
Long Memory in Economics
Springer (Publisher)
Published on 12. February 2010
Book
Paperback/Softback
XII, 389 pages
978-3-642-06154-7 (ISBN)
Description
A comprehensive survey on current and future developments in long memory analysis. The book assembles three different strands of long memory analysis: statistical literature - including tests - on the properties of LRD processes; mathematical literature on stochastic processes; and models from economic theory providing. The text is aimed at economists, econometricians, and statisticians interested in the study of long memory in economics.
More details
Edition
Softcover reprint of hardcover 1st ed. 2007
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
XII, 389 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 22 mm
Weight
610 gr
ISBN-13
978-3-642-06154-7 (9783642061547)
DOI
10.1007/978-3-540-34625-8
Schweitzer Classification
Other editions
Additional editions

Gilles Teyssière | Alan P. Kirman
Long Memory in Economics
Book
08/2006
Springer
€106.99
Shipment within 10-15 days
Content
Statistical Methods.- Recent Advances in ARCH Modelling.- Intermittency, Long-Memory and Financial Returns.- The Spectrum of Euro-Dollar.- Hölderian Invariance Principles and Some Applications for Testing Epidemic Changes.- Adaptive Detection of Multiple Change-Points in Asset Price Volatility.- Bandwidth Choice, Optimal Rates and Adaptivity in Semiparametric Estimation of Long Memory.- Wavelet Analysis of Nonlinear Long-Range Dependent Processes. Applications to Financial Time Series.- Prediction, Orthogonal Polynomials and Toeplitz Matrices. A Fast and Reliable Approximation to the Durbin-Levinson Algorithm.- Economic Models.- A Nonlinear Structural Model for Volatility Clustering.- Volatility Clustering in Financial Markets: Empirical Facts and Agent-Based Models.- The Microeconomic Foundations of Instability in Financial Markets.- A Minimal Noise Trader Model with Realistic Time Series Properties.- Long Memory and Hysteresis.