Analysis Forecasting Financial Time by Sen Jaydip (8 results)

Condition: New. pp. 264.

Taschenbuch. Condition: Neu. Analysis and Forecasting of Financial Time Series Using R | Models and Applications | Jaydip Sen (u. a.) | Taschenbuch | 264 S. | Englisch | 2017 | Scholars' Press | EAN 9783330653863 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Analysis and prediction of stock market time series data have attracted considerable interest from the research community over the last decade. Rapid development and evolution of sophisticated algorithms for statistical analysis of time series data and availability of high-performance hardware have made it possible to process and analyze high volume stock market time series data effectively, in real-time. Among many other important characteristics and behavior of such data, forecasting is an area which has witnessed considerable focus. This book presents some of the state of the art research work in the field of time series analysis and forecasting. Rich libraries of R software have been used for time series decomposition and for designing of efficient forecasting approaches. It will surely be a valuable source of knowledge for researchers, engineers, practitioners, analysts, data scientists and graduate and doctoral students who are working in the field of econometrics, statistical modeling, time series analysis, forecasting and financial analytics. It will also be useful for faculty members of graduate schools and universities. 264 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sen JaydipProf. Jaydip Sen is currently working as a Professor in the Department of Analytics and Information Technology in Praxis Business School, Kolkata,INDIA. His main areas of research include cryptography, network security, pri.

Condition: New. Print on Demand pp. 264.

Condition: New. PRINT ON DEMAND pp. 264.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Analysis and prediction of stock market time series data have attracted considerable interest from the research community over the last decade. Rapid development and evolution of sophisticated algorithms for statistical analysis of time series data and availability of high-performance hardware have made it possible to process and analyze high volume stock market time series data effectively, in real-time. Among many other important characteristics and behavior of such data, forecasting is an area which has witnessed considerable focus. This book presents some of the state of the art research work in the field of time series analysis and forecasting. Rich libraries of R software have been used for time series decomposition and for designing of efficient forecasting approaches. It will surely be a valuable source of knowledge for researchers, engineers, practitioners, analysts, data scientists and graduate and doctoral students who are working in the field of econometrics, statistical modeling, time series analysis, forecasting and financial analytics. It will also be useful for faculty members of graduate schools and universities.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 264 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Analysis and prediction of stock market time series data have attracted considerable interest from the research community over the last decade. Rapid development and evolution of sophisticated algorithms for statistical analysis of time series data and availability of high-performance hardware have made it possible to process and analyze high volume stock market time series data effectively, in real-time. Among many other important characteristics and behavior of such data, forecasting is an area which has witnessed considerable focus. This book presents some of the state of the art research work in the field of time series analysis and forecasting. Rich libraries of R software have been used for time series decomposition and for designing of efficient forecasting approaches. It will surely be a valuable source of knowledge for researchers, engineers, practitioners, analysts, data scientists and graduate and doctoral students who are working in the field of econometrics, statistical modeling, time series analysis, forecasting and financial analytics. It will also be useful for faculty members of graduate schools and universities.