Optimal model averaging based on forward-validation

Xiaomeng Zhang and Xinyu Zhang

Journal of Econometrics, 2023, vol. 237, issue 2

Abstract: In this paper, noting that the prediction of time series follows the temporal order of data, we propose a frequentist model averaging method based on forward-validation. Our method also considers the uncertainty of the window size in estimation, i.e., we allow the sample size to vary among candidate models. We establish the asymptotic optimality of our method in the sense of achieving the lowest possible squared prediction risk. We also prove that if there exists one or more correctly specified models, our method will automatically assign all the weights to them. The promising performance of our method for finite samples is demonstrated by simulations and an empirical example of predicting the equity premium.

Keywords: Model averaging; Forward-validation; Asymptotic optimality; Forecasting; Minimum risk; Window size (search for similar items in EconPapers)
JEL-codes: C22 C53 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:237:y:2023:i:2:s030440762200094x

DOI: 10.1016/j.jeconom.2022.03.010

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