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  • Search: subject:"Forecast combining"
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Year of publication
Subject
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Forecast combining 4 forecast combining 4 Bayesian model averaging 3 Forecasting model 3 Prognoseverfahren 3 Forecast 2 Forecasting 2 Inflation 2 Prognose 2 Theorie 2 Theory 2 forecast-combining 2 hypothesis testing 2 instability in model selection 2 model selection 2 nonlinear 2 nonparametric 2 time-varying 2 Akaike criteria 1 Akaike criterion 1 Bayes-Statistik 1 Bayesian inference 1 COVID-19 1 Coronavirus 1 Distributional forecasts 1 Economic forecast 1 Factor analysis 1 Faktorenanalyse 1 Forecasting, Inflation, Bayesian model averaging, Akaike criteria, Forecast combining 1 Forecasting, Inflation, Bayesian model averaging, Akaike criterion, Forecast combining 1 Frühindikator 1 Interval forecasts 1 Leading indicator 1 Modellierung 1 Mortality 1 OR in health services 1 Portfolio selection 1 Portfolio-Management 1 Risikomaß 1 Risk measure 1
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Online availability
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Undetermined 8 Free 2
Type of publication
All
Article 8 Book / Working Paper 4
Type of publication (narrower categories)
All
Article in journal 2 Aufsatz in Zeitschrift 2 Working Paper 2
Language
All
English 7 Undetermined 5
Author
All
Kapetanios, George 4 Labhard, Vincent 4 Price, Simon 4 Chen, Zhuo 2 Li, Fuchun 2 Taylor, James W. 2 Tkacz, Greg 2 Yang, Yuhong 2 Ben-Zion, Uri 1 Preminger, Arie 1 Stock, James H. 1 Taylor, Kathryn S. 1 Trucíos, Carlos 1 Watson, Mark W. 1 Wettstein, David 1
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Institution
All
School of Economics and Finance, Queen Mary 2
Published in...
All
Studies in Nonlinear Dynamics & Econometrics 4 Working Paper 2 Working Papers / School of Economics and Finance, Queen Mary 2 European journal of operational research : EJOR 1 Handbook of economic forecasting ; 1 1 Journal of forecasting 1 The European Journal of Finance 1
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Source
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RePEc 7 ECONIS (ZBW) 3 EconStor 2
Showing 1 - 10 of 12
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Combining probabilistic forecasts of COVID-19 mortality in the United States
Taylor, James W.; Taylor, Kathryn S. - In: European journal of operational research : EJOR 304 (2023) 1, pp. 25-41
Persistent link: https://www.econbiz.de/10013454170
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A comparison of methods for forecasting value at risk and expected shortfall of cryptocurrencies
Trucíos, Carlos; Taylor, James W. - In: Journal of forecasting 42 (2023) 4, pp. 989-1007
Persistent link: https://www.econbiz.de/10014292894
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Forecasting using predictive likelihood model averaging
Kapetanios, George; Labhard, Vincent; Price, Simon - 2006
Recently, there has been increasing interest in forecasting methods that utilise large datasets. We explore the possibility of forecasting with model averaging using the out-of-sample forecasting performance of various models in a frequentist setting, using the predictive likelihood. We apply...
Persistent link: https://www.econbiz.de/10010284123
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Forecasting using Bayesian and information theoretic model averaging: An application to UK inflation
Kapetanios, George; Labhard, Vincent; Price, Simon - 2006
In recent years there has been increasing interest in forecasting methods that utilise large datasets, driven partly by the recognition that policymaking institutions need to process large quantities of information. Factor analysis is one popular way of doing this. Forecast combination is...
Persistent link: https://www.econbiz.de/10010284215
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Time Series Models for Forecasting: Testing or Combining?
Chen, Zhuo; Yang, Yuhong - In: Studies in Nonlinear Dynamics & Econometrics 11 (2008) 1, pp. 1385-1385
use of forecast combining when there is considerable instability in model selection by testing procedures. On the other … hand, when there is little instability, testing procedures could work well or even better than forecast combining in terms …
Persistent link: https://www.econbiz.de/10004966144
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Combining Forecasts with Nonparametric Kernel Regressions
Li, Fuchun; Tkacz, Greg - In: Studies in Nonlinear Dynamics & Econometrics 8 (2007) 4, pp. 1129-1129
We introduce a flexible nonparametric technique that can be used to select weights in a forecast-combining regression … nonlinear forecast-combining procedures. The simulation results show that when forecast errors are correlated across models, the … application to inflation forecasting is also presented to demonstrate the use of all forecast-combining techniques. …
Persistent link: https://www.econbiz.de/10004966209
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Cover Image
Time Series Models for Forecasting: Testing or Combining?
Chen, Zhuo; Yang, Yuhong - In: Studies in Nonlinear Dynamics & Econometrics 11 (2007) 1, pp. 1385-1385
use of forecast combining when there is considerable instability in model selection by testing procedures. On the other … hand, when there is little instability, testing procedures could work well or even better than forecast combining in terms …
Persistent link: https://www.econbiz.de/10005579856
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Extended switching regression models with time-varying probabilities for combining forecasts
Preminger, Arie; Ben-Zion, Uri; Wettstein, David - In: The European Journal of Finance 12 (2006) 6-7, pp. 455-472
This paper introduces a new methodology, which extends the well-known switching regression model. The extension is via the introduction of several latent state variables, each one of which influencing a disjoint set of the model parameters. Furthermore, the probability distribution of the state...
Persistent link: https://www.econbiz.de/10005471900
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Cover Image
Forecasting using Bayesian and Information Theoretic Model Averaging: An Application to UK Inflation
Kapetanios, George; Labhard, Vincent; Price, Simon - School of Economics and Finance, Queen Mary - 2006
In recent years there has been increasing interest in forecasting methods that utilise large datasets, driven partly by the recognition that policymaking institutions need to process large quantities of information. Factor analysis is one popular way of doing this. Forecast combination is...
Persistent link: https://www.econbiz.de/10005106353
Saved in:
Cover Image
Forecasting Using Predictive Likelihood Model Averaging
Kapetanios, George; Labhard, Vincent; Price, Simon - School of Economics and Finance, Queen Mary - 2006
Recently, there has been increasing interest in forecasting methods that utilise large datasets. We explore the possibility of forecasting with model averaging using the out-of-sample forecasting performance of various models in a frequentist setting, using the predictive likelihood. We apply...
Persistent link: https://www.econbiz.de/10005106379
Saved in:
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