Publications by authors named "Manuel Angel Fernandez"

Article Synopsis
  • Capital flows are significant in the international monetary system, offering benefits and risks that can make open economies vulnerable.
  • Existing models for predicting sudden stop events in capital flows are limited, primarily focused on emerging countries, and require further research for improved accuracy.
  • This paper introduces a new prediction model that applies to both emerging and developed countries, using decision trees to analyze data from 103 countries, aiming to enhance macroeconomic policy and global financial stability against sudden capital flow stops.
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The study of financial distress has been the focus of financial research in recent decades and has led to the development of models for predicting financial distress that help assess the financial situation and the risks faced by companies. These models have focused exclusively on industrial and financial companies. However, a specific model that reflects the special characteristics of the football industry has not yet been created.

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Article Synopsis
  • The article DOI: 10.1371/journal.pone.0166693 has been corrected to address previous errors or inaccuracies.
  • This correction aims to clarify the research findings and uphold the integrity of the published work.
  • Readers are encouraged to review the corrected version for accurate information.
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The recent world financial crisis has increased the number of bankruptcies in numerous countries and has resulted in a new area of research which responds to the need to predict this phenomenon, not only at the level of individual countries, but also at a global level, offering explanations of the common characteristics shared by the affected companies. Nevertheless, few studies focus on the prediction of bankruptcies globally. In order to compensate for this lack of empirical literature, this study has used a methodological framework of logistic regression to construct predictive bankruptcy models for Asia, Europe and America, and other global models for the whole world.

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