Abstract Background - Bankruptcy is an issue that not only affects the company that is registered as bankrupt, but also the society since it has an impact on the economy. Previous studies have been focusing on larger listed companies outside of Sweden hence there is a lack of empirical findings about Swedish companies in this research area. Small and medium companies represent most of the Sweden's labor force and therefore the bankruptcy issue is important to investigate for these companies. Purpose - The purpose of the thesis is to find out which financial information distinguishes bankrupt from non-bankrupt companies in Sweden. In other words, which financial ratios have predictive power on bankruptcy. Furthermore, the thesis wants to provide knowledge towards current and future companies so that they can avoid bankruptcy by paying attention to the ratios distinguished in the thesis and keeping the ratios at an acceptable level. Method – The thesis conducts the research with a quantitative strategy by observing financial information from companies’ annual reports. The logistic regression model is used to test for the 11 ratios, by matching two samples; bankrupt and non-bankrupt companies, as well as a classification matrix, Pearson correlation matrix and variance inflation factor. The bankrupt companies selected, are classified as bankrupt for the period 2016-2019. The thesis implements a deductive approach to establish expectation and deduct which financial ratios are predictive. Conclusion - The thesis ends up with 92 companies, where 46 are bankrupt and 46 are nonbankrupt. Out of the 11 ratios, three are statistically significant and have predictive power on bankruptcy. These three are; debt rate, gross profit margin and, cash and cash equivalents. The debt rate has a positive effect on bankruptcy, which means that a higher debt rate increases the risk of bankruptcy. Gross profit margin and cash and cash equivalents have a negative effect on bankruptcy; as they increase, the risk of bankruptcy decreases.

The thesis deals with the recognition of the financial situation of „Hospodářské obchodní družstvo Jabloňov-Ruda“ in years 2012 – 2016. The first part of the thesis contains theoretic findings that are subsequently applied at the evaluation of the financial health of the analysed organization during the application of chosen methods of the strategic and financial analysis.On the basis of the total recognition of the financial situation of the agricultural co-operative, actions leading to improvements of an exist status are brought in.

The master‘s thesis deals with analysis of the financial situation of the company Znovín Znojmo, a.s. in years 2005 – 2008 by means of selected methods of the financial analysis. At the basis of identified problematic areas proposal of measures for an improvement of the present status of the company are formulated.

The aim of this thesis is to assess the level of financial management, joint-stock company Autic and formulation of proposals to improve the financial situation in problem areas. During its processing particularly the methods of financial analysis have found application. Data of the firm over the period of 2006 – 2008 are used for the financial analysis.

The Master’s thesis focuses on the evaluation of financial situation in selected company during the years 2011 – 2015. The first part of the thesis contains theoretical framework which is subsequently applied in evaluating the financial health of the company using suitable methods of the strategic and financial analysis. The next part consists of proposals to company’s improvement based on the overall assessment of the financial situation of the company.

This study develops a bankruptcy prediction model for South African companies listed on the Johannesburg Stock Exchange. The model is of considerable efficiency and the findings reported extend bankruptcy literature to developing countries. 64 financial ratios for 28 companies, grouped into failed and non-failed companies, were tested using multiple discriminant analysis after conducting normality tests. Three variables were found to be significant which are: Times Interest Earned, Cash to Debt and Working Capital to Turnover. The model correctly classified about 75% of failed and non-failed in the original and cross validation procedures. This study went on to conduct an external validation of the model superiority by introducing a sample of failed companies, which showed that the model predictive accuracy is more than chance. Despite the popularity of the topic among researchers this study highlighted the importance and relevance of the topic to corporate managers, policy makers and to investors especially in a developing market perspective, thereby contributing significantly towards understanding the factors that lead to corporate bankruptcy.

American black duck (Anas rubripes) populations declined throughout North America from 1950–1990, but the breeding population since has stabilized. However, limited information exists on black ducks in the Mississippi Flyway, where wintering populations continue to decline. I radiomarked 111 female black ducks at Tennessee National Wildlife Refuge (TNWR) in winters 2010–2012 to estimate winter survival and investigate patterns of habitat selection. Winter survival (83–85%) was greater than or comparable to previous estimates for black duck populations in North America. Interval survival increased 0.6% with a 100 g increase in body mass, but survival differed between years and waterfowl hunting seasons relative to body mass. Black ducks selected habitats on TNWR and emergent/scrub-shrub wetlands throughout winter regardless of hunting season or time of day. High winter survival rates and consistent use of TNWR suggest the refuge provides an important complex of habitats for black ducks wintering in Tennessee.

The concept of temperature dependent sex determination (TSD) has been somewhat of an evolutionary enigma for many decades and has had increased attention with the growing predictions of a changing climate, particularly in species that are already threatened or endangered. TSD taxa of concern include marine turtles, which go through various life stages covering a range of regions. This, in turn, creates difficulties in addressing basic demographic questions. Secondary sex ratios (from life stages post-hatchling) were investigated by capturing juvenile green turtles (Chelonia mydas), 22.6-60.9 cm in straight carapace length (SCL), from three developmental areas along the east coast of Florida (a region known to have important juvenile aggregations) by analyzing circulating testosterone levels. All three aggregations exhibited significant female biases with an overall ratio of 3.2:1 (female: male). The probability of a turtle being female increased as the size of the individual decreased. Ratios obtained in this study were slightly less female-biased, but not significantly different, than those observed in the late 1990s. However, they were significantly more biased than those found in a late 1980s pilot study. The shift to significantly female-biased ratios may be beneficial to a recovering population, an evolutionary adaptation, and is common among juvenile aggregations. A more skewed female bias in smaller size classes may be indicative of recent, warmer periods during incubation on the nesting beaches. This female bias could become more exaggerated if temperatures meet future climate warming predictions.

The thesis describes a stochastic procedure developed for assessing risk and reducing uncertainty inherent in the investment decision making process. It is proposed that the two most important profitability financial ratios in relation to investment decisions are the return on equity and the return on assets respectively. In order to exploit their use as criteria for risk measurement and uncertainty reduction, a stochastic formulation is adopted in which these ratios are expressed in probabilistic terms. A density function to describe their behaviour is derived; it is found that density distribution analysis for both ratios indicate that the Weibull distribution apart from being the most flexible and adaptable model of all those considered, provides the best overall fit to the data. It is accordingly used in the latter part of the research for evaluating industrial sector and company investment risk.

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