JordiCorbilla/stock-prediction-deep-neural-learning
TensorFlow LSTM-based deep learning repository for stock and cryptocurrency price forecasting.
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The project provides reproducible deep-learning experiments for financial time-series forecasting using TensorFlow LSTM models. It supports multiple target formulations including price, return, delta, and trend-residual, with multi-task architectures for direction and magnitude prediction. It includes walk-forward validation, naive baselines, directional accuracy metrics, transaction-cost-aware strategy diagnostics, and a CSV benchmark CLI for quantitative evaluation.
Frequently asked
- What is JordiCorbilla/stock-prediction-deep-neural-learning?
- TensorFlow LSTM-based deep learning repository for stock and cryptocurrency price forecasting.
- Is stock-prediction-deep-neural-learning open source?
- Yes — JordiCorbilla/stock-prediction-deep-neural-learning is open source, released under the Apache-2.0 license.
- What language is stock-prediction-deep-neural-learning written in?
- JordiCorbilla/stock-prediction-deep-neural-learning is primarily written in Python.
- How popular is stock-prediction-deep-neural-learning?
- JordiCorbilla/stock-prediction-deep-neural-learning has 689 stars on GitHub.
- Where can I find stock-prediction-deep-neural-learning?
- JordiCorbilla/stock-prediction-deep-neural-learning is on GitHub at https://github.com/JordiCorbilla/stock-prediction-deep-neural-learning.