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To combine or not to combine: selecting among forecasts and their combinations
13 references·16 citing·29 second hop
To combine or not to combine: selecting among forecasts and their combinations (2004)To combine or not to combine: selecting a…Intuitions About Combining Opinions: Misappreciation of the Averaging Principle (2006)Intuitions About Combining Op…Principles of Forecasting (2001)Principles of ForecastingPrinciples of forecasting : a handbook for researchers and practitioners (2001)Principles of forecasting : a…The M3-Competition: results, conclusions and implications (2000)The M3-Competition: results, …Out-of-sample tests of forecasting accuracy: an analysis and review (2000)Out-of-sample tests of foreca…On the asymmetry of the symmetric MAPE (1999)On the asymmetry of the symme…Comparing Predictive Accuracy (1995)Comparing Predictive AccuracyComparing Predictive Accuracy (1994)Comparing Predictive AccuracyCombining forecasts: A review and annotated bibliography (1990)Combining forecasts: A review…Combining forecasts: A review and annotated bibliography (1989)Combining forecasts: A review…Averages of Forecasts: Some Empirical Results (1983)Averages of Forecasts: Some E…The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)The accuracy of extrapolation…The Combination of Forecasts (1969)The Combination of ForecastsForecast combinations: An over 50-year review (2022)Forecast combinations: An ove…Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion (2020)Demand forecasting in supply …Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition (2019)Improving forecasting accurac…Hybrid structures in time series modeling and forecasting: A review (2019)Hybrid structures in time ser…Forecasting in social settings: The state of the art (2019)Forecasting in social setting…Economic policy uncertainty and the Chinese stock market volatility: Novel evidence (2019)Economic policy uncertainty a…Research on the peak of CO2 emissions in the developing world: Current progress and future prospect (2018)Research on the peak of CO2 e…Judgmental selection of forecasting models (2018)Judgmental selection of forec…Financial time series prediction using a dendritic neuron model (2016)Financial time series predict…Forecasting realized volatility in a changing world: A dynamic model averaging approach (2015)Forecasting realized volatili…Improving forecasting by estimating time series structural components across multiple frequencies (2014)Improving forecasting by esti…‘Horses for Courses’ in demand forecasting (2014)‘Horses for Courses’ in deman…Combining forecasts: An application to elections (2013)Combining forecasts: An appli…Combining linear and nonlinear model in forecasting tourism demand (2011)Combining linear and nonlinea…Tourism forecasting: To combine or not to combine? (2007)Tourism forecasting: To combi…A comparative study of autoregressive neural network hybrids (2005)A comparative study of autore…Expert judgment: Some necessary conditions and an example. (1974)Chapter 4 Forecast Combinations (2006)Error measures for generalizing about forecasting methods: Empirical comparisons (1992)Exponential smoothing: The state of the art—Part II (2006)A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition (2012)Forecasting: theory and practice (2022)Construct validity in psychological tests. (1955)Time Series Analysis: Forecasting and Control. (1978)Time Series Analysis, Forecasting, and Control (1995)Judgmental forecasting: A review of progress over the last 25years (2006)Consensus measurement in Delphi studies (2012)Time Series Analysis: Forecasting and Control (1977)Exponential smoothing: The state of the art (1985)Forecasting methods and applications (1993)Time series forecasting using a hybrid ARIMA and neural network model (2003)25 years of time series forecasting (2006)Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy (2009)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Expert Opinions in Forecasting: The Role of the Delphi Technique (2001)Rethinking Partial Least Squares Path Modeling: In Praise of Simple Methods (2012)Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts (1998)A Comprehensive Look at The Empirical Performance of Equity Premium Prediction (2007)Strictly Proper Scoring Rules, Prediction, and Estimation (2007)Combination forecasts of output growth in a seven‐country data set (2004)Handbook of Economic Forecasting (2013)Testing the equality of prediction mean squared errors (1997)Consumption, Aggregate Wealth, and Expected Stock Returns (2001)Deep learning with long short-term memory networks for financial market predictions (2017)
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References

  • 1994Comparing Predictive Accuracy5,495 cited
  • 1995Comparing Predictive Accuracy5,214 cited
  • 1969The Combination of Forecasts3,194 cited
  • 1989Combining forecasts: A review and annotated bibliography2,170 cited
  • 2000The M3-Competition: results, conclusions and implications1,700 cited
  • 1982The accuracy of extrapolation (time series) methods: Results of a forecasting competition1,465 cited
  • 1990Combining forecasts: A review and annotated bibliography1,465 cited
  • 2001Principles of Forecasting1,178 cited
  • 2001Principles of forecasting : a handbook for researchers and practitioners1,045 cited
  • 2000Out-of-sample tests of forecasting accuracy: an analysis and review1,014 cited
  • 1983Averages of Forecasts: Some Empirical Results622 cited
  • 2006Intuitions About Combining Opinions: Misappreciation of the Averaging Principle407 cited
  • 1999On the asymmetry of the symmetric MAPE329 cited

Cited by

  • 2019Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition309 cited
  • 2015Forecasting realized volatility in a changing world: A dynamic model averaging approach

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292 cited
  • 2022Forecast combinations: An over 50-year review286 cited
  • 2019Hybrid structures in time series modeling and forecasting: A review240 cited
  • 2005A comparative study of autoregressive neural network hybrids219 cited
  • 2007Tourism forecasting: To combine or not to combine?210 cited
  • 2020Demand forecasting in supply chain: The impact of demand volatility in the presence of promotion202 cited
  • 2014‘Horses for Courses’ in demand forecasting201 cited
  • 2014Improving forecasting by estimating time series structural components across multiple frequencies184 cited
  • 2016Financial time series prediction using a dendritic neuron model183 cited
  • 2019Economic policy uncertainty and the Chinese stock market volatility: Novel evidence167 cited
  • 2018Judgmental selection of forecasting models166 cited
  • 2011Combining linear and nonlinear model in forecasting tourism demand163 cited
  • 2013Combining forecasts: An application to elections160 cited
  • 2018Research on the peak of CO2 emissions in the developing world: Current progress and future prospect155 cited
  • 2019Forecasting in social settings: The state of the art145 cited