Research: NSE Pre-Market Open Sentiment Dispersion

Methodology

We examined the NSE equity universe using pre-market open sentiment factors (S-Factors) derived from Twitter. To capture the breadth of participation in discussions, we focused on S-Dispersion, which measures the percentage of tweets coming from unique accounts (i.e., how diverse the sources of sentiment are). This metric falls between 0 and 1, where 1 represents 100% of the tweets come from unique accounts.

To smooth out daily noise, we computed a 7-day moving average of S-Dispersion. We then sorted securities into quintiles daily based on this rolling dispersion metric and tracked forward returns across each quintile. Returns were calculated from market open to the following market open.

Results

Our analysis shows a monotonic spread across the quintiles:

• Lower quintiles (low dispersion): Returns are weakest when discussion is concentrated among a smaller set of accounts.
• Higher quintiles (high dispersion): Returns improve steadily, with the top quintile (broadest participation) delivering the strongest performance.
• Quintile 5: Averaging S-Dispersion of 99% indicates that the portfolio of NSE securities where near all conversation is from unique accounts. This group significantly outperforms the others.

This indicates that stocks discussed by a more diverse set of accounts prior to the open tend to outperform those where sentiment is driven by a narrower, more concentrated group.

Takeaways

• Breadth matters: When sentiment comes from a wide range of unique sources, it reflects organic and distributed investor attention rather than being driven by a few dominant voices.
• Concentration risk: Low dispersion often reflects potential spam, coordinated chatter, or amplification from small communities, which does not translate into sustained price performance.
• Investor takeaway: Monitoring pre-market S-Dispersion provides a robust leading indicator of returns in the NSE universe, outperforming traditional raw volume or sentiment measures.

TL;DR:

Context Analytics analyzed pre-market sentiment dispersion on Twitter for NSE-listed stocks using its proprietary S-Dispersion metric. Results show that stocks with highly diverse pre-market discussion (high dispersion) outperform those with sentiment concentrated among few accounts. The top dispersion quintile showed the strongest next-day open-to-open returns, making S-Dispersion a valuable early signal for traders.