EconBiz - Find Economic Literature
    • Logout
    • Change account settings
  • A-Z
  • Beta
  • About EconBiz
  • News
  • Thesaurus (STW)
  • Academic Skills
  • Help
  •  My account 
    • Logout
    • Change account settings
  • Login
EconBiz - Find Economic Literature
Publications Events
Search options
Advanced Search history
My EconBiz
Favorites Loans Reservations Fines
    You are here:
  • Home
  • Search: subject:"forecasting practice"
Narrow search

Narrow search

Year of publication
Subject
All
Forecasting practice 19 Forecasting model 15 Prognoseverfahren 15 Forecast 10 Prognose 10 Theorie 8 Theory 8 Time series analysis 8 Zeitreihenanalyse 8 Economic forecast 6 Wirtschaftsprognose 6 forecasting practice 6 Time series 4 Artificial intelligence 3 Bayesian methods 3 Demand 3 Demand forecasting 3 Evaluating forecasts 3 Hamiltonian sampler 3 Kalman filter 3 Künstliche Intelligenz 3 Nachfrage 3 State space model 3 State space models 3 Zustandsraummodell 3 Bayes-Statistik 2 Bayesian inference 2 Empirical research 2 First-order Taylor series expansion 2 Forecast error variance 2 Frühindikator 2 Leading indicator 2 Machine learning 2 Macroeconomic forecasting 2 Most probable point 2 Multi-step-ahead forecasts 2 Nowcasting 2 Replication 2 SUR 2 Search engine 2
more ... less ...
Online availability
All
Undetermined 13 Free 9
Type of publication
All
Article 19 Book / Working Paper 5 Other 1
Type of publication (narrower categories)
All
Article in journal 13 Aufsatz in Zeitschrift 13 Working Paper 3 Arbeitspapier 2 Graue Literatur 2 Non-commercial literature 2 Article 1
more ... less ...
Language
All
English 20 Undetermined 5
Author
All
Brons, Kester 3 Lange, Rutger-Jan 3 Behnamian, J. 2 Bermúdez, José D. 2 Boylan, John E. 2 Fildes, Robert 2 Goodwin, Paul 2 Karimi, B. 2 Knüppel, Malte 2 Mohammadipour, Maryam 2 Moludi, M. Fadaei 2 Niesert, Robin 2 Oorschot, Jochem 2 Syntetos, Aris A. 2 Veldhuisen, Chris 2 Armstrong, J. Scott 1 Asimakopoulos, Stavros 1 Audrino, Francesco 1 Cancelo, Jose Ramon 1 Chassot, Jonathan 1 Colasante, Annarita 1 Demetrescu, Matei 1 Dix, Alan 1 Espasa, Antoni 1 Fatemi Ghomi, S. M. T. 1 Gallegati, Mauro 1 Ghomi, S.M.T. Fatemi 1 Grafe, Rosemarie 1 Harvey, Nigel 1 Huber, Jakob 1 Kolassa, Stephan 1 Ma, Shaohui 1 McSharry, Patrick 1 Niesert, Robin F. 1 Nikolopoulos, Konstantinos I. 1 Oorschot, Jochem A. 1 Orrell, David 1 Palestrini, Antonio 1 Phillips, Christina Jane 1 Richardson, Adam 1
more ... less ...
Institution
All
Departamento de Estadistica, Universidad Carlos III de Madrid 1 Department of Economics, George Washington University 1
Published in...
All
International journal of forecasting 11 International Journal of Forecasting 3 Discussion paper / Tinbergen Institute 1 European Journal of Industrial Engineering 1 European journal of industrial engineering : EJIE 1 Journal of Industrial Engineering International 1 Journal of industrial engineering international 1 Research paper series / Swiss Finance Institute 1 Statistics and Econometrics Working Papers 1 Tinbergen Institute Discussion Paper 1 Working Papers / Department of Economics, George Washington University 1
more ... less ...
Source
All
ECONIS (ZBW) 15 RePEc 6 BASE 2 EconStor 2
Showing 1 - 10 of 25
Cover Image
(Structural) VAR models with ignored changes in mean and volatility
Demetrescu, Matei; Salish, Nazarii - In: International journal of forecasting 40 (2024) 2, pp. 840-854
Persistent link: https://www.econbiz.de/10014547211
Saved in:
Cover Image
HARd to beat : the overlooked impact of rolling windows in the era of machine learning
Audrino, Francesco; Chassot, Jonathan - 2024
Persistent link: https://www.econbiz.de/10015130715
Saved in:
Cover Image
Retail forecasting : research and practice
Fildes, Robert; Ma, Shaohui; Kolassa, Stephan - In: International journal of forecasting 38 (2022) 4, pp. 1283-1318
Persistent link: https://www.econbiz.de/10014381082
Saved in:
Cover Image
Can Google search data help predict macroeconomic series?
Niesert, Robin; Oorschot, Jochem; Veldhuisen, Chris; … - 2019
We use Google search data with the aim of predicting unemployment, CPI and consumer confidence for the US, UK, Canada, Germany and Japan. Google search queries have previously proven valuable in predicting macroeconomic variables in an in-sample context. To our knowledge, the more challenging...
Persistent link: https://www.econbiz.de/10011987495
Saved in:
Cover Image
Nowcasting GDP using machine-learning algorithms : a real-time assessment
Richardson, Adam; Van Florenstein Mulder, Thomas; … - In: International journal of forecasting 37 (2021) 2, pp. 941-948
Persistent link: https://www.econbiz.de/10012792884
Saved in:
Cover Image
Can Google Search Data Help Predict Macroeconomic Series?
Niesert, Robin; Oorschot, Jochem; Veldhuisen, Chris; … - 2019
We use Google search data with the aim of predicting unemployment, CPI and consumer confidence for the US, UK, Canada, Germany and Japan. Google search queries have previously proven valuable in predicting macroeconomic variables in an in-sample context. To our knowledge, the more challenging...
Persistent link: https://www.econbiz.de/10012114774
Saved in:
Cover Image
Daily retail demand forecasting using machine learning with emphasis on calendric special days
Huber, Jakob; Stuckenschmidt, Heiner - In: International journal of forecasting 36 (2020) 4, pp. 1420-1438
Persistent link: https://www.econbiz.de/10012546798
Saved in:
Cover Image
Can Google search data help predict macroeconomic series?
Niesert, Robin F.; Oorschot, Jochem A.; Veldhuisen, … - In: International journal of forecasting 36 (2020) 3, pp. 1163-1172
Persistent link: https://www.econbiz.de/10012498584
Saved in:
Cover Image
An iterative method for forecasting most probable point of stochastic demand
Behnamian, J.; Fatemi Ghomi, S. M. T.; Karimi, B.; … - In: Journal of industrial engineering international 10 (2014), pp. 1-9
The demand forecasting is essential for all production and non-production systems. However, nowadays there are only few researches on this area. Most of researches somehow benefited from simulation in the conditions of demand uncertainty. But this paper presents an iterative method to find most...
Persistent link: https://www.econbiz.de/10011556537
Saved in:
Cover Image
An iterative method for forecasting most probable point of stochastic demand
Behnamian, J.; Ghomi, S.M.T. Fatemi; Karimi, B.; … - In: Journal of Industrial Engineering International 10 (2014), pp. 1-9
The demand forecasting is essential for all production and non-production systems. However, nowadays there are only few researches on this area. Most of researches somehow benefited from simulation in the conditions of demand uncertainty. But this paper presents an iterative method to find most...
Persistent link: https://www.econbiz.de/10011640811
Saved in:
  • 1
  • 2
  • 3
  • Next
  • Last
A service of the
zbw
FAQ-Assistent (beta)
  • Sitemap
  • Plain language
  • Accessibility
  • Contact us
  • Imprint
  • Privacy

Loading...