September 12, 2025Open Access

A Hybrid Model for Stock Price Forecasting Integrating XGBoost and LSTM with Financial Indicators

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This model achieves an R² above 0.99 with 98.25% directional accuracy, indicating high prediction performance.
XGBoost predicts daily closing prices using financial indicators while LSTM captures patterns for 22 days, showcasing effective short-term and multiday forecasting.
The model is based on over 1,600 Indian stocks, employing key financial features like Open, High, Low, and calculated financial ratios.
Performance is superior to traditional methods like ARIMA and Linear Regression, emphasizing the model's scalability and real-time application.

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This hybrid model demonstrates improved stock price forecasting accuracy in Indian markets, integrating xgboost and lstm financial indicators.

Dubey et al. (2025) studied this question.

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This hybrid model demonstrates improved stock price forecasting accuracy in Indian markets, integrating xgboost and lstm financial indicators.