Statistical Inference in Multifractal Random Walk Models for Financial Time Series
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A01=Cristina Sattarhoff
Author_Cristina Sattarhoff
Category=KCA
Category=KF
Cristina
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eq_business-finance-law
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Product details
- ISBN 9783631606735
- Weight: 150g
- Dimensions: 148 x 210mm
- Publication Date: 15 Apr 2011
- Publisher: Peter Lang AG
- Publication City/Country: CH
- Product Form: Paperback
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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.
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 in Economics.
