Machine Learning Approaches in Financial Analytics
| 団体著者: | |
|---|---|
| その他の著者: | , , , |
| 要約: | XX, 483 p. 105 illus., 88 illus. in color. text |
| 言語: | 英語 |
| 出版事項: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| 版: | 1st ed. 2024. |
| シリーズ: | Intelligent Systems Reference Library,
254 |
| 主題: | |
| オンライン･アクセス: | https://doi.org/10.1007/978-3-031-61037-0 |
| フォーマット: | 電子媒体 図書 |
目次:
- -- 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.