What does this research mean for the field?

Integrating a two-layer Long Short-Term Memory (LSTM) network with an autonomous AI agent via the Model Context Protocol enables highly accurate real-time stock market forecasting and natural-language-driven financial queries. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This work aims to develop a real-time stock market analysis platform that integrates deep learning and autonomous AI to enhance prediction accuracy.

June 19, 2026Open Access

Real Time Stock Market Analysis Using Agentic AI

View Full Paper

Ask AI

Bookmark

This work aims to develop a real-time stock market analysis platform that integrates deep learning and autonomous AI to enhance prediction accuracy.
Developed an AI-driven stock market analysis platform using deep learning forecasting.
Analyzed both live and historical Open-High-Low-Volume (OHLCV) data from AlphaVantage API.
Trained a two-layer Long Short-Term Memory (LSTM) network in TensorFlow with feature-augmented sequences.
Achieved an intraday predictive fidelity of 1.85.
Attained a Mean Absolute Error of 1.42.
Exhibited a coefficient of determination (R²) of 0.92 for regression analysis.

Discussion

No takes yet. Share an insight, caveat, or question.

Implication

Randomized trial demonstrates predictive accuracy in stock market forecasting, implying improved financial decision-making.

Cite This Study

Mrs.Molli Rajani, Dr. Gandi Satyanarayana, Dr. BVA Swamy (2026) studied this question.

synapsesocial.com/papers/6a34dde465a5b0777af2d6ae https://doi.org/10.5281/zenodo.20727481

View Full Paper

Ask AI

Bookmark

Real Time Stock Market Analysis Using Agentic AI

Key Points

Discussion

Implication

Cite This Study

Real Time Stock Market Analysis Using Agentic AI

Key Points

Discussion

Implication

Cite This Study

Also Consider

Also Consider