In the article the author has presented the methodology of assessment of market risk connected with investing in all sorts of financial instruments such as: shares, bonds and other derivatives, e.g. RiskGrade (RG). The measure has been introduced by RiskMetrics. The article presents the application of RiskGrades methodology while choosing the optimum investment portfolio for a Polish investor who invests in shares in the Warsaw Stock Exchange. Moreover, some other risk measures have been discussed which describe the efficiency of the optimum financial portfolio.
There is a growing demand for models which enable to measure and assess the risk in long-term horizons (sometimes more than 2 years). The practical demand for such models is required by the institutions which manage the investments and retirement funds. In the paper the theoretical aspects of risk assessment methodology with the use of Value at Risk (VaR) were presented. In this method in order to estimate the long-term VaR limits the hybrid model which is the optimum mixture of random walk and mean reversion was used. The application of the presented methodology was exemplified by the estimation of long-term predictions for VaR limits for stock prices.
In the article there were presented the traditional discriminant methods that are commonly used in the world in the context of a risk analysis of business bankruptcy. There was done the characteristics of the world concept in this field, as well as those developed in the domestic market. A survey and an assessmentof the models effectiveness was conducted exemplified by entities operating in the Polish conditions.
The paper presents examples of gas prices modeling in Poland by means of the VAR model (AutoRegression Vector Model). For comparison, the predictions are made for the models estimated by different variations of the generalized least squares method. The analysis is based on gas prices set by the Carpathian Gas Company after 2000 for the tariffs applied for individual customers. Thus, value forecasts were presented for this type of energy for the “ordinary” customers in the light of the existing regulations.
In this paper, we present the ranking of living standards in Poland in a cross-section of counties as constructed by using selected methods of linear ordering. The analysis was of a dynamic character and the study involved data from the years 2003 to 2012. The positions of the counties in the annual section rankings were distinguished. Additionally, we assessed the trends of the synthetic measure of the standard of living for each country between 2003-2012. An important issue when creating rankings was determining the spatial extent of the study. For example, when examining the standard of living in the counties of the Podkarpackie province, should not the counties in other provinces be taken into account as a reference point? In the case of multivariate analysis, the interaction of objects can indeed be changed by an extended context analysis. Therefore, in this paper, comparisons made of the rankings compliance obtained in the analysis were narrowed down to a single province with the results of the analyses being carried out in the broader context of all the counties in Poland. As with today’s data processing, it is not important whether the population of a few dozen or a few hundred objects is analysed. The conclusion from the conducted considerations is that one should always strive for the widest possible context for the research. We then propose a modification of the linear ordering method that takes the spatial relationships between the districts into account. Two rankings were presented: one where the neighbourhood matrix between the counties was applied and one where the length of the shared border was considered. In the discussion of the results, we highlighted the fact that spatial relationships should be determined separately for each diagnostic variable. In this way, the directions for further research were determined.
PL
W pracy przedstawiono ranking poziomu życia mieszkańców Polski w przekroju powiatów, skonstruowany za pomocą wybranych metod porządkowania liniowego. Analiza miała charakter dynamiczny, badaniem objęto dane z lat 2003-2012. Wyodrębniono pozycje powiatów w rankingach przekrojowych (dla poszczególnych lat), oceniono także kierunki zmian syntetycznej miary poziomu życia w latach 2003-2012 dla każdego powiatu. Ważną kwestią podczas tworzenia rankingów jest określenie zakresu przestrzennego prowadzonych badań. Przykładowo, czy badając poziom życia w powiatach województwa podkarpackiego nie należałoby, jako punktu odniesienia, przyjąć także powiatów z innych województw? Wszak w przypadku analizy wielowymiarowej wzajemne relacje obiektów mogą się zmieniać przy rozszerzonym kontekście analizy. Dlatego też w pracy dokonano porównań zgodności rankingów uzyskanych przy analizie zawężonej tylko do jednego województwa z wynikami analiz prowadzonych w szerszym kontekście – wszystkich powiatów w Polsce. Następnie zaproponowano modyfikację metody porządkowania liniowego, w której uwzględnione zostały przestrzenne relacje pomiędzy powiatami. W omówieniu uzyskanych wyników zwrócono uwagę na fakt, iż relacje przestrzenne powinny być określane odrębnie dla każdej zmiennej diagnostycznej. W ten sposób określono kierunki dalszych badań.
The article focuses on assessing the effectiveness of a non-statistical approach to bankruptcy modelling in enterprises operating in the logistics sector. In order to describe the issue more comprehensively, the aforementioned prediction of the possible negative results of business operations was carried out for companies functioning in the Polish region of Podkarpacie, and in Slovakia. The bankruptcy predictors selected for the assessment of companies operating in the logistics sector included 28 financial indicators characterizing these enterprises in terms of their financial standing and management effectiveness. The purpose of the study was to identify factors (models) describing the bankruptcy risk in enterprises in the context of their forecasting effectiveness in a one-year and two-year time horizon. In order to assess their practical applicability the models were carefully analysed and validated. The usefulness of the models was assessed in terms of their classification properties, and the capacity to accurately identify enterprises at risk of bankruptcy and healthy companies as well as proper calibration of the models to the data from training sample sets.
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