Feedforward Neural Networks

Matthew F. Dixon, Igor Halperin and Paul Bilokon
Additional contact information
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

Chapter Chapter 4 in Machine Learning in Finance, 2020, pp 111-166 from Springer

Abstract: 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.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41068-1_4

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DOI: 10.1007/978-3-030-41068-1_4

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