A bibliographic overview of financial engineering in the emerging financial market
JR Jena, SK Biswal, AK Shrivastava… - International Journal of …, 2023 - Springer
Financial engineering is constantly changing and encountering new problems. Financial
engineering helps us detect emerging trends and challenges, such as fintech's effect on …
engineering helps us detect emerging trends and challenges, such as fintech's effect on …
Corporate bankruptcy prediction using machine learning methodologies with a focus on sequential data
We examine whether corporate bankruptcy predictions can be improved by utilizing the
recurrent neural network (RNN) and long short-term memory (LSTM) algorithms, which can …
recurrent neural network (RNN) and long short-term memory (LSTM) algorithms, which can …
[HTML][HTML] Machine learning for bankruptcy prediction in the American stock market: dataset and benchmarks
Predicting corporate bankruptcy is one of the fundamental tasks in credit risk assessment. In
particular, since the 2007/2008 financial crisis, it has become a priority for most financial …
particular, since the 2007/2008 financial crisis, it has become a priority for most financial …
[HTML][HTML] A review of the limitations of financial failure prediction research: Revisión de las limitaciones de la investigación sobre predicción de quiebras financieras
EK Laitinen, N Muñoz-Izquierdo - Revista de Contabilidad-Spanish …, 2023 - revistas.um.es
El objetivo de este artículo es evaluar críticamente los principales puntos débiles asociados
a las limitaciones de los estudios de investigación sobre predicción de quiebras financieras …
a las limitaciones de los estudios de investigación sobre predicción de quiebras financieras …
Big data analytics for default prediction using graph theory
With the unprecedented increase in data all over the world, financial sector such as
companies and industries try to remain competitive by transforming themselves into data …
companies and industries try to remain competitive by transforming themselves into data …
[HTML][HTML] Measuring financial soundness around the world: A machine learning approach
We use a fully data-driven approach and information provided by the IMF's financial
soundness indicators to measure the condition of a country's financial system around the …
soundness indicators to measure the condition of a country's financial system around the …
[HTML][HTML] Corporate governance and financial distress: lessons learned from an unconventional approach
Using a and a unique set of Italian non-listed Unlikely to Pay (UTP) positions, that consist in
the phase that precedes the insolvency but where it is still possible for the company to …
the phase that precedes the insolvency but where it is still possible for the company to …
[HTML][HTML] Determining of the Bankrupt Contingency as the Level Estimation Method of Western Ukraine Gas Distribution Enterprises' Competence Capacity
The functioning of Ukrainian national gas sector is directly dependent on the processes of
fuel and energy resources consumption and trends in domestic and foreign markets …
fuel and energy resources consumption and trends in domestic and foreign markets …
A machine learning-based early warning system for the housing and stock markets
This study analyzes the relationship between the housing and stock markets, focusing on
housing market bubbles. Stock market dynamics generally have a more significant impact …
housing market bubbles. Stock market dynamics generally have a more significant impact …
[HTML][HTML] The application of structural and machine learning models to predict the default risk of listed companies in the Iranian capital market
Inattention of economic policymakers to default risk and making inappropriate decisions
related to this risk in the banking system and financial institutions can have many economic …
related to this risk in the banking system and financial institutions can have many economic …