Machine Learning Approaches in Financial Analytics
| 企業作者: | |
|---|---|
| 其他作者: | , , , |
| 總結: | XX, 483 p. 105 illus., 88 illus. in color. text |
| 語言: | 英语 |
| 出版: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
|
| 版: | 1st ed. 2024. |
| 叢編: | Intelligent Systems Reference Library,
254 |
| 主題: | |
| 在線閱讀: | https://doi.org/10.1007/978-3-031-61037-0 |
| 格式: | 電子 圖書 |
書本目錄:
- -- Part I: Foundations.
- Chapter 1: Introduction to Optimal Execution.
- Part II: Tools and techniques.
- Chapter 2: Python Stack for Design and Visualization in Financial Engineering.
- Chapter 3: Neurodynamic approaches to cardinality-constrained portfolio optimization.
- Chapter 4: Fully Homomorphic Encrypted Wavelet Neural Network for Privacy-Preserving Bankruptcy Prediction in Banks.
- Chapter 5: Tools and Measurement Criteria of Ethical Finance through Computational Finance.
- Chapter 6: Data Mining Techniques for Predicting the Non-Performing Assets (NPA) of Banks in India.
- Chapter 7: Multiobjective optimization of mean-variance-downside-risk portfolio selection models.
- Part III: Risk assessment and ethical considerations.
- Chapter 8: Bankruptcy Forecasting Of Indian Manufacturing Companies Post Ibc Using Machine Learning Techniques.
- Chapter 9: Ensemble Deep Reinforcement Learning for Financial Trading. Part IV: Real-world Applications.
- Chapter 10: Bibliometric Analysis of Digital Financial Reporting.
- Chapter 11: The Quest for Financing Environmental Sustainability in Emerging Nations: Can Internet Access and Financial Technology be Crucial?
- Chapter 12: A comprehensive review of Bitcoin’s energy consumption and its environmental implications, etc.