Artificial Intelligence for Financial Markets The Polymodel Approach
Language: English
Published by Springer, 2022
- Hardcover
- New
Condition: New
£ 149.38
Quantity: 2 available
Add to basketItem description from seller
This book introduces the novel artificial intelligence technique of polymodels and applies it to the prediction of stock returns. The idea of polymodels is to describe a system by its sensitivities to an environment, and to monitor it, imitating what a natural brain does spontaneously. In practice this involves running a collection of non-linear univariate models. This very powerful standalone technique has several advantages over traditional multivariate regressions. With its easy to interpret results, this method provides an ideal preliminary step towards the traditional neural network approach. The first two chapters compare the technique with other regression alternatives and introduces an estimation method which regularizes a polynomial regression using cross-validation. The rest of the book applies these ideas to financial markets. Certain equity return components are predicted using polymodels in very different ways, and a genetic algorithm is describedwhich combines these different predictions into a single portfolio, aiming to optimize the portfolio returns net of transaction costs. Addressed to investors at all levels of experience this book will also be of interest to both seasoned and non-seasoned statisticians. Sprache: Englisch Gewicht in Gramm: 401.…
Seller Inventory # IB-1722478
- Title
- Artificial Intelligence for Financial Markets The Polymodel Approach
- Author
- Raphael Douady, Thomas Barrau
- Publisher
- Springer
- Publication year
- 2022
- Condition
- Neu
- Binding
- Gebundene Ausgabe
- Language
- English
- ISBN 10
- 3030973182
- ISBN 13
- 9783030973186
- Item weight
- 401 grams
"Synopsis" may belong to another edition of this title.
About the Author
Raphael Douady is a French mathematician and economist specializing in data science, financial mathematics and chaos theory at the University of Paris I-Panthéon-Sorbonne. He formerly held the Frey Chair of quantitative finance at Stony Brook University and was academic director of the French Laboratory of Excellence on Financial Regulation. He earned his PhD in Hamiltonian dynamics and has more than 25 years of experience in the financial industry. He has particular interest in researching portfolio risks, for which he has developed especially suited powerful nonlinear statistical and data science models, as well as macroeconomics and systemic risk. He founded fin tech firms Riskdata (risk management for the buyside) and Datacore (quantitative portfolio of ETFs) and is Chief Science Officer of NM Fin tech (numerical methods for fixed income trading in China).
"About the title" may belong to another edition of this title.
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