Statistical Inference in Multifractal Random Walk Models for Financial Time Series
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Statistical Inference in Multifractal Random Walk Models for Financial Time Series

Statistical Inference in Multifractal Random Walk Models for Financial Time Series


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About the Book

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.
About the Author: 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.


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Product Details
  • ISBN-13: 9783631606735
  • Publisher: Peter Lang AG
  • Binding: Paperback
  • Edition: New ed
  • Language: English
  • Returnable: N
  • Spine Width: 0 mm
  • Width: 148 mm
  • ISBN-10: 3631606737
  • Publisher Date: 15 Apr 2011
  • Depth: 13
  • Height: 210 mm
  • No of Pages: 102
  • Series Title: Volkswirtschaftliche Analysen
  • Weight: 750 gr


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Statistical Inference in Multifractal Random Walk Models for Financial Time Series
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