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1

TEPLOTNÉ DERIVÁTY CHARAKTERU OPCIÍ AKO NÁSTROJE NA ELIMINÁCIU DÔSLEDKOV POVETERNOSTNÉHO RIZIKA

100%
Tumpach M., Juhászová Z.
Ekonomický časopis (Journal of Economics)
|
2007
|
vol. 55
|
issue 2
125-144
EN
The derivative instruments are widely accepted tools in hedging against the market risks. However, they can be used for elimination of impacts of the non-market risks as well. Weather derivatives, like other Arrow-Debreu instruments (Jaimungal, 2004) provide specific payouts in the case of occurrence of the weather risk events (e.g. temperature and precipitations). Dissimilarity of such risks even in very close areas and inability to settle them directly by delivery of underlying, makes the effective application of such derivatives dependent both on of the analytical model and on availability of the relevant empirical data as well. This paper is focused on certain issues in application of option-based temperature derivatives.
2

RELEVANTNOSŤ NÁRODNÉHO PODNIKOVÉHO FINANČNÉHO VÝKAZNÍCTVA V SLOVENSKEJ REPUBLIKE Z POHĽADU VERITEĽOV AKO NEPRIVILEGOVANÝCH POUŽÍVATEĽOV

81%
Tumpach M., Manová E., Meluchová J.
Ekonomický časopis (Journal of Economics)
|
2014
|
vol. 62
|
issue 5
495 – 507
EN
There are different groups of external users of business information, whose needs are more often in mutual contradiction. As a result, data about the business transactions, events and conditions need to be presented in the form of general purpose financial statements. Since 1946 the accounting rules in Slovakia has been prescribed by the government in a very detailed way. Because the government itself is one of the parties interested in such information, we have been examining whether the current system of business financial reporting could be relevant also for parties, which have not such privileged status. Our study has been focused on the assessment of the impact of available financial reporting data on the decisions taken by the creditors.
3

PREDICTION OF THE BANKRUPTCY OF SLOVAK COMPANIES USING NEURAL NETWORKS WITH SMOTE

71%
Tumpach M., Surovičová A., Juhászová Z., Marci A., Kubaščíková Z.
Ekonomický časopis (Journal of Economics)
|
2020
|
vol. 68
|
issue 10
1021 – 1039
EN
Although the bankruptcy prediction models can be a stabilizing element on both macro and microeconomic levels, they are rather a domain of academic research than an instrument, widely applied in a business practice. It is especially true if the models are reflecting the conditions of countries of their origin, rather than countries of their intended uses. Besides, few of the models contain inherent flaws, including the absence of a methodical approach addressing this problem of the severely imbalanced representation of bankrupt companies in financial datasets. The article is focused on the use of oversampling with SMOTE (Synthetic Minority Oversampling Technique) algorithm under the condition of extremely imbalanced data sets of Slovak companies. While the model does not provide a single answer in many (if not most) of the situations, it still could be used for the selection of companies for which the more detailed (and expensive) analysis is not required.
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