Economic Archive

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  FINANCE AND ECONOMIC ACCOUNTING – FACULTIES, SCIENTIFIC RESEARCH AND A 70-YEAR TRADITION

  At a solemn joint session, the Faculty Councils of the Faculty of Finance and the Faculty of Economic Accounting at the D.A. Tsenov Academy of Economics celebrated the 70th anniversary of their establishment. By Decree No. 289 of August 20, 1953, effective from September 1, 1953, the Presidium of the National Assembly redistributed and regrouped ... At a solemn joint session, the Faculty Councils of the Faculty of Finance and the Faculty of Economic Accounting at the D.A. Tsenov Academy of Economics celebrated the 70th anniversary of their establishment. By Decree No. 289 of August 20, 1953, effective from September 1, 1953, the Presidium of the National Assembly redistributed and regrouped the specialties at the Higher Financial and Economic Institute in Svishtov, into two faculties - Financial-Statistical and Accounting. Over the years, the faculties have changed their names several times - Financial-Statistical (1953), Financial-Economic (1973), and the Faculty of Finance (1993), and respectively - Accounting (1953), Accounting-Economic (1973), and the Faculty of Economic Accounting (1993). The purpose of this article is to present the results of celebrating the 70th anniversary of the Faculty of Finance and the Faculty of Economic Accounting at the D.A. Tsenov Academy of Economics through the organization and conduct of a prestigious international scientific forum.

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  DISCRIMINATIVE ABILITY IN ESTIMATING PROBABILITY OF DEFAULT WITH CERTAIN MACHINE LEARNING ALGORITHMS

  The article highlights the importance and added value of some machine learning algorithms in assessing default probability. The results of the research highlight the discriminative ability added to many other essential aspects of machine learning in assessing credit risk. These aspects can be identified as specific opportunities and challenges. As ... The article highlights the importance and added value of some machine learning algorithms in assessing default probability. The results of the research highlight the discriminative ability added to many other essential aspects of machine learning in assessing credit risk. These aspects can be identified as specific opportunities and challenges. As for the discriminative ability regarding the analysed sample, the results prove the superiority of machine learning over the traditionally established and known models. For individual business organizations with exposures to credit risk, machine learning could contribute to reducing the credit losses with larger volumes of business transactions.

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  ON SOCIAL REALITY, THEORY AND ECONOMICS EDUCATION

  The article is an attempt to defend the based on the Seneca’s maxim thesis that the present is to fix the past and foresee the future. Employing a broader socio-economic paradigm, it analyses the essence of societal reality and economic reality in particular; the dominance of economic considerations surpassed by time and the necessity for a more ... The article is an attempt to defend the based on the Seneca’s maxim thesis that the present is to fix the past and foresee the future. Employing a broader socio-economic paradigm, it analyses the essence of societal reality and economic reality in particular; the dominance of economic considerations surpassed by time and the necessity for a more comprehensive education in economics. Finally, the solution to the problem is proposed through the enhancement of traditional economic scientific and educational disciplines with inter-disciplinary knowledge.