Why Model Selection Fails in Time Series Forecasting: An Empirical Study of Instability Across Data Regimes
时间序列预测中的模型选择为何失效:跨数据状态的不稳定性
Time series forecasting models often exhibit inconsistent performance across datasets with varying statistical and structural properties. Despite the wide range of available forecasting techniques, it remains unclear whether model selection can be reliably guided by simple data characteristics. This paper investigates why rule-based model selection fails in time series forecasting by analyzing the relationship between data-regime descriptors and model performance. A…