Name: Fractal Dimension for Fractal Structures: With Applications to Finance (Sema Simai Springer Series) (en Inglés)
Price: 132486.00 ARS
Availability: InStock
Author: Manuel FernÁNdez-MartÍNez; Juan Luis GarcÍA Guirao; Miguel ÁNgel SÁNchez-Granero; Juan Evangelista Trinidad Segovia
ISBN: 9783030166441

portada Fractal Dimension for Fractal Structures: With Applications to Finance (Sema Simai Springer Series) (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Manuel FernÁNdez-MartÍNez; Juan Luis GarcÍA Guirao; Miguel ÁNgel SÁNchez-Granero; Juan Evangelista Trinidad Segovia

Año

2019

Idioma

Inglés

N° páginas

204

Encuadernación

Tapa Dura

ISBN13

9783030166441

N° edición

Categorías

Probabilidad y estadística

Fractal Dimension for Fractal Structures: With Applications to Finance (Sema Simai Springer Series) (en Inglés)

Manuel FernÁNdez-MartÍNez; Juan Luis GarcÍA Guirao; Miguel ÁNgel SÁNchez-Granero; Juan Evangelista Trinidad Segovia (Autor) · Springer · Tapa Dura

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Reseña del libro "Fractal Dimension for Fractal Structures: With Applications to Finance (Sema Simai Springer Series) (en Inglés)"

This book provides a generalised approach to fractal dimension theory from the standpoint of asymmetric topology by employing the concept of a fractal structure. The fractal dimension is the main invariant of a fractal set, and provides useful information regarding the irregularities it presents when examined at a suitable level of detail. New theoretical models for calculating the fractal dimension of any subset with respect to a fractal structure are posed to generalise both the Hausdorff and box-counting dimensions. Some specific results for self-similar sets are also proved. Unlike classical fractal dimensions, these new models can be used with empirical applications of fractal dimension including non-Euclidean contexts. In addition, the book applies these fractal dimensions to explore long-memory in financial markets. In particular, novel results linking both fractal dimension and the Hurst exponent are provided. As such, the book provides a number of algorithms for properly calculating the self-similarity exponent of a wide range of processes, including (fractional) Brownian motion and Lévy stable processes. The algorithms also make it possible to analyse long-memory in real stocks and international indexes.This book is addressed to those researchers interested in fractal geometry, self-similarity patterns, and computational applications involving fractal dimension and Hurst exponent.