Livrare gratuită pentru comenzile peste 349,00 lei.

Verifică starea comenzii

Faceți parte dintr-o comunitate de iubitori de cărți din întreaga lume și beneficiați de o mulțime de avantaje Creați-vă un cont gratuit

Transport gratuit la punctele de livrare Pick Up peste 349.00 lei

Packeta 15.00 lei Serviciul de curierat Cargus 28.00 lei Easybox 20.00 lei FAN Courier 20.00 lei Punct FAN 16.00 lei Punct DPD 17.00 lei Curier DPD 25.00 lei

Contact

Cum să cumpăr

Ajutor

Contul meu

▸ Gol :-(

Livrare gratuită pentru comenzile peste 349,00 lei.

Artificial Intelligence for Financial Markets

Name: Artificial Intelligence for Financial Markets
Brand: Springer Nature Switzerland AG
SKU: 38633862
Price: 723.41 RON
Availability: InStock
Author: Thomas Barrau
ISBN: 9783030973186

The Polymodel Approach

Thomas Barrau

Raphael Douady

Limba

engleză

Carte Copertă tare

Codul Libristo: 38633862

Editura Springer Nature Switzerland AG, iunie 2022

This book introduces the novel artificial intelligence technique of polymodels and applies it to the... Descrierea completă

Codul Libristo: 38633862

334 b

723.41 lei

În depozitul extern Expediem în 10-13 zile

Până la 30 de zile pentru returnare

Clienții au cumpărat de asemenea

The New Controller Guidebook: Sixth Edition Steven M. Bragg

Carte broșată

175.75 lei

Understanding Your Child's Brain Álvaro Bilbao

Carte broșată

189.99 lei

Digital Marketing Dave Chaffey

Carte broșată

1 140.93 lei

Instagram Power, Second Edition: Build Your Brand and Reach More Customers with Visual Influence Jason Miles

Carte broșată

109.13 lei

An Introduction to Human Communication Joy L. Hart

Carte broșată

606.27 lei

Business Model Generation - A Handbook for Visionaries Game Changers and Challengers Alexander Osterwalder

Carte broșată

157.35 lei

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 described which 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.