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Springer Artificial Intelligence for Financial Markets Book

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Description

Explore the novel artificial intelligence technique of polymodels in this professional text from Springer. This book introduces the polymodel approach to predict stock returns by describing a system through its sensitivities to an environment. By monitoring these sensitivities, the method imitates the spontaneous functions of a natural brain. This approach utilizes a collection of non-linear univariate models, offering a powerful alternative to traditional multivariate regressions. Because the results are easy to interpret, this method serves as an ideal preliminary step before moving toward traditional neural network approaches. It is an essential resource for those studying financial mathematics and fintech.

Key Features

This Springer publication introduces the novel polymodel technique for artificial intelligence applications in financial markets.

The book applies polymodels to the specific task of predicting stock returns using non-linear univariate models.

Learn how to describe a system by its sensitivities to an environment to monitor it like a natural brain.

This method provides a powerful standalone alternative to traditional multivariate regressions with easy to interpret results.

The polymodel approach serves as an ideal preliminary step for those transitioning toward traditional neural network methods.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
02 June 2023
Listed Since
05 May 2023

Barcode

No barcode data available

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