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Feedforward Neural Networks

In: Machine Learning in Finance

Author

Listed:
  • Matthew F. Dixon

    (Illinois Institute of Technology, Department of Applied Mathematics)

  • Igor Halperin

    (New York University, Tandon School of Engineering)

  • Paul Bilokon

    (Imperial College London, Department of Mathematics)

Abstract

This chapter provides a more in-depth description of supervised learning, deep learning, and neural networks—presenting the foundational mathematical and statistical learning concepts and explaining how they relate to real-world examples in trading, risk management, and investment management. These applications present challenges for forecasting and model design and are presented as a reoccurring theme throughout the book. This chapter moves towards a more engineering style exposition of neural networks, applying concepts in the previous chapters to elucidate various model design choices.

Suggested Citation

  • Matthew F. Dixon & Igor Halperin & Paul Bilokon, 2020. "Feedforward Neural Networks," Springer Books, in: Machine Learning in Finance, chapter 0, pages 111-166, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41068-1_4
    DOI: 10.1007/978-3-030-41068-1_4
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