Statistical Inference in Multifractal Random Walk Models for Financial Time Series
New
Book Details
Format
Paperback / Softback
Book Series
Volkswirtschaftliche Analysen
ISBN-10
3631606737
ISBN-13
9783631606735
Edition
New
Publisher
Peter Lang AG
Imprint
Peter Lang AG
Country of Manufacture
DE
Country of Publication
GB
Publication Date
Apr 15th, 2011
Print length
102 Pages
Weight
146 grams
Dimensions
15.00 x 21.00 x 0.70 cms
Product Classification:
Economic theory & philosophy
Ksh 4,700.00
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Multifractal Random Walk models can capture statistical relation between returns and return periods, thus facilitating an accurate representation of real price changes. This book provides a method of moments estimation technique for model parameters with enhanced performance in finite samples, and a novel testing procedure for multifractality.
The dynamics of financial returns varies with the return period, from high-frequency data to daily, quarterly or annual data. Multifractal Random Walk models can capture the statistical relation between returns and return periods, thus facilitating a more accurate representation of real price changes. This book provides a generalized method of moments estimation technique for the model parameters with enhanced performance in finite samples, and a novel testing procedure for multifractality. The resource-efficient computer-based manipulation of large datasets is a typical challenge in finance. In this connection, this book also proposes a new algorithm for the computation of heteroscedasticity and autocorrelation consistent (HAC) covariance matrix estimators that can cope with large datasets.
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