It is well known that model selection via cross validation can be biased for time series models. However, many researchers have argued that this bias does not apply when using cross-validation with vector autoregressions (VAR) or with time series models whose errors follow a martingale-like structure. I show that even under these circumstances, performing cross-validation on time series data will still generate bias in general.

翻译：众所周知，通过交叉验证进行模型选择对于时间序列模型可能存在偏差。然而，许多研究者认为，当对向量自回归（VAR）模型或误差服从类鞅结构的时间序列模型使用交叉验证时，这种偏差并不适用。本文证明，即使在这些条件下，对时间序列数据执行交叉验证通常仍会产生偏差。