TITLE:
The Logit Model: A Prediction of Future Economic Events
AUTHORS:
Gretta Saab, Tony Jamhour, Marie-Michelle El-Hayek, Hala Khayr Yaacoub
KEYWORDS:
Logit Mode, Early Warning System, Logistic Regression
JOURNAL NAME:
Journal of Mathematical Finance,
Vol.14 No.1,
February
28,
2024
ABSTRACT: Financial
crises are recurrent events with profound economic and social implications.
Accurately predicting these crises is of paramount importance for policymakers,
financial institutions, and investors. This abstract provides an overview of a
study that explores the utility of Logit models in predicting financial crises
and their ability to provide insights into the factors contributing to these
crises and the value of Logit models in predicting financial crises and gaining
insights into their underlying drivers. Such predictive models can enhance risk
management strategies and help prevent or mitigate the devastating consequences
of financial crises. Future research could focus on refining the model by
incorporating additional data sources and improving predictive accuracy
further.