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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.
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Informazioni sull?autore
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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Statistical Inference in Multifractal Random Walk Models for Financial Time Series
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Peter Lang Ltd. International Academic Publishers Apr 2011, 2011
ISBN 10: 3631606737
ISBN 13: 9783631606735
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 102 pp. Englisch. Codice articolo 9783631606735
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Statistical Inference in Multifractal Random Walk Models for Financial Time Series
Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Codice articolo 9783631606735
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Statistical Inference in Multifractal Random Walk Models for Financial Time Series
Da: preigu, Osnabrück, Germania
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Taschenbuch. Condizione: Neu. Statistical Inference in Multifractal Random Walk Models for Financial Time Series | Cristina Sattarhoff | Taschenbuch | Englisch | Peter Lang | EAN 9783631606735 | Verantwortliche Person für die EU: Zeitfracht Medien GmbH, Ferdinand-Jühlke-Str. 7, 99095 Erfurt, produktsicherheit[at]zeitfracht[dot]de | Anbieter: preigu. Codice articolo 103831627
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