The aim of this article is to analyze and evaluate the usability of discriminant models in predicting bankruptcy for companies listed on NewConnect. This market was established in 2007 and operates as an alternative trading system next to Warsaw Stock Exchange S.A., which in practice means that its regulatory regime in relation to issuers and listed companies is not as strict as the one applicable to the main market, therefore shares of small and medium-size businesses, including start-ups, can be listed on NewConnect. In this paper, discriminant models are used to analyse the financial situation of four companies removed from trading on NewConnect due to bankruptcy, Perfect Line S.A., Promet S.A., InwazjaPC S.A. and Budostal-5 S.A. The analysis is based on three models: Altman's model for emerging markets, as well as two models of the highest predictive ability according to P. Antonowicz's research, Z7INEPAN model developed in the Polish Academy of Sciences and E. Mączyńska's model, developed by Polish scientists and adapted to the Polish economy. The results confirm that these models are a valuable tool in assessing the financial condition of enterprises and allow for bankruptcy forecasting. Their application to companies listed on NewConnect, however, may be limited due to the specific profile of these entities as most of these enterprises are in fact newly formed and therefore the existing empirical data may prove insufficient.
The aim of this article is to present the principles of the Norwegian pension scheme, which is being reorganized since 1 January 2011 with regard to the acquisition and determination of pension rights and the possibility of combining work with pension in the light of demographic challenges. The phenomenon of an aging population (which is the result of, i.a., rising longevity and declining fertility rate) and the migration processes have become a serious threat to public pension systems of most countries. For this reason, they decided to implement radical reforms in the retirement security of citizens. Among these countries was also Norway, despite the fact that its liberal immigration policy, very high fertility rate and, primarily, the funds collected in the state pension fund seem to protect its pension system, as well as public finances, against the collapse. The choice of the subject was influenced by the growing popularity of Norway as a destination for employment and by the considerable complexity of the Norwegian pension scheme, especially in the ongoing transition period in which the old and new regulations operate simultaneously. This paper is based on the materials collected in the branches of the Norwegian Labour and Welfare Administration (NAV) in Stavanger, statistical data and analyses compiled by Statistics Norway (SSB), as well as the information published by NAV and the Norwegian Ministry of Labour and Social Affairs.
The SME sector has been attracting attention of Polish and European public authorities for many years. In 2013 Polish government implemented the guarantees and sureties programmes designated particularly for the SMEs. The primary goal of these programmes is to improve the access to external financial sources for entrepreneurs, especially those who belong to the SMEs sector. The purpose of this article is to present those recent activities and, furthermore, to provide their preliminary assessment. The article is based on literature studies as well as on the analysis of the primary documents and operational framework of the selected programmes.
The aim of the paper is to evaluate the effects of the intervention of the Chinese government undertaken during the 2015–2016 crisis on the Shanghai Stock Exchange (SSI). The following research hypothesis was set up: in the long run, both the initial efforts of the Chinese authorities to drive individual investors to invest in stock exchanges along with the interventions launched by the government to stop the market falls were not relevant to stock valuation. The study results have proven that in the analysed time monetary authorities, as well as government and regulatory bodies, generated many decisions and announcements which were expected to influence the behaviour of the stock exchange investors. In short term it created artificially market anomalies, observed between the Q4 2014 and Q1 2016. The interventions interfered with the long term growth trend of SSI index, however did not shift this trend and after interventions ended it was apparently ongoing and not disturbed until 2017.
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