Modelling forecasting financial data (13 Ergebnisse)

Hardcover. Zustand: Brand New. 192 pages. 9.25x6.25x1.00 inches. In Stock.

Zustand: New. This book is an accessible practitioners guide to the most cutting-edge models used in high-frequency finance modelling, providing advanced techniques and tools for understanding market microstructure and more generally for analyzing financial markets using recent HF data. Num Pages: 304 pages, 33 black & white tables, 34 figures. BIC Classification: KCJ; KFF. Category: (P) Professional & Vocational. Dimension: 167 x 241 x 26. Weight in Grams: 620. . 2015. Hardcover. . . . . Books ship from the US and Ireland. …

Zustand: New. pp. 192.

hardcover. Zustand: Sehr gut. 516 Seiten; 9780792376804.2 Gewicht in Gramm: 1.

Taschenbuch. Zustand: Neu. Modelling and Forecasting Financial Data | Techniques of Nonlinear Dynamics | Liangyue Cao (u. a.) | Taschenbuch | xxviii | Englisch | 2012 | Springer US | EAN 9781461353102 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Zustand: New. In English.

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic. To make such methods readily useful in practice, the contributors to this volume have agreed to make available to readers upon request all computer programs used to implement the methods discussed in their respective chapters. Modelling and Forecasting Financial Data is a valuable resource for researchers and graduate students studying complex systems in finance, biology, and physics, as well as those applying such methods to nonlinear time series analysis and signal processing.…

Gebunden. Zustand: New. Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic. To make such methods readily useful in practice, the contributors to this volume have agreed to mak.

Buch. Zustand: Neu. Neuware - Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic. To make such methods readily useful in practice, the contributors to this volume have agreed to make available to readers upon request all computer programs used to implement the methods discussed in their respective chapters. Modelling and Forecasting Financial Data is a valuable resource for researchers and graduate students studying complex systems in finance, biology, and physics, as well as those applying such methods to nonlinear time series analysis and signal processing.…

Zustand: New. Presents computer programs used to implement the methods discussed in the respective chapters. This book is suitable for researchers and graduate students studying complex systems in finance, biology, and physics, as well as those applying such methods to nonlinear time series analysis and signal processing. Editor(s): Soofi, Abdol S.; Cao, Liangyue. Series: Studies in Computational Finance. Num Pages: 488 pages, biography. BIC Classification: KCH; KFF. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 28. Weight in Grams: 901. . 2002. Hardback. . . . . Books ship from the US and Ireland.…

Zustand: gut. 2002. Modelling and Forecasting Financial Data: Techniques of Nonlinear Dynamics (Studies in Computational Finance, 2, Band 2) In englischer Sprache. pages.

Zustand: Wie neu. Gebraucht - Wie neu Wie neu, Importqualität, auf Lager - Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Predictive analytics encompasses a variety of techniques from statistics, data mining and game theory that analyze current and historical facts to make predictions about future events. In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision making for candidate transactions. One of the most well-known applications is credit scoring, which is used throughout financial services. Scoring models process a customer''s credit history, loan application, customer data, etc., in order to rank-order individuals by their likelihood of making future credit payments on time. Predictive analytics are also used in insurance, telecommunications, retail, travel, healthcare, pharmaceuticals and other fields.…