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$Statistical Inference in multifractal random walk models for financial time series Cover Image$ E-book

E-book

Statistical Inference in multifractal random walk models for financial time series

Summary: Annotation 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.

Record details

ISBN: 3631606737
ISBN: 9783631606735
ISBN: 9783653007954 (electronic bk.)
ISBN: 365300795X (electronic bk.)
Physical Description: 1 online resource (101 p.) ill.
remote
electronic resource
Publisher: Frankfurt am Main ; New York : Peter Lang, 2011

Content descriptions

General Note:	CatBulkString:jan.03.13 Multi-User. CatMonthString:jan.13
Bibliography, etc. Note:	Includes bibliographical references (p. [97]-101).
Terms Governing Use and Reproduction Note:	Access requires VIU IP addresses and is restricted to VIU students, faculty and staff. Access restricted by subscription.
Source of Description Note:	Description based on print version record.