Note—Sliding Simulation: A New Approach to Time Series Forecasting
提出一种新的时间序列预测方法，基于三个原则：模型选择依据样本外预测能力、并行运行多个模型并利用样本外信息选择、为每个预测水平单独优化模型。该方法在M竞赛的111个序列子样本上大幅优于最佳方法。
This paper proposes a new approach to time series forecasting based upon three premises. First, a model is selected not by how well it fits historical data but on its ability to accurately predict out-of-sample actual data. Second, a model/method is selected among several run in parallel using out-of-sample information. Third, models/methods are optimized for each forecasting horizon separately, making it possible to have different models/methods to predict each of the m horizons. This approach outperforms the best method of the M-Competition by a large margin when tested empirically with the 111 series subsample of the M-Competition data.