Novel financial applications of machine learning and deep learning : algorithms, product modeling, and applications / Mohammad Zoynul Abedin, Petr Hajek, editors.
Abedin, Mohammad Zoynul, editor.; Hajek, Petr, editor.
2023
HG173 .N68 2023
Available Online

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Title
Novel financial applications of machine learning and deep learning : algorithms, product modeling, and applications / Mohammad Zoynul Abedin, Petr Hajek, editors.
ISBN
9783031185526 electronic book
3031185528 electronic book
303118551X
9783031185519
DOI
https://doi.org/10.1007/978-3-031-18552-6
Published
Cham, Switzerland : Springer, [2023]
Language
English
Description
1 online resource
Item Number
10.1007/978-3-031-18552-6 doi
Call Number
HG173 .N68 2023
Dewey Decimal Classification
332.0285631
Summary
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.
Access Note
Access limited to authorized users.
Source of Description
Description based on online resource; title from digital title page (viewed on April 19, 2023).
Added Author
Abedin, Mohammad Zoynul, editor.
Hajek, Petr, editor.
Series
International series in operations research & management science ; 336. 2214-7934
Available in Other Form
Print version: 9783031185519
Novel financial applications of machine learning and deep learning
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Part 1: Recent Developments in FinTech
1. FinTech Risk Management and Monitoring
2. Digital Transformation of Supply Chain with Supportive Culture in Blockchain Environment
3. Integration of Artificial Intelligence Technology in Management Accounting Information System - An Empirical Study
4. The Impact of Big Data on Accounting Practices: Empirical Evidence from Africa
Part 2: Financial Risk Prediction using Machine Learning
5. Using Outlier Modification Rule for Improvement of the Performance of Classification Algorithms in the Case of Financial Data
6. Default Risk Prediction Based on Support Vector Machine and Logit Support Vector Machine
7. Predicting Corporate Failure using Ensemble Extreme Learning Machine
8. Assessing and Predicting Small Enterprises Credit Ratings: A Multicriteria Approach
Part 3: Financial Time-Series Forecasting
9. An Ensemble LGBM (Light Gradient Boosting Machine) Approach for Crude Oil Price Prediction
10. Model Development for Predicting the Crude Oil Price: Comparative Evaluation of Ensemble and Machine Learning Methods
part 4: Emerging Technologies in Financial Education and Healthcare
11. Discovering the Role of M-learning among Finance Students: The Future of Online Education
12. Exploring the Role of Mobile Technologies in Higher Education: The Impact of Online Teaching on Traditional Learning.-13. Knowledge Mining from Health Data: Application of Feature Selection Approaches.

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