Introduction to Bayesian Machine Learning in Quantitative Finance

Wilson Tsakane Mongwe (), Rendani Mbuvha () and Tshilidzi Marwala
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Wilson Tsakane Mongwe: University of Johannesburg
Rendani Mbuvha: University of Witwatersrand
Tshilidzi Marwala: United Nations University

Chapter Chapter 1 in Bayesian Machine Learning in Quantitative Finance, 2025, pp 1-12 from Springer

Abstract: Abstract This chapter introduces the Bayesian framework and how it can be applied to the various areas of quantitative finance, including derivative modeling, banking, financial management, insurance, and investments. We highlight the impact machine learning has had on the finance industry and the potential benefits of framing problems in quantitative finance within the Bayesian framework. The Bayesian framework allows us to naturally answer questions such as: (1) How can we explain the prediction or output of the models? (2) What is the distribution of the parameters of the model? (3) How do we select between the different models in a statistically principled manner? and (4) Which inputs are most relevant for the task at hand? This book aims to answer these questions across various fields within quantitative finance.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-88431-3_1

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DOI: 10.1007/978-3-031-88431-3_1

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