AI model aims to boost stock price forecasting
AI model aims to boost stock price forecasting
Can AI forecast stock prices more reliably? A new study introduces NP-DNN, which pairs NeuralProphet (a time-series forecasting tool) with a deep neural network (multi-layer perceptron) to learn hidden patterns in market data.
- Clean the data: Z-score normalization removes scale differences so trends stand out.
- Fill the gaps: Missing values are imputed to make the history complete.
- Learn the signal: The MLP captures complex, non-linear relationships for stronger predictions.
In their experiments on historical prices, NP-DNN reportedly reached 99.21% accuracy, outperforming other tested approaches.
Read the paper: https://arxiv.org/abs/2601.05202v1
Note: Results are on past data and may not generalize. Not financial advice.
Paper: https://arxiv.org/abs/2601.05202v1
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AI finance stocks deep-learning time-series forecasting neuralprophet machine-learning research
