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This research aims to develop an AI framework for enhancing stock market predictions and portfolio analysis for retail investors.

July 1, 2026Iconic Research and Engineering Journals

Stocksage AI: An Intelligent Explainable Deep Learning Framework for Stock Market Prediction and Portfolio Analysis

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This research aims to develop an AI framework for enhancing stock market predictions and portfolio analysis for retail investors.
Developed StockSage AI combining LSTM networks and Linear Regression for stock predictions.
Utilized technical indicators like RSI, MACD, and SMA for feature extraction from real-time data.
Implemented portfolio management to calculate capital gains taxes according to Indian rules.
LSTM model demonstrated superior prediction accuracy compared to conventional regression models.
Achieved low inference latency while providing explainable AI insights.
Effective in predicting prices for both established and newly listed stocks.

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Randomized trial evaluates stock market prediction and portfolio analysis in retail investors, suggesting improved decision-making tools.

Priya et al. (2026) studied this question.

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