Long Memory in Economics / Edition 1

Long Memory in Economics / Edition 1

ISBN-10:
354022694X
ISBN-13:
9783540226949
Pub. Date:
09/14/2006
Publisher:
Springer Berlin Heidelberg
ISBN-10:
354022694X
ISBN-13:
9783540226949
Pub. Date:
09/14/2006
Publisher:
Springer Berlin Heidelberg
Long Memory in Economics / Edition 1

Long Memory in Economics / Edition 1

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Overview

When applying the statistical theory of long range dependent (LRD) processes to economics, the strong complexity of macroeconomic and financial variables, compared to standard LRD processes, becomes apparent. In order to get a better understanding of the behaviour of some economic variables, the book assembles three different strands of long memory analysis: statistical literature on the properties of, and tests for, LRD processes; mathematical literature on the shastic processes involved; models from economic theory providing plausible micro foundations for the occurence of long memory in economics. Each chapter of the book will give a comprehensive survey of the state of the art and the directions that future developments are likely to take. Taken as a whole the book provides an overview of LRD processes which is accessible to economists, econometricians and statisticians.


Product Details

ISBN-13: 9783540226949
Publisher: Springer Berlin Heidelberg
Publication date: 09/14/2006
Edition description: 2007
Pages: 389
Product dimensions: 6.10(w) x 9.25(h) x 0.04(d)

Table of Contents

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.
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