ISBN: 9783631606735 - statistical inference in multifractal random walk models for financial time series: 18 (4 risultati)

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.; Dissertationsschrift.…

Originalbroschur. Condizione: Wie neu. 101 S. Tadelloses Exemplar. - Contents: Financial econometrics - Multifractal volatility - Multifractal Random Walk - GMM estimation - Monte Carlo simulation study - Multifractality test - Empirical analysis of international stock index data - Financial markets efficiency - HAC estimation - Stylized facts of financial time series - Fat-tailed distribution - Scale invariance - MATLAB. - 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. (Verlagstext). ISBN 9783631606735 Sprache: Deutsch Gewicht in Gramm: 550.…

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: Kolibri 360 GmbH, Ettore-Bugatti-Str. 6-14, 51149 Köln, produktsicherheit[at]kolibri360[dot]de | Anbieter: preigu. …

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.…