Pretrained TTM shows large transfer and sample-efficiency gains in three financial forecasting tasks relative to training from scratch, but methodological flaws including possible look-ahead bias weaken the quantitative claims.
A combination of artificial neural network and random walk models for financial time series forecasting,
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Time Series Foundation Models for Multivariate Financial Time Series Forecasting
Pretrained TTM shows large transfer and sample-efficiency gains in three financial forecasting tasks relative to training from scratch, but methodological flaws including possible look-ahead bias weaken the quantitative claims.