deepdow merges portfolio optimization with deep learning by constructing pipelines of differentiable layers. Feature extractors (such as LSTM networks) process market data, and a final allocation layer produces portfolio weights. The entire network is trained via gradient descent to find optimal buy-and-hold weight allocations.