NSE Post Market Analysis 1 min read 0.0 (0)

Factor Analysis: Early Ignition in ONGC

R
Ran
Posted on 19 Feb 2026, 11:14 PM
For educational study of price-volume behavior only. The Oil and Natural Gas Corporation Limited (ONGC) achieved a perfect score of 100/100 in our Institutional Factor Model. This score reflects a robust combination of trend strength, relative strength (RS) against its sector, and favorable volatility metrics. The strong trend indicates a positive price movement over time, while the relative strength showcases ONGC's performance compared to its peers. Additionally, the volatility assessment suggests a controlled price movement, which is conducive for potential breakout scenarios. The observed Volatility Contraction Pattern (VCP) indicates a 'Tight Base' with a tightness percentage of 14.7%. This level of tightness suggests that the stock has been consolidating within a narrow price range, which is often a precursor to significant price movements. The reduced volatility during this phase implies that the market is absorbing supply and demand, setting the stage for a potential breakout as the stock prepares to make a decisive move. In terms of risk management, the structural invalidation level is set at ₹252.68. This level serves as a stop-loss point, indicating that if the price were to fall below this threshold, it would invalidate the current bullish setup. Maintaining a disciplined approach to risk management is crucial, as it allows for the protection of capital while navigating potential market fluctuations. [{'Stock': 'ONGC', 'Score': 100}, {'Stock': 'HSCL', 'Score': 88}, {'Stock': 'NLCINDIA', 'Score': 88}]
⚠️ Institutional Analysis Disclaimer

This report is a quantitative factor analysis generated by FindNex's AI Engine. It identifies mathematical probabilities based on historical volatility and momentum factors. It is NOT a buy/sell recommendation. Trading involves substantial financial risk.

Filed under:
#Quantitative #Technical Analysis #Factor Model
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About Ran

Senior Market Analyst at FindNex. Specializes in Algorithmic Trading strategies and Technical Analysis.

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