Chapter 4 Forecast Combinations

By Allan G. Timmermann. 2006

740 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

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Citations in the corpus

FFORMA: Feature-based forecast model averaging (2020, background): “There has been a vast literature on the latter motivated by the seminal work of Bates & Granger (1969) and followed by a plethora of empirical applications showing that combination forecasts are often superior to their individual counterparts (see, Clemen 1989; Timmermann 2006, for example).”
Forecast combinations of computational intelligence and linear models for the NN5 time series forecasting competition (2011, background): “Since then, there have been many developments in the field, and several review articles have appeared (Clemen, 1989; de Menezes, Bunn, & Taylor, 2000; Diebold & Lopez, 1996; Timmermann, 2006).”
Manager sentiment and stock returns (2019, methodology): “In the same spirit, Timmermann (2006) and Rapach, Strauss, and Zhou (2010) find that the simple “1/N”-weighted combination forecast often beats forecasts with sophisticated optimally estimated weights in environments with complex and constantly evolving data generating processes.”
Forecasts of US Short-Term Interest Rates: A Flexible Forecast Combination Approach (2005, methodology): “…the forecast combination literature by proposing a flexible combination approach that extends earlier work in the combination literature by Bates and Granger (1969), Diebold and Pauly (1987), Deutsch, Granger and Terasvirta (1994), Stock and Watson (2001, 2005) and Aiolfi and Timmermann (2006).”
Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models (2019, background): “Some research has demonstrated that forecast combinations tend to improve the forecast accuracy (Timmermann, 2006).”
A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition (2011, background): “…Chapelle and Vapnik, 2000), eﬀect of deseasonalization (Hylleberg, 1992; Makridakis et al., 1998; Nelson et al., 1999; Zhang and Qi, 2005), forecasts combination (Bates, J. M. and Granger, C. W. J., 1969; Clemen, 1989; Timmermann, 2006) and many other critical topics (Gooijer and Hyn-dman, 2006).”
Forecasting with temporal hierarchies (2017, methodology): “…investigated, resulting in various sophisticated weighting methods (see Newbold and Granger, 1974; Min and Zellner, 1993; Elliott and Timmermann, 2004, 2005); yet, simple approaches, such as the unweighted average, are found to perform as well as more sophisticated approaches (Timmermann, 2006).”
Fused Estimators of the Central Subspace in Sufficient Dimension Reduction (2014, background): “There have been many studies on forecast combinations since Bates and Granger (1969), see Timmermann (2006) for an overview.”
Optimal combinations of realised volatility estimators (2009, background): “Motivated by the success of combination forecasts over individual forecasts in a range of forecasting applications (see Clemen, 1989, and Timmermann, 2006, for example), this paper sought to answer the question: do combinations of individual estimators offer accuracy gains relative to individual…”