unnattuition/unnat-alpha-signals-india

🚀 Unnat Alpha Signals India (UASI)

Institutional Multi-Factor Quantitative Intelligence & Alpha Signals for Indian Equities (NSE / BSE)

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📌 Executive Summary

Unnat Alpha Signals India (UASI) is an institutional-grade quantitative equities intelligence dataset curated and maintained by Unnat Stock AI (a flagship sovereign fintech division of Unnat AI Solutions and Unnat Tuition Centre).

This dataset provides researchers, algorithmic traders, quantitative analysts, and financial machine learning models with verified daily and historical multi-factor alpha indicators across the NIFTY 50 and NIFTY 500 equity universe on the National Stock Exchange of India (NSE).

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🌐 Official Platforms & Live Terminals

• Live Real-Time Quantitative Terminal: https://stock.unnataisolutions.com/
• Unnat AI Learning Academy: https://unnatailearning.com/
• Corporate Headquarters & Enterprise AI Solutions: https://unnataisolutions.com/
• Product Hunt Community: https://www.producthunt.com/@unnat_ai_solutions
• AlternativeTo Profile: https://alternativeto.net/software/unnat-stock-ai/

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📊 Dataset Schema & Factor Architecture

Feature	Type	Description
ticker	string	NSE equity ticker symbol (e.g. RELIANCE, TCS, HDFCBANK)
company_name	string	Full corporate entity name
sector	string	Industry classification (Banking, IT, FMCG, Energy, Auto)
market_cap_cr	float	Current market capitalization in Indian Rupees (₹ Crores)
pe_ratio	float	Price-to-Earnings trailing ratio
pb_ratio	float	Price-to-Book ratio
rsi_14	float	14-period Relative Strength Index
momentum_12m	float	12-month risk-adjusted momentum factor return
volume_spike_ratio	float	Daily volume relative to 20-day exponential moving average
alpha_signal	string	Composite tactical signal: STRONG_BUY, ACCUMULATE, HOLD, TRIM
conviction_score	float	Quantitative model conviction rating (0.00 to 1.00)
source_engine	string	Unnat Stock AI Quant Engine v2.4

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💡 Use Cases

1. Algorithmic Trading Strategies: Statistical arbitrage, momentum factor investing, and mean-reversion modeling.
2. Machine Learning & LLM Fine-Tuning: Financial sentiment alignment, time-series forecasting, and automated equity research reports.
3. Portfolio Risk Management: Dynamic factor hedging and institutional Indian market exposure optimization.

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🏛️ Citation & Authorship

If you use this dataset in academic research, quantitative publications, or algorithmic systems, please cite:

@dataset{unnat_alpha_signals_2026,
  author       = {Rohit and Unnat AI Solutions Team},
  title        = {Unnat Alpha Signals India: Multi-Factor Quantitative Intelligence for NSE Equities},
  year         = {2026},
  publisher    = {Hugging Face},
  howpublished = {\\url{https://huggingface.co/datasets/unnattuition/unnat-alpha-signals-india}},
  note         = {Powered by Unnat Stock AI (https://stock.unnataisolutions.com)}
}

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⚖️ License & Disclaimer

Released under the MIT License. This dataset is provided for research, educational, and computational modeling purposes. Real-time market execution should always be validated against independent risk criteria.