scholarly journals Risk Analysis in Project Evaluation

This final chapter is devoted to the analysis of the risks associated with foreign direct investments, namely business (commercial) risk, political risk, and currency exchange rate risk. Each risk factor is considered as a separate evaluation criterion. That is, an investment project may be rejected due to having a high level of any one of these three risk factors. For instance, a profitable investment proposal may not have a significant business risk but might have a high level of political risk requiring its rejection. Risk analysis is conducted only if a foreign investment project is profitable from the viewpoint of the parent company. Otherwise, there is no need for a risk analysis since a direct investment project that does not create profit for the parent company would be rejected anyway.

2019 ◽  
pp. 23-25
Author(s):  
Olha OHDANSKA ◽  
Viktoriia MAKARENKO

Introduction. It has been indicated that high level of debt burden in Ukraine in the conditions of insufficient budgetary funds and volatile economic and political situation exerts negative impact both upon the economy of the country and its every sector. This actualizes the research on the state and dynamics of the public debt within the context of achieving stabilization of economic processes, particularly Ukraine’s integration into global economic environment. The purpose of the paper is the analysis of the state and dynamics of the public debt of Ukraine in the context of solving the problems of its servicing. Results. It has been established that the major trend in Ukraine is a rapid increase in the total public debt which testifies to the instability and crisis events in the country’s economy. It has been defined that public and publicly guaranteed debt of Ukraine in Hryvnia equivalent is growing from year to year (increased by 106 times in 2018 as compared to 1996), while major periods of accelerated growth of public debt occurred during the periods of economic and financial crises (2008-2010 and 2014-2018). It has been determined that in 1999 and during 2014-2018 public and publicly guaranteed debt exceeded the critical limit of 60%, which asserts the presence of crisis events in the economy. It has been substantiated that there exists a close correlation between the public debt and change in currency exchange rate (correlation coefficient of 0,99 – very high bond strength on the Chaddock scale). It is revealed that the public debt-to-GDP ratio reaches maximum levels in the periods of economic crises and decreases in the periods of economic upturn. Conclusion. Hence, the issue of the debt-related security in Ukraine is topical and affects the economic situation. Prospects of further research in this area lie with solving the issues of managing public debt through changing the direction of the economic policy of the country as well as the scientific substantiation of managing public debt employing advanced economic instruments and progressive global practices.


Author(s):  
Zahidur Rahman ◽  
Jannatul Ferdous Bristy

In the endeavor of conquering the worlds consumers, multinational companies face enormous risks. Such risks may arise from different political, economic, and financial factors. These factors are commonly referred to country risk as a whole. Focusing Bangladesh in this regard, objective of this study is to find out the level of country risk in terms of political, economic, and financial riskiness. Analysis of country risk has been done using an internationally recognized methodology named International Country Risk Guide (ICRG). For political risk analysis, primary data has been collected from 20 journalists, bureaucrats and policy makers, business persons, corporate professionals, and academicians with a structured closed-ended questionnaire. Results indicate that Bangladesh is in high risk position in terms of political risk, low risk position in terms of economic risk and very low risk position in terms of financial risk. Compositely, Bangladesh has been found to be a moderately risky country for investment.


1992 ◽  
Vol 18 (3) ◽  
pp. 167-178 ◽  
Author(s):  
J.M. Chermak
Keyword(s):  

Author(s):  
Ruofan Liao ◽  
Paravee Maneejuk ◽  
Songsak Sriboonchitta

In the past, in many areas, the best prediction models were linear and nonlinear parametric models. In the last decade, in many application areas, deep learning has shown to lead to more accurate predictions than the parametric models. Deep learning-based predictions are reasonably accurate, but not perfect. How can we achieve better accuracy? To achieve this objective, we propose to combine neural networks with parametric model: namely, to train neural networks not on the original data, but on the differences between the actual data and the predictions of the parametric model. On the example of predicting currency exchange rate, we show that this idea indeed leads to more accurate predictions.


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