Cantitate/Preț
Produs
Total produse
Vezi coșul
Machine Learning Approaches in Financial Analytics de Leandros A. Maglaras

Machine Learning Approaches in Financial Analytics: Intelligent Systems Reference Library, cartea 254

Editat de Leandros A. Maglaras, Sonali Das, Naliniprava Tripathy, Srikanta Patnaik
en Limba Engleză Hardback – 18 sep 2024
This book addresses the growing need for a comprehensive guide to the application of machine learning in financial analytics. It offers a valuable resource for both beginners and experienced professionals in finance and data science by covering the theoretical foundations, practical implementations, ethical considerations, and future trends in the field. It bridges the gap between theory and practice, providing readers with the tools and knowledge they need to leverage the power of machine learning in the financial sector responsibly.
Citește tot Restrânge

Din seria Intelligent Systems Reference Library

Preț: 111947 lei

Preț vechi: 136520 lei
-18% Nou

Puncte Express: 1679
Preț estimativ în valută:
21422€ • 22440$ • 17753£

Carte tipărită la comandă

Livrare economică 08-22 aprilie

 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă
Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783031610363
ISBN-10: 3031610369
Ilustrații: X, 390 p.
Dimensiuni: 155 x 235 mm
Ediția:2024
Editura: Springer Nature Switzerland
Colecția Springer
Seria Intelligent Systems Reference Library

Locul publicării:Cham, Switzerland

Cuprins

.- 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.

Textul de pe ultima copertă

This book addresses the growing need for a comprehensive guide to the application of machine learning in financial analytics. It offers a valuable resource for both beginners and experienced professionals in finance and data science by covering the theoretical foundations, practical implementations, ethical considerations, and future trends in the field. It bridges the gap between theory and practice, providing readers with the tools and knowledge they need to leverage the power of machine learning in the financial sector responsibly.

Caracteristici

Covers all aspects of financial markets along with effective exploration and exploitation of machine learning techniques Presents recent research on machine learning approaches in Financial Analytics Provides theoretical concepts, empirical analysis, and applications