1.

Record Nr.

UNINA9910574052003321

Autore

Barrau Thomas

Titolo

Artificial Intelligence for Financial Markets : The Polymodel Approach / / by Thomas Barrau, Raphael Douady

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022

ISBN

3-030-97319-0

Edizione

[1st ed. 2022.]

Descrizione fisica

1 online resource (182 pages)

Collana

Financial Mathematics and Fintech, , 2662-7175

Disciplina

332.64028563

332.6015195

Soggetti

Social sciences - Mathematics

Mathematics in Business, Economics and Finance

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di contenuto

1. Introduction -- 2. Polymodel Theory: An Overview -- 3. Estimation Method: the Linear Non-Linear Mixed Model -- 4. Predictions of Market Returns -- 5. Predictions of Industry Returns -- 6. Predictions of Specific Returns -- 7. Genetic Algorithm-Based Combination of Predictions -- 8. Conclusions -- 9. Appendix.

Sommario/riassunto

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.