econometric forecasting models (21 risultati)

Condizione: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Condizione: Good. Good condition. A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains.

Pamphlet. Condizione: Very Good. Vol 10, No 3, pp. 325-333, Extracted from orig vol, thus begins with title page, trimmed & stapled pamphlet, else VG.

Hardcover. Condizione: Very Good. No Jacket. First Edition. This is an ex-library book with stamps etc. The covers show some shelf wear. The binding is tight. The pages are clean and unmarked. Electronic delivery tracking will be issued free of charge.

gr8°, Orgklebebroschur. 141 S. Sauberes und solides Exemplar ohne Gebrauchs- oder Lagerspuren. Mit persönlicher Widmung des Verfassers. ****An unsere Kunden in Deutschland: Versand nach Deutschland einmal in der Woche ab Freilassing mit der Deutschen Post.*** - Sprache: Englisch Gewicht in Gramm: 550.

Taschenbuch. Condizione: Neu. Neuware - Reactive PublishingModern forecasting is no longer about guessing the future. It is about engineering it. Economists, analysts, and quantitative leaders now demand models that explain why, not just what. This book shows how to build causal and predictive forecasting systems using the full power of econometrics and Python, bridging classical statistical tools with machine learning, structural modeling, and real-world business applications.Readers learn how to design time series pipelines, estimate causal effects, and translate empirical models into operational forecasts that drive executive decisions. From ARIMA to VAR, from causal inference to Bayesian time series, and from model selection to forecast evaluation, the book provides a rigorous yet accessible framework for forecasting markets, macroeconomic indicators, commodities, operational demand, financial performance, and policy scenarios.Beyond the theory, Applied Econometric Forecasting with Python emphasizes implementation. Full workflows demonstrate how to structure data, choose the correct econometric formulation, evaluate forecast accuracy, and deploy models at scale. The book closes with advanced chapters on structural breaks, adaptive forecasting, rolling horizons, scenario analysis, and machine learning augmentation.You will learn: - How to construct causal models that isolate drivers and explain economic behavior- How to implement econometric time series forecasting pipelines in Python- How to integrate machine learning with classical econometrics for more robust predictions- How to evaluate forecast performance and uncertainty- How to build rolling, scenario-based, and probabilistic forecasts- How to translate empirical models into operational decision frameworksIdeal for: Finance professionals, economists, data scientists, policy analysts, enterprise planning teams, academic researchers, and quantitative practitioners seeking a rigorous applied forecasting playbook.The future belongs to those who can quantify uncertainty, measure causality, and model change. This book shows you how.

Condizione: New. pp. 236.

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Taschenbuch. Condizione: Neu. Econometric Forecasting Models for Short Term Natural Rubber Prices | Economic Development of World Natural Rubber Industry Models Specifications, Simulation and Evaluation | Aye Aye Khin (u. a.) | Taschenbuch | 236 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846515464 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Hardcover. Condizione: Very Good-. 1st Edition. 155 pages in very good condition. Pages have some pencil underlining on a few pages, otherwise clean and unmarked with some black and white tables and charts throughout. Previous owner's stamp and marking on the ffep. Bound in blue hardcovers with black titles. A small label taped to the tail end of the spine. Lightly faded on the spine, lightly worn around the edges. 1ST EDITION. VG-. Book.

hardcover. Condizione: Good. Good. Dust Jacket NOT present. CD WILL BE MISSING. . SHIPS FROM MULTIPLE LOCATIONS. book.

paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

paperback. Condizione: Good. Modern Management Science Series entry econometric forecasting and prediction models.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This study presents a number of short-term ex-post forecasts of single equation model, Multivariate Autoregressive Moving Average (MARMA) model, simultaneous supply-demand and price system equation model, and Autoregressive Integrated Moving Average (ARIMA) model, and ARCH-type models of natural rubber (NR) SMR20 (Standard Malaysia Rubber of grade 20) prices in the world NR market. The ARCH-type models (Autoregressive Conditional Heteroskedasticity) used include the GARCH (1,1) (Generalized ARCH) model, EGARCH (1,1) (The Exponential GARCH) model, PARCH (1,1) (The Power ARCH) and CGARCH (1,1) (The Component GARCH) model. The models were utilized using monthly data from January 1990 to December 2008 as estimation period, providing a total of 228 observations and data was used as an ex-post forecasts. The results revealed that the forecasting performance of the simultaneous supply-demand and price system equation model was more efficient than single equation model, MARMA model and ARIMA model, and ARCH-type models for ex-post forecast in estimating the price of SMR20 in the next 6 months or so. 236 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Khin Aye AyeAye Aye Khin has successfully obtained her Ph.D Degree in Agribusiness and worked as a Post Doctoral Research Fellow at Universiti Putra Malaysia (UPM) in 2010. In 2011, she has joined as a Lecturer in Multimedia Universi.

Taschenbuch. Condizione: Neu. Forecasting with Econometric Methods | A Comparitive Performance of ARIMA Models | A. Mohan Babu (u. a.) | Taschenbuch | Englisch | 2013 | Scholars' Press | EAN 9783639518580 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Forecasting is an important aid in effective and efficient planning. It is an attempt to predict the feature by examining the past. The main purpose of making a forecast is to gain knowledge about uncertain events that are important to our present decisions. In the present study, an attempt has been made to forecast the production of prime food grains of Indian Agriculture sector like Rice, Wheat, Pulses and Oil seeds by using different types of ARIMA models. And also to fit the best suited time series model for the data collected with the help of forecasting accuracy measures.

Condizione: New. Print on Demand pp. 236 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condizione: New. PRINT ON DEMAND pp. 236.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This study presents a number of short-term ex-post forecasts of single equation model, Multivariate Autoregressive Moving Average (MARMA) model, simultaneous supply-demand and price system equation model, and Autoregressive Integrated Moving Average (ARIMA) model, and ARCH-type models of natural rubber (NR) SMR20 (Standard Malaysia Rubber of grade 20) prices in the world NR market. The ARCH-type models (Autoregressive Conditional Heteroskedasticity) used include the GARCH (1,1) (Generalized ARCH) model, EGARCH (1,1) (The Exponential GARCH) model, PARCH (1,1) (The Power ARCH) and CGARCH (1,1) (The Component GARCH) model. The models were utilized using monthly data from January 1990 to December 2008 as estimation period, providing a total of 228 observations and data was used as an ex-post forecasts. The results revealed that the forecasting performance of the simultaneous supply-demand and price system equation model was more efficient than single equation model, MARMA model and ARIMA model, and ARCH-type models for ex-post forecast in estimating the price of SMR20 in the next 6 months or so.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 236 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This study presents a number of short-term ex-post forecasts of single equation model, Multivariate Autoregressive Moving Average (MARMA) model, simultaneous supply-demand and price system equation model, and Autoregressive Integrated Moving Average (ARIMA) model, and ARCH-type models of natural rubber (NR) SMR20 (Standard Malaysia Rubber of grade 20) prices in the world NR market. The ARCH-type models (Autoregressive Conditional Heteroskedasticity) used include the GARCH (1,1) (Generalized ARCH) model, EGARCH (1,1) (The Exponential GARCH) model, PARCH (1,1) (The Power ARCH) and CGARCH (1,1) (The Component GARCH) model. The models were utilized using monthly data from January 1990 to December 2008 as estimation period, providing a total of 228 observations and data was used as an ex-post forecasts. The results revealed that the forecasting performance of the simultaneous supply-demand and price system equation model was more efficient than single equation model, MARMA model and ARIMA model, and ARCH-type models for ex-post forecast in estimating the price of SMR20 in the next 6 months or so.