Novel Financial Applications of Machine Learning and Deep Learning: Algorithms, Product Modeling, and Applications - Softcover

Softcover

ISBN 10: 3031185536 ISBN 13: 9783031185533

Publisher: Springer, 2023

Synopsis

This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study.

The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice.

The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.

Edition details

• Publisher: Springer
• Publication date: 2023
• Language: English
• ISBN 10: 3031185536
• ISBN 13: 9783031185533
• Binding: Paperback
• Number of pages: 248
• Editor: Abedin Mohammad Zoynul, Hajek Petr