Statistical Inference in Multifractal Random Walk Models for Financial Time Series

By Cristina Sattarhoff

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.

• Format: Paperback
• Language: English
• ISBN: 3631606737
• ISBN13: 9783631606735
• Release Date: April 2011
• Publisher: Peter Lang Gmbh, Internationaler Verlag Der W
• Length: 102 Pages
• Weight: 0.30 lbs.
• Dimensions: 0.3" x 5.8" x 8.0"