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Time-varying Forecast Combination for High-Dimensional Data

Bin Chen, Kenwin Maung

arXiv 20 Oct 2020 · Econometrics · publishedJournal of Econometrics (2023) · 14 citations (OpenAlex)

arXiv:2010.10435 · PDF · DOI · OpenAlex · Extracted main text

Abstract

In this paper, we propose a new nonparametric estimator of time-varying forecast combination weights. When the number of individual forecasts is small, we study the asymptotic properties of the local linear estimator. When the number of candidate forecasts exceeds or diverges with the sample size, we consider penalized local linear estimation with the group SCAD penalty. We show that the estimator exhibits the oracle property and correctly selects relevant forecasts with probability approaching one. Simulations indicate that the proposed estimators outperform existing combination schemes when structural changes exist. Two empirical studies on inflation forecasting and equity premium prediction highlight the merits of our approach relative to other popular methods.

Citation extraction

49
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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Elliott, G., Timmermann, A (2005) Optimal forecast combination under regime switching1.00084100%
2Bates, J.M., Granger, C.W (1969) The combination of forecasts1.00063100%
3Chen, B., Hong, Y (2012) Testing for smooth structural changes in time series models via nonparametric regression self0.92844100%
4Li, D., Ke, Y., Zhang, W (2015) Model selection and structure specification in ultra-high dimensional generalised semi-varying coefficient models0.8749667%
5Robinson, P.M (1989) Nonparametric estimation of time-varying parameters0.84333100%
6Timmermann, A (2006) Chapter 4 forecast combinations0.84333100%
7Cai, Z (2007) Trending time-varying coefficient time series models with serially correlated errors0.8307357%
8Rapach, D.E., Strauss, J.K., Zhou, G (2010) Out-of-sample equity premium prediction: Combination forecasts and links to the real economy0.81142100%
9Deutsch, M., Granger, C.W., Teräsvirta, T (1994) The combination of forecasts using changing weights0.73732100%
10Diebold, F.X., Shin, M (2019) Machine learning for regularized survey forecast combination: Partially-egalitarian lasso and its derivatives0.73732100%

Showing the top 10 of 49 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
12107.125520.40511
2Econometrics of Machine Learning Methods in Economic Forecasting0.40511