Pre-trained RNN models with global self-attention or sliding-window sparse attention deliver the highest value-weighted Sortino ratios (2.0 and 1.80) in a COVID-era backtest of 420 large-cap US stocks.
Centre for Financial Research (CFR), working paper (2020)
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Is attention truly all we need? An empirical study of asset pricing in pretrained RNN sparse and global attention models
Pre-trained RNN models with global self-attention or sliding-window sparse attention deliver the highest value-weighted Sortino ratios (2.0 and 1.80) in a COVID-era backtest of 420 large-cap US stocks.