Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations… Más…
Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations. Such methods are much needed in practice as real data usually comes in irregular form. In the theoretical part he develops laws of large numbers and central limit theorems as well as a new bootstrap procedure to assess asymptotic laws. The author then applies the theoretical results to estimate the quadratic covariation and to construct tests for the presence of common jumps. The simulation results show that in finite samples his methods despite the much more complex setting perform comparably well as methods based on regular data. ?About the Author: Dr. Ole Martin completed his PhD at the Kiel University (CAU), Germany. His research focuses on high-frequency statistics for semimartingales with the aim to develop methods based on irregularly observed data. MATHEMATICS,Probability & Statistics,General, eBooks.com<
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Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations… Más…
Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations. Such methods are much needed in practice as real data usually comes in irregular form. In the theoretical part he develops laws of large numbers and central limit theorems as well as a new bootstrap procedure to assess asymptotic laws. The author then applies the theoretical results to estimate the quadratic covariation and to construct tests for the presence of common jumps. The simulation results show that in finite samples his methods despite the much more complex setting perform comparably well as methods based on regular data. About the Author: Dr. Ole Martin completed his PhD at the Kiel University (CAU), Germany. His research focuses on high-frequency statistics for semimartingales with the aim to develop methods based on irregularly observed data. Books > Mathematics eBook, Springer Shop<
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(*) Libro agotado significa que este título no está disponible por el momento en alguna de las plataformas asociadas que buscamos.
Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations… Más…
Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations. Such methods are much needed in practice as real data usually comes in irregular form. In the theoretical part he develops laws of large numbers and central limit theorems as well as a new bootstrap procedure to assess asymptotic laws. The author then applies the theoretical results to estimate the quadratic covariation and to construct tests for the presence of common jumps. The simulation results show that in finite samples his methods despite the much more complex setting perform comparably well as methods based on regular data. ?About the Author: Dr. Ole Martin completed his PhD at the Kiel University (CAU), Germany. His research focuses on high-frequency statistics for semimartingales with the aim to develop methods based on irregularly observed data. MATHEMATICS,Probability & Statistics,General, eBooks.com<
new in stock. Gastos de envío:plus shipping costs., más gastos de envío
Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations… Más…
Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations. Such methods are much needed in practice as real data usually comes in irregular form. In the theoretical part he develops laws of large numbers and central limit theorems as well as a new bootstrap procedure to assess asymptotic laws. The author then applies the theoretical results to estimate the quadratic covariation and to construct tests for the presence of common jumps. The simulation results show that in finite samples his methods despite the much more complex setting perform comparably well as methods based on regular data. About the Author: Dr. Ole Martin completed his PhD at the Kiel University (CAU), Germany. His research focuses on high-frequency statistics for semimartingales with the aim to develop methods based on irregularly observed data. Books > Mathematics eBook, Springer Shop<
new in stock. Gastos de envío:zzgl. Versandkosten. (EUR 0.00)
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Detalles del libro - High-Frequency Statistics with Asynchronous and Irregular Data
EAN (ISBN-13): 9783658284183 Año de publicación: 2019 Editorial: Springer Spektrum
Libro en la base de datos desde 2020-01-04T15:51:01-06:00 (Mexico City) Página de detalles modificada por última vez el 2022-11-22T21:35:51-06:00 (Mexico City) ISBN/EAN: 9783658284183
ISBN - escritura alterna: 978-3-658-28418-3 Mode alterno de escritura y términos de búsqueda relacionados: Título del libro: irre
Datos del la editorial
Autor: Ole Martin Título: Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics; High-Frequency Statistics with Asynchronous and Irregular Data Editorial: Springer Spektrum; Springer Fachmedien Wiesbaden GmbH 323 Páginas Año de publicación: 2019-11-05 Wiesbaden; DE Idioma: Inglés 74,89 € (DE) 77,00 € (AT) 83,00 CHF (CH) Available XIII, 323 p. 34 illus.
EA; E107; eBook; Nonbooks, PBS / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; High-frequency statistics; Asynchronous data; Irregular data; Asynchronous observations; Random observations; Quadratic covariation; Test for jumps; Test for common jumps; Bootstrap; Laws of large numbers; Central limit theorems; Bootstrapping asymptotic laws; Random observation schemes; Estimating quadratic covariation; Common jumps; quantitative finance; C; Probability Theory; Statistics in Business, Management, Economics, Finance, Insurance; Mathematics in Business, Economics and Finance; Mathematics and Statistics; Stochastik; Wirtschaftswissenschaft, Finanzen, Betriebswirtschaft und Management; Angewandte Mathematik; BC
Laws of Large Numbers.- Random Observation Schemes.- Bootstrapping Asymptotic Laws.- Testing for (Common) Jumps. New methods extending theory for regular data
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