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Machine Learning Approaches in Financial Analytics

  • Book
  • © 2024

Overview

Editors:
  1. Leandros A. Maglaras

    1. Edinburgh Napier University, Edinburgh, UK

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    You can also search for this editor in PubMed   Google Scholar

  2. Sonali Das

    1. Department of Business Management, University of Pretoria, Hatfield, South Africa

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    You can also search for this editor in PubMed   Google Scholar

  3. Naliniprava Tripathy

    1. Indian Institute of Management, Shillong, India

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  4. Srikanta Patnaik

    1. Institute of Management and Technology, Bhubaneswar, India

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  • 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

Part of the book series: Intelligent Systems Reference Library (ISRL, volume 254)

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About this book

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 (22 chapters)

  1. Front Matter

    Pages i-xx
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  2. Foundations

    1. Front Matter

      Pages 1-1
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    2. Introduction to Optimal Execution

      • Makoto Shimoshimizu
      Pages 3-50

  3. Tools and Techniques

    1. Front Matter

      Pages 51-51
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    2. Python Stack for Design and Visualization in Financial Engineering

      • Jayanth R. Varma, Vineet Virmani
      Pages 53-67

    3. Neurodynamic Approaches to Cardinality-Constrained Portfolio Optimization

      • Man-Fai Leung, Jun Wang
      Pages 69-96

    4. Fully Homomorphic Encrypted Wavelet Neural Network for Privacy-Preserving Bankruptcy Prediction in Banks

      • Syed Imtiaz Ahamed, Vadlamani Ravi, Pranay Gopi
      Pages 97-115

    5. Tools and Measurement Criteria of Ethical Finance Through Computational Finance

      • Marco Piccolo, Francesco Vigliarolo
      Pages 117-131

    6. Data Mining Techniques for Predicting the Non-performing Assets (NPA) of Banks in India

      • Gaurav Kumar, Arun Kumar Misra
      Pages 133-150

    7. Multiobjective Optimization of Mean–Variance-Downside-Risk Portfolio Selection Models

      • Georgios Mamanis, Eftychia Kostarelou
      Pages 151-175

  4. Risk Assessment and Ethical Considerations

    1. Front Matter

      Pages 177-177
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    2. Bankruptcy Forecasting of Indian Manufacturing Companies Post the Insolvency and Bankruptcy Code 2016 Using Machine Learning Techniques

      • Simrat Kaur, Anjali Munde
      Pages 179-189

    3. Ensemble Deep Reinforcement Learning for Financial Trading

      • Mendhikar Vishal, Vadlamani Ravi, Ramanuj Lal
      Pages 191-207

  5. Real-World Applications

    1. Front Matter

      Pages 209-209
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    2. Bibliometric Analysis of Digital Financial Reporting

      • Neha Puri, Vikas Garg
      Pages 211-227

    3. The Quest for Financing Environmental Sustainability in Emerging Nations: Can Internet Access and Financial Technology Be Crucial?

      • Ekundayo Peter Mesagan, Precious Muhammed Emmanuel, Mohammed Bashir Salaudeen
      Pages 229-245

    4. A Comprehensive Review of Bitcoin’s Energy Consumption and Its Environmental Implications

      • Sidhartha Harichandan, Sanjay Kumar Kar, Abhishek Kumar
      Pages 247-265

    5. Emerging Economies: Volatility Prediction in the Metal Futures Markets Using GARCH Model

      • Ravi Kumar, Babli Dhiman, Naliniprava Tripathy
      Pages 267-278

    6. Constructing a Broad View of Tax Compliance Intentions Based on Big Data

      • Mekar Satria Utama, Solimun, Adji Achmad Rinaldo Fernandes
      Pages 279-305

    7. Influence of Firm-Specific Variables on Capital Structure Decisions: An Evidence from the Fintech Industry

      • Suzan Dsouza, Ajay Kumar Jain
      Pages 307-323
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Editors and Affiliations

  • Edinburgh Napier University, Edinburgh, UK

    Leandros A. Maglaras

  • Department of Business Management, University of Pretoria, Hatfield, South Africa

    Sonali Das

  • Indian Institute of Management, Shillong, India

    Naliniprava Tripathy

  • Institute of Management and Technology, Bhubaneswar, India

    Srikanta Patnaik

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