What actually moves Indian stocks — an evidence review
Every trading desk and Telegram channel has a confident answer to one question: what makes an Indian stock jump on a single day, and does the jump continue or fade? We took the most-repeated claims and checked them against the actual evidence — peer-reviewed studies on Indian markets, SEBI and exchange rules, and credible practitioner research — keeping only the claims that survived an adversarial review where each had to withstand independent attempts to refute it. Of 25 specific claims tested, 15 held and 10 were cut. Here is what stood up.
One framing matters before the details: every strong finding below points the same way — the durable edges in Indian equities are long-biased and catalyst-driven, while several popular "signals" turn out to be descriptive rather than predictive.
Corporate announcements: which catalysts actually move price
Buybacks are a real, positive signal (high confidence). Across large-cap announcements, buybacks generate statistically significant positive abnormal returns around the announcement window, consistent with the classic signalling story — management buying its own stock is read as a credible undervaluation message. The caveat for traders: a meaningful chunk of the move happens before the public announcement (consistent with leakage), so the clean, post-disclosure edge is smaller than the headline cumulative-return figures suggest.
Mergers and acquisitions are largely priced in (medium confidence). The abnormal returns around M&A cluster in a pre-announcement run-up — roughly 30 and again 10 days before the news — plus a positive announcement-day pop, after which acquirers tend to decay. In other words, by the time an acquisition is public, the market has mostly absorbed it. M&A is a poor "react on the headline" trade.
Post-earnings drift exists, but the Indian evidence is genuinely split (medium confidence, contested). The well-known IIT-Delhi study on the Nifty 500 finds significant post-earnings-announcement drift — positive-surprise stocks keep drifting up for weeks — and a long-short portfolio built on earnings surprise earned roughly 6% over ~64 trading days. But a separate peer-reviewed study reaches the opposite conclusion and finds the market efficient with respect to earnings. The supporting evidence also predates the post-2020 retail and derivatives surge. Treat earnings drift as a directional tendency, not a settled law.
Order wins, regulatory approvals, credit-rating changes and promoter buying are widely traded as catalysts, but we could not find dedicated, quantified India-specific studies for them — a genuine gap in the public evidence, and an area where a stock-specific measurement would add real value.
Gaps: catalyst and volume matter, size alone does not
A popular rule of thumb says "small gaps continue, big gaps reverse." At the index level, that did not survive: across roughly a decade of Nifty gap-down days, the open-to-close outcome is close to a coin flip with a tiny positive drift, and the claim that larger gaps fade more reliably was refuted on the same dataset.
What does hold up (high confidence on direction, weaker on magnitude) is the distinction between catalyst gaps and technical gaps. Gaps backed by a real catalyst — an earnings beat, an approval, a contract — attract volume and tend to follow through; gaps with no catalyst behind them tend to fill, often quickly. The practical implication is to gate on why the stock gapped and whether volume confirms it, not on the gap's size in isolation.
Volume and flow: separate the predictive from the descriptive
This is where several common beliefs broke down. Bulk- and block-deal disclosures, traded as if they carry exploitable signal, tested as descriptive only — the claim that they deliver 5–7% abnormal returns in the surrounding week was refuted across multiple phrasings. The one piece that did survive (high confidence) is an asymmetry: block purchases carry more permanent price impact and information than block sales, with evidence of front-running minutes before large buys but not before large sells. So the useful takeaway is a directional prior (buying is more informative than selling), not a tradable "a bulk deal happened" alert.
Foreign-investor flows chase returns; they confirm rather than lead (high confidence). Daily foreign equity flows follow recent Nifty returns — FIIs behave as positive-feedback (momentum) traders, while domestic institutions lean the other way. Flow data is therefore a lagging, confirming variable, not a clean leading predictor of the next move.
Market structure: the frictions that decide tradability
Two India-specific frictions matter enough to gate on. First, surveillance (high confidence): a stock placed under the Additional Surveillance Measure can be moved to Trade-to-Trade, which forces 100% delivery, removes intraday trading, and imposes large additional margins and tighter bands. A catalyst move on an ASM/GSM-flagged stock may simply be untradeable intraday — surveillance status has to be checked before acting on any signal.
Second, settlement (high confidence): India's move to T+1 cut counterparty risk but is out of step with most global markets, creating funding and securities-lending strain for foreign participants — though the introduction of an early confirmation deadline has largely mitigated the operational impact.
Long versus short: the asymmetry is structural
The single most consistent finding is that the long side works and the short side is structurally handicapped (high confidence). A long-only, monthly-rebalanced top-decile momentum portfolio on the Nifty 100 has outperformed the index by roughly 10.7% a year — and the long-only framing is a deliberate response to India's shorting constraints, not a simplification. On the other side, SEBI's own leadership has described the securities-lending-and-borrowing segment as "significantly underdeveloped": shorting is confined to about 100–125 liquid names with high borrow costs and forced closures around corporate actions. Layer on the SEBI finding that roughly nine in ten retail derivatives traders lose money, and the conclusion is hard to avoid — long-biased systems have a structural tailwind that short systems do not.
What did not survive the review
In the interest of transparency, the claims that were cut after independent verification:
- Bulk- and block-deal disclosures carry exploitable abnormal returns — refuted (descriptive only; the buy/sell asymmetry is the part that survives).
- "Larger gaps fade more," as a clean size-based rule — refuted at the index level.
- The Indian market is efficient with respect to earnings (no drift at all) — the anti-drift position lost the verification, leaving drift as the stronger, if contested, finding.
- F&O-eligible stocks have no price bands and move freely — refuted.
- Individual stocks face simple fixed 2/5/10/20% bands by tier — over-specified; band assignment is more nuanced.
How to read all of this
| Claim | Verdict | Confidence |
|---|---|---|
| Buyback announcements are a positive signal | Holds | High |
| M&A is largely priced in pre-announcement | Holds | Medium |
| Post-earnings drift in India | Holds, contested | Medium |
| Catalyst + volume gaps sustain; bare gaps fill | Holds | High |
| Long-only momentum outperforms | Holds | High |
| Block buys more informative than sells | Holds | High |
| FII flows lead the market | Reframed: they lag/confirm | High |
| Bulk-deal disclosures are tradable signal | Refuted | — |
| "Bigger gaps fade more" (size rule) | Refuted (index level) | — |
| Short setups work as well as longs | Refuted (structural) | — |
The honest limits: the strongest academic findings rest on samples ending around 2016–2019, before the retail and derivatives boom and the move to T+1 — none establishes that the edges persist unchanged in today's regime. The gap-behaviour evidence is the weakest tier, leaning on practitioner backtests rather than exchange data, and India-specific, stock-level gap measurements remain a gap worth filling. We flag confidence on each finding for exactly this reason: the direction of these effects is better established than their current magnitude.
Sources
- Post-Earnings-Announcement Drift Anomaly in India: A Test of Market Efficiency — Harshita, Singh & Yadav (IIT Delhi), 2018
- Share Buybacks and Abnormal Returns in Indian Large-Caps — Vyas & Patel (SSRN 3516889)
- Market Reaction to M&A Announcements in India — Marisetty & Koluru (SSRN 4597687)
- Momentum: Evidence from the Indian Stock Market (long-only NIFTY100) — Raju & Chandrasekaran, IIMA 2019
- Price Impact of Block Trades: Buy vs Sell Asymmetry — IIMB Management Review
- Foreign Institutional Flows and Indian Equity Returns (Granger causality) — PMC9145119
- India's Derivatives Market and Retail Investors (91% loss-making) — CFA Institute Market Integrity, 2025
- Securities lending 'significantly underdeveloped' — SEBI — Securities Finance Times
- What is ASM? Additional Surveillance Measure & Trade-to-Trade — Zerodha
- India introduces T+1 trade settlement — ION Group
- Nifty gap-down history analysis — IntradayLab
- Gap-and-go: why catalyst gaps follow through — TradeZella