Statistical Inference In Multifractal Random Walk Models For Financial Time Series

Statistical Inference In Multifractal Random Walk Models For Financial Time Series

eBook - 2011
Rate this:
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.
Publisher: Frankfurt a.M. : Peter Lang GmbH, Internationaler Verlag der Wissenschaften, 2011
Copyright Date: ©2011
ISBN: 9783653007954
9783631606735
Branch Call Number: ebook
Additional Contributors: Ebook Library

Opinion

From the critics


Community Activity

Comment

Add a Comment

There are no comments for this title yet.

Age

Add Age Suitability

There are no ages for this title yet.

Summary

Add a Summary

There are no summaries for this title yet.

Notices

Add Notices

There are no notices for this title yet.

Quotes

Add a Quote

There are no quotes for this title yet.

Explore Further

Recommendations

Subject Headings

  Loading...

Find it at MCL

  Loading...
[]
[]
To Top