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https://ah.lib.nccu.edu.tw/handle/140.119/139778
題名: | Optimal Multi-step VAR Forecast Averaging | 作者: | 廖仁哲 Liao , Jen-Che Tsay, Wen-Jen |
貢獻者: | 經濟系 | 日期: | 十二月-2020 | 上傳時間: | 11-四月-2022 | 摘要: | This article proposes frequentist multiple-equation least-squares averaging approaches for multistep forecasting with vector autoregressive (VAR) models. The proposed VAR forecast averaging methods are based on the multivariate Mallows model averaging (MMMA) and multivariate leave-h-out cross-validation averaging (MCVAh) criteria (with h denoting the forecast horizon), which are valid for iterative and direct multistep forecast averaging, respectively. Under the framework of stationary VAR processes of infinite order, we provide theoretical justifications by establishing asymptotic unbiasedness and asymptotic optimality of the proposed forecast averaging approaches. Specifically, MMMA exhibits asymptotic optimality for one-step-ahead forecast averaging, whereas for direct multistep forecast averaging, the asymptotically optimal combination weights are determined separately for each forecast horizon based on the MCVAh procedure. To present our methodology, we investigate the finite-sample behavior of the proposed averaging procedures under model misspecification via simulation experiments. | 關聯: | Econometric Theory, Vol.36, No.6, pp.1099-1126 | 資料類型: | article | DOI: | https://doi.org/10.1017/S0266466619000434 |
Appears in Collections: | 期刊論文 |
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