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LSTM-Based Stock Price Prediction Model by Lie Po is a document available to read on EtoBox.

The document presents a novel stock price prediction model using the Long Short-Term Memory (LSTM) algorithm to assist investors in making informed decisions amidst dynamic market conditions. The model demonstrates high accuracy with low error rates, achieving RMSE and MAPE values that indicate its effectiveness in predicting stock movements. The paper outlines the methodology, experimental setup, and contributions of the proposed model in addressing challenges in stock price forecasting.

Author
Lie Po
Language
EN