Wilson Tsakane Mongwe: Bayesian Machine Learning in Quantitative Finance, Gebunden
Bayesian Machine Learning in Quantitative Finance
- Theory and Practical Applications
(soweit verfügbar beim Lieferanten)
- Verlag:
- Springer Nature Switzerland, 06/2025
- Einband:
- Gebunden
- Sprache:
- Englisch
- ISBN-13:
- 9783031884306
- Artikelnummer:
- 12333163
- Umfang:
- 372 Seiten
- Gewicht:
- 591 g
- Maße:
- 216 x 153 mm
- Stärke:
- 25 mm
- Erscheinungstermin:
- 22.6.2025
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Klappentext
This book offers a comprehensive discussion of the Bayesian inference framework and demonstrates why this probabilistic approach is ideal for tackling the various modelling problems within quantitative finance. It demonstrates how advanced Bayesian machine learning techniques can be applied within financial engineering, investment portfolio management, insurance, municipal finance management as well as banking.
The book covers a broad range of modelling approaches, including Bayesian neural networks, Gaussian processes and Markov Chain Monte Carlo methods. It also discusses the utility of Bayesian inference in quantitative finance and discusses future research goals in the applications of Bayesian machine learning in quantitative finance. Chapters are rooted in the theory of quantitative finance and machine learning while also outlining a range of practical considerations for implementing Bayesian techniques into real-world quantitative finance problems. This book is ideal for graduate researchers and practitioners at the intersection of machine learning and quantitative finance, as well as those working in computational statistics and computer science more broadly.
Wilson Tsakane Mongweis a machine learning research fellow at the University of Johannesburg, South Africa, and an Associate Director and the Head Quantitative Analyst at a Big Four audit firm's Financial Services Advisory business unit. He is an author of the machine learning book entitled "Hamiltonian Monte Carlo Methods in Machine Learning".
Rendani Mbuvhais Associate Professor of Actuarial Science in the Department of Mathematics at the University of Manchester, UK. He is a fellow of the Institute and Faculty of Actuaries and Co-Founder of AfriClimate AI. He has published extensively in probabilistic inference in machine learning, renewable energy modeling, and computational finance.
Tshilidzi Marwalais United Nations Under-Secretary-General and Rector of the UN University. He was the trustee of the Nelson Mandela Foundation and is a member of the American Academy of Arts and Sciences, Chinese Academy of Sciences, The World Academy of Sciences, and the African Academy of Sciences. He has published 27 books in artificial intelligence and related areas.
Biografie (Tshilidzi Marwala)
Tshilidzi Marwala is the Executive Dean of the Faculty of Engineering and the Built Environment at the University of Johannesburg. He was previously the Adhominem Professor of Electrical Engineering as well as the Carl and Emily Fuchs Chair of Systems and Control Engineering at the University of the Witwatersrand. He is a Fellow of the Royal Society of Arts as well as the Royal Statistical Society. He holds a PhD in Engineering from the University of Cambridge and a PLD from Harvard University in the USA. He was a post-doctoral research associate at Imperial College working in the general area of computational intelligence. He has been a visiting fellow at Harvard University and Cambridge University. His research interests include the application of computational intelligence to mechanical. civil, aerospace and biomedical engineering. Professor Marwala has made fundamental contributions to engineering including the development of the concept of pseudo-modal energies and the development of Bayesian framework for solving engineering problems such as finite element model updating. He has supervised 40 masters and PhD students many of whom have proceeded to distinguish themselves at universities such as Harvard, Oxford and Cambridge. He has published over 200 papers in journals such as the American Institute of Aeronautics and Astronautics Journal, proceedings and book chapters. He has published two books: Computational Intelligence for Modelling Complex Systems published by Research India Publications as well as Computational Intelligence for Missing Data Imputation, Estimation, and Management: Knowledge Optimization Techniques published by the IGI Global Publications (New York). His work has appeared in prestigious publications such as New Scientist. He is a senior member of the IEEE.
