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  • Machine Learning Approaches in Financial Analytics
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      • Publisher's listprice EUR 213.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        88 752 Ft (84 526 Ft + 5% VAT)
      • Discount 20% (cc. 17 750 Ft off)
      • Discounted price 71 002 Ft (67 621 Ft + 5% VAT)

    88 752 Ft

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    Product details:

    • Edition number 2024
    • Publisher Springer Nature Switzerland
    • Date of Publication 28 August 2024
    • Number of Volumes 1 pieces, Book

    • ISBN 9783031610363
    • Binding Hardback
    • No. of pages483 pages
    • Size 235x155 mm
    • Language English
    • Illustrations XX, 483 p. 105 illus., 88 illus. in color. Illustrations, black & white
    • 591

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    Long description:

    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.

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    Table of Contents:

    .- 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.

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