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.
Frankfurt am Main, Berlin, Bern, Bruxelles, New York, Oxford, Wien, 2011. 101 pp., 4 fig., num. tables and graphs
Cristina Sattarhoff holds a Diploma in Business Administration from the University of Hamburg. From 2005 to 2010 she worked
as a research assistant at the Institute of Statistics and Econometrics of the University of Hamburg and received her PhD