningen. Istället får företag frivilligt presentera information rörande personal i övriga delar i sina årsredovisningar. Vad för typ av information, och hur den ska redovisas, bestämmer företagen själva. Forskning senaste år har dock visat att företagen har slutat presentera information om humankapitalet, samt att det endast var en trend som nu bytts ut mot andra trender. Dessutom visar forskningen att rapporteringen varit ologiskt, och att företagens rapportering skiljer sig från år till år. Syfte: Syftet med studien är att bidra med en ökad förståelse om redovisningen av humankapitalet skiljer sig åt mellan företag ur olika sektorer. Vi vill med detta ge en bild av om och i så fall hur olika typer av företag redovisar humankapitalet. Detta för att skapa en bättre förståelse om humankapitalet är ett viktigt inslag i företagens redovisning, men även om det prioriteras olika beroende på vilken sektor de tillhör. Metod: En totalundersökning av företagen inom small cap från de tre sektorerna industri, teknologi och hälsovård på Nasdaq OMX Stockholm. Mätinstrumentet disclosure index användes vid analys och insamling av data från företagens årsredovisningar. Indexen delades in i 6 olika kategorier, och byggdes på ett tidigare index gjort av Bukh m.fl. (2005), samt en egen förstudie. Referensram: Här ges en djupare inblick inom begreppet humankapital och intellektuella kapitalet. Vidare ges en historisk återblick från 1960 talet till idag angående forskning och redovisningen av humankapitalet. Olika motiv och faktorer tas upp till varför företagen väljer att presentera humankapitalet. Empiri och slutsats: Undersökningens utfall visade på att det inte förkom direkta skillnader mellan sektorerna. Det var mer likheter än skillnader mellan sektorerna med hur de redovisar information om humankapitalet. Inga skillnader hittades angående mängden redovisat humankapital och endast små skillnader hittades angående innehållet. Detta resultat var oväntat, då det inte var tydliga skillnader mellan sektorerna. Vidare förekom det stora variationer avseende mängden mellan företagen inom respektive sektor. Den sektor som hade största genomsnittsmängden var teknologisektorn. Hälsovårdssektorn kom efter, och industrisektorn redovisade minst. Avseende vilken typ av information de presenterade så redovisade teknologisektorn främst information angående olika fördelningar på anställda. Industri- och hälsovårdssektorn presenterade däremot främst information angående personalens utveckling och motivation. / Background and research issue: Although human capital is often regarded as an asset, it cannot be included in the balance sheet. Instead, companies may voluntarily present information about their personal in other parts of their annual reports. What type of information, and how it should be reported, is up to the companies to determine themselves. However, research in recent years has shown that companies have ceased to present information about human capital, and that it was only a trend that has now been replaced with other trends. In addition, research shows that reporting has been illogical, and the reporting by the companies differs year to year. Purpose: The purpose of this study is to contribute to an increased understanding if the reporting of human capital differs between companies from different sectors. We want to give a picture if and how different types of companies report human capital. This is for a better understanding if human capital appears to be an important element in the companies accounting, also whether it is prioritized differently depending on which sector they belong to. Method: A total survey of small cap companies from the three sectors industry, technology and healthcare at Nasdaq OMX Stockholm. The measuring instrument disclosure index was used in analyzing and collecting data from the companies’ annual reports. The index was divided into 6 different categories, and was based on a previous index made by Bukh et al (2005), as well as a separate preliminary study. Empiricism: Here gives a deeper insight into the concept of human capital and intellectual capital. In addition, a historical recital from the 1960s to today is presented regarding research and the accounting of human capital. Furthermore, different motives are presented to show why companies choose to present human capital. Conclusion: The outcome of the study showed that there were no direct differences between the sectors. There were more similarities than differences between the sectors regarding how they report human capital. No differences were found regarding the amount of disclosure, and only a few differences was found regarding the type of information disclosed. This result was unexpected, as there were no clear differences in the reporting between each sector. Furthermore, there were large variations in the amount of disclosure between the companies in each sector. The sector with the largest average amount disclosure was the Technology sector. The Healthcare sector came after, and the Industry sector reported least. Regarding what type of information they presented, the Technology sector mainly reported information about different employee distributions. The Industry and Healthcare sector mainly presented information about staff development and motivation.

The thesis investigates the impact of the fundamental news announcements on the movements of the VIX volatility index and the VIX Futures prices. The theoretical part of the thesis explains the construction of the VIX Index and the VIX Futures, describes the most important fundamental news for the US economy and presents a methodology for the modelling of the relationship between the news announcements and the VIX index movements with a simple linear regression model. In the empirical part of the thesis, we analyze the impact of 105 US fundamental news, from the Reuters Eikon database, on the VIX Index movements on theday of the news announcements as well as on the subsequent day. We find a strong relationship between the surprise component of the news and the VIX Index movements on the day of the news announcement, with the statistically significant news explaining 5-10% of the total return variance (for news with small number of observations up to 30-50%) on the announcement day. In the second part of the empirical study, simple trading system is proposed in order to utilize the possible impact of the economic news on the next-day (after announcement) returns of VIX futures in order to achieve speculative profits. Although the models seem to possess some limited out-sample profitability for some of the news, the results are for most of the cases statistically insignificant and the potential profits from the news trading seem to be relatively low.

This thesis describes fundamental analysis method based on a price to earnings ratio and an effort is put on the following areas: (i) empirical verification of factors determining the price to earnings ratio, (ii) empirical verification of an investment strategy based on historical price to earnings ratios and (iii) behavior of P/Es in bear market periods. The empirical verification of the main factors determining the price to earnings ratio is conducted on empirical data for a sample of eleven stocks listed on Prague Stock Exchange in period 2006-2011. The empirical verification of macroeconomic factors determining the price to earnings ratio as well as the empirical verification of an investment strategy based on historical price to earnings ratios are researched based on empirical data of an equity index S&P 500 in period 1954-2011 and an equity index PX in period 2001-2011. Behavior of P/Es in bear markets is researched on empirical data of index S&P 500 in period 1954-2011 and index PX in period 2001-2011.

Soil moisture is a key variable in off-road mobility. Mobility analysis was conducted based on three soil moisture sources: WindSat (a satellite), LIS (a computer model), and in situ ground sensors (assumed to represent ground truth). Mobility of six vehicles, each with different ranges of sensitivity to soil moisture, was examined in three test sites. Two methods were used: a simplified method based on time series and a fulleatured terrain method. The results demonstrated that the effect of the soil moisture error on mobility predictions is complex and may produce very significant errors in mobility analysis for certain combinations of vehicles, seasons, and climates. Soil moisture biases vary in both direction and magnitude with season and location. Furthermore, vehicles are sensitive to different ranges of soil moistures. In the wet season, differences in soil strength resulted in more significant differences in mobility predictions than in the dry season.

The classical Extreme Value Theory deals with independent random variables. If random variables are dependent, large values tend to cluster (that is, one large value is followed by a series of large values). It is of interest to describe probabilistically the clustering and estimate the relevant cluster functionals. We consider disjoint blocks, sliding blocks and runs estimators of cluster indices. Using a modern theory of multivariate, regularly varying time series, we obtain consistency results and central limit theorems under conditions that can be easily verified for a large class of short-range dependent models. In particular, we show that in the Peak-over-Threshold framework, all the estimators have the same limiting variances. This solves a longstanding open problem and is in contrast to the Block Maxima method. Our findings are illustrated by simulation experiments.

As more dams experience spillway flows from flood events, identification and analysis of erosion in auxiliary rock surface spillways has become a primary focus in maintaining dam integrity. The spillway erosion risk assessment developed for this research is based on parameters identified and discussed in previous research as the leading factors influencing spillway damage from erosion. Parameters applied in this analysis were channel geometry, stream hydrology, and geologic materials. Channel geometry is described by the length of spillway channel and slope of the spillway floor; stream hydrology is classified by the peak discharge and its duration; and geologic material is identified by its behavior in resisting erosion. The Sites Spillway Erosion Analysis (SSEA) was used to produce a risk assessment based on U.S. Army Corps of Engineers case histories. The risk assessment was used to classify and refine model uncertainties, an important advancement in evaluating spillway erosion.

Location plays an ever increasing role in modern web-based applications. Many of these applications leverage off-the-shelf search engine technology to provide interactive access to large collections of data. Unfortunately, these commodity search engines do not provide special support for location-based indexing and retrieval. Many applications overcome this constraint by applying geographic bounding boxes in conjunction with range queries. We propose an alternative technique based on geographic identifiers and suggest it will yield faster query evaluation and provide higher search precision. Our experiment compared the two approaches by executing thousands of unique queries on a dataset with 1.8 million records. Based on the quantitative results obtained, our technique yielded drastic performance improvements in both query execution time and precision.

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Yes / In this paper, we focus on the financial and fiscal stress transmission for the G5 economies. Using financial and fiscal stress indexes, we assess the spillovers within each economy, as well as the cross-sectional effects. Two supplementary methodologies, measuring the degree of interconnectedness, are employed. Our findings indicate that the interactions between these two kinds of distress are intensive, especially during and after the Global Financial Crisis outbreak. The above reiterates the necessity for coordinated macroprudential policies, as a means to confine the adverse effects of excessive financial and fiscal stress.

Master of Science / Department of Statistics / Perla Reyes Cuellar / A frost index is a calculated value that can be used to describe the state and the changes in the weather conditions. Frost indices affect not only natural and managed ecosystems, but also a variety of human activities. In addition, they could indicate changes in extreme weather and climate events. Growing season length is one of the most important frost indices. In this report, growing season lengths were collected from 23 long-term stations over Kansas territory. The records extended to the late 1800s for a few stations, but many started observations in the early 1900s. Though the start dates of the records were different, the end dates were the same (2009). To begin with, time series models of growing season length for all the stations were fitted. In addition, by using fitted time series models, predictions and validation checking were conducted. Then a regular linear regression model was fitted for the GSL data. It removed the temporal trend by doing regression on year and it showed us the relationship between GSL and elevation. Finally, based on a penalized likelihood method with least angle regression (LARS) algorithm, spatial-temporal model selection and parameter estimation were performed simultaneously. Different neighborhood structures were used for model fitting. The spatial-temporal linear regression model obtained was used for interpreting growing season length of those stations across Kansas. These models could be used for agricultural management decision-making and updating recommendations for planting date in Kansas area.