lilianweng/stock-rnn
Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
Supports both single-stock and multi-stock prediction modes, with optional learned embeddings to capture cross-stock relationships when training on multiple equities simultaneously. Built in TensorFlow with configurable LSTM depth and size, includes data fetching utilities for S&P 500 constituent stocks and historical pricing, and integrates TensorBoard for training visualization. Designed as a reference implementation emphasizing RNN architecture patterns in TensorFlow rather than optimizing prediction accuracy.
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Jul 28, 2022
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