Deep learning for financial applications: A survey
Computational intelligence in finance has been a very popular topic for both academia and
financial industry in the last few decades. Numerous studies have been published resulting …
financial industry in the last few decades. Numerous studies have been published resulting …
Statistical and machine learning models in credit scoring: A systematic literature survey
X Dastile, T Celik, M Potsane - Applied Soft Computing, 2020 - Elsevier
In practice, as a well-known statistical method, the logistic regression model is used to
evaluate the credit-worthiness of borrowers due to its simplicity and transparency in …
evaluate the credit-worthiness of borrowers due to its simplicity and transparency in …
An innovative neural network approach for stock market prediction
This paper aims to develop an innovative neural network approach to achieve better stock
market predictions. Data were obtained from the live stock market for real-time and off-line …
market predictions. Data were obtained from the live stock market for real-time and off-line …
Bankruptcy prediction using imaged financial ratios and convolutional neural networks
T Hosaka - Expert systems with applications, 2019 - Elsevier
Convolutional neural networks are being applied to identification problems in a variety of
fields, and in some areas are showing higher discrimination accuracies than conventional …
fields, and in some areas are showing higher discrimination accuracies than conventional …
Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting
The paper examines the potential of deep learning to support decisions in financial risk
management. We develop a deep learning model for predicting whether individual spread …
management. We develop a deep learning model for predicting whether individual spread …
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 …
A new CNN-based model for financial time series: TAIEX and FTSE stocks forecasting
Financial time series forecasting has been becoming one of the most attractive topics in so
many aspects owing to its broad implementation areas and substantial impact. Because of …
many aspects owing to its broad implementation areas and substantial impact. Because of …
Advancing financial resilience: A systematic review of default prediction models and future directions in credit risk management
This research presents a systematic review of a substantial body of high-quality research
articles on Default Prediction Models published from 2015 to 2024. It is a comprehensive …
articles on Default Prediction Models published from 2015 to 2024. It is a comprehensive …
Comparing the performance of deep learning methods to predict companies' financial failure
One of the most crucial problems in the field of business is financial forecasting. Many
companies are interested in forecasting their incoming financial status in order to adapt to …
companies are interested in forecasting their incoming financial status in order to adapt to …
Corporate failure prediction: An evaluation of deep learning vs discrete hazard models
N Alam, J Gao, S Jones - … of International Financial Markets, Institutions and …, 2021 - Elsevier
In recent years, deep learning has emerged as a dominant machine learning method used
in a variety of applications, including robotics (such as self-driving cars), speech recognition …
in a variety of applications, including robotics (such as self-driving cars), speech recognition …