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Empirical Market Study

IPO Subscription Demand and Listing-Day Returns:
Evidence from 30 Mainboard IPOs (Study A 2025 Cohort)

An institutional-grade empirical analysis evaluating the statistical association between primary market bidding demand, investor category dynamics, and listing-day price behavior on the National Stock Exchange.

August 2026 Research Report 12 min read (2,500+ words)

Short Answer / Key Empirical Finding

In our empirical study of 30 Mainboard IPOs listed between January and July 2025 in the Study A sample, overall primary market subscription demand showed a strong, statistically significant positive association with listing-day initial returns (Spearman rank correlation ρ = 0.7071 for Open Return, and ρ = 0.7775 for Close Return).

Among all investor segments, QIB demand outside Anchor allocations showed the strongest observed rank association with listing returns (ρ = 0.7468 Open, ρ = 0.7677 Close), followed by High Net-Worth Individuals (bNII ρ = 0.6912, sNII ρ = 0.6925) and Retail investors (ρ = 0.5826 Open, ρ = 0.6356 Close).

However, subscription should be treated as one signal rather than a guarantee of listing gains. In the < 2x demand bucket (N=3), all 3 IPOs closed below issue price on listing day (median close return of -5.83%).

1. What We Studied

Every IPO investor closely monitors published subscription multiples during the book-building window. Whether applying as a retail individual or a high net-worth investor, market participants frequently use oversubscription figures as a primary gauge of listing-day sentiment. However, retail market commentary often conflates total subscription multiples with guaranteed listing profits.

To establish a rigorous empirical baseline, Digital Arthalaya conducted Study A: Institutional & Public IPO Subscription vs. Listing Day Returns. This quantitative research project audits 30 Mainboard IPOs listed on the National Stock Exchange (NSE) between January 1, 2025, and July 30, 2025, verifying every bid and trade against official regulatory sources including the Lead Manager Basis of Allotment documents and official NSE Bhavcopy trade ledgers.

Sample Size 30 Mainboard IPOs in Cohort
Median Public Demand 32.81x Range: 1.29x to 232.41x
Median Open Return 10.83% Range: -8.86% to 49.79%
Median Close Return 11.50% Range: -8.73% to 53.10%

Across the 30 analyzed issues, initial opening performance exhibited broad positive breadth: 22 IPOs opened at a premium to issue price, 4 opened flat (0.00% return), and 4 opened at a discount.

2. How Subscription Demand Was Defined

In standard financial media reports, the headline subscription multiple often blends Anchor investor commitments with general public bidding. Because Anchor investors are allocated shares at a fixed price prior to public issue opening, including their allocation in public demand ratios alters the competitive bidding ratio.

To accurately capture genuine competitive market bidding, we defined the Canonical Public Market Demand Multiple as:

Canonical Public Demand Multiple = (Total Shares Applied Pre-Rejection − Anchor Shares Applied) ÷ (Total Shares Offered − Anchor Shares Reserved)

This definition isolates competitive bids submitted across Retail, Non-Institutional (HNI), and Qualified Institutional Buyer (QIB) categories prior to technical rejections by registrars.

3. Main Result: Canonical Demand vs. Listing Performance

Primary Confirmatory Statistical Tests

To assess the monotonicity of the relationship without making restrictive parametric assumptions about normality or linearity, we utilized the Spearman rank correlation coefficient (ρ) with family-wise multiplicity control via the Holm-Bonferroni step-down procedure.

Primary Relationship Sample (N) Spearman ρ Raw p-Value Holm p-Value 95% Bootstrap CI Permutation p Status
Demand vs. Listing Open Return 30 0.7071 0.000012 0.000012 [0.5086, 0.8151] 0.000010 Statistically Significant
Demand vs. Listing Close Return 30 0.7775 < 0.000001 0.000001 [0.5858, 0.8779] 0.000010 Statistically Significant

Statistical Robustness Summary:

  • Resampling Confidence Intervals: 20,000 paired bootstrap resamples produced empirical 95% confidence intervals bounded strictly away from zero ([0.5086, 0.8151] for Open Return and [0.5858, 0.8779] for Close Return).
  • Permutation Support: 100,000 Monte Carlo random permutations yielded an empirical p-value of 0.000010 for both listing open and close returns, confirming that the observed co-movement is highly unlikely to arise from random chance.
  • Linear Sensitivity: Raw Pearson correlation was 0.6221 (Open) and 0.7023 (Close). When transformed via log10(Demand), Pearson correlation increased to 0.6888 (Open) and 0.7510 (Close).
  • Comparative Strength: The observed rank association was stronger for Close Return than Open Return in this sample.

Parametric Regression Modeling (OLS with HC3 Standard Errors)

To evaluate explanatory power, we fitted Ordinary Least Squares (OLS) models on log10(Demand) using MacKinnon-White HC3 heteroskedasticity-consistent standard errors:

  • Opening Return Model (O1): Estimated slope β = 13.23 (R2 = 0.4745, HC3 p = 0.000004). In this linear specification, each unit increase in log10(Demand) was associated with an average 13.23 percentage point higher opening return.
  • Closing Return Model (C1): Estimated slope β = 16.13 (R2 = 0.5640, HC3 p < 0.000001). The model explains approximately 56.40% of the cross-sectional variance in closing returns.

4. Secondary Analysis: Investor Category Breakdown

A central question for market observers is whether bidding across distinct investor quotas carries varying degrees of informational correlation with listing returns. We evaluated the independent demand multiples across five full-universe investor segments under Benjamini-Hochberg False Discovery Rate (BH-FDR) control across the M=10 secondary hypothesis family:

Investor Category Definition / Criteria Open Return ρ Close Return ρ BH-FDR q-Value Observed Association
QIB (ex-Anchor) Qualified Institutional Buyers (Competitive Bids) 0.7468 0.7677 q < 0.00002 Strongest Observed
bNII (Big HNI) Non-Institutional Applications > ₹10 Lakh 0.6492 0.6912 q < 0.00020 Strong
sNII (Small HNI) Non-Institutional Applications ₹2 Lakh to ₹10 Lakh 0.6296 0.6925 q < 0.00022 Strong
NII Total Combined Non-Institutional Bidding 0.6403 0.6850 q < 0.00020 Strong
Retail Individual Applications up to ₹2 Lakh 0.5826 0.6356 q < 0.00073 Moderate-Strong

Category Key Takeaways:

  • Institutional Co-Movement: QIB ex-Anchor showed the strongest observed rank association among the five tested full-universe investor categories (ρ = 0.7468 Open, ρ = 0.7677 Close).
  • HNI Bidding: Both Big HNI (bNII) and Small HNI (sNII) categories exhibited strong rank co-movement (ρ ≈ 0.69 with Close Returns).
  • Retail Participation: Retail bidding demand demonstrated statistically significant positive co-movement (ρ = 0.5826 Open, ρ = 0.6356 Close), though numerically lower than institutional multiples.

Exploratory Subsets: Employee & Shareholder Quotas

Special reserved quotas were analyzed under explicit exploratory framing:

  • Employee Reservation (N=12 Applicable, Exploratory): Evaluated across the 12 IPOs in the sample that included employee quotas. Spearman rank correlation was 0.2324 with Open Return (p = 0.47) and 0.0699 with Close Return (p = 0.83). In this exploratory subset, employee bidding did not establish a statistically strong rank relationship with public listing returns.
  • Shareholder Quota (N=2 Applicable, Descriptive Only): Only 2 IPOs in the 30-issue sample featured parent-company shareholder reservation quotas. Because an N of 2 is insufficient for inferential statistical testing, shareholder quota performance is reported descriptively only with zero inferential tests conducted.

5. Descriptive Demand-Bucket Distribution

To provide practical perspective for investors, the 30 IPOs were categorized into five discrete demand brackets. These bucket partitions serve as descriptive summaries of the sample cohort and were not the primary inferential test:

Demand Bracket IPOs (N) Median Open Return Median Close Return Positive Open % Positive Close % Sample IPOs in Cohort
< 2x (Cold) 3 1.18% -5.83% 66.7% 0.0% AGARWALEYE, QPOWER, ATHERENERG
2x to < 10x (Mild) 6 0.00% 2.98% 33.3% 66.7% AJAXENGG, THELEELA, KALPATARU
10x to < 50x (Moderate) 8 11.11% 9.35% 75.0% 75.0% BELRISE, OSWALPUMPS, HDBFS
50x to < 100x (Hot) 5 14.71% 25.56% 80.0% 100.0% PROSTARM, SCODATUBES, CRIZAC
≥ 100x (Blockbuster) 8 26.64% 28.63% 100.0% 100.0% INDOFARM, QUADFUTURE, LAXMIDENTL

Descriptive Cohort Observations: In this sample, all 13 IPOs with canonical demand of 50x or more closed above issue price on listing day, while 12 of 13 opened above issue price. Conversely, in the < 2x subscription bracket, all 3 IPOs closed below issue price on Day 1 (median close return of -5.83%).

6. Practical Insights for IPO Investors

What the Study Demonstrates:

  • Subscription as an Informative Signal: In this 30-IPO Study A cohort, higher canonical public subscription demand was strongly associated with stronger listing-day Open and Close returns.
  • QIB Demand as a Key Indicator: QIB ex-Anchor demand showed the strongest observed rank correlation with listing-day returns (ρ = 0.7468 Open, ρ = 0.7677 Close) among all tested investor categories.
  • Downside Skew in Sub-2x Issues: Low competitive subscription (< 2x) was associated with negative listing closes across all three sample occurrences.

What the Study Does NOT Demonstrate (Important Cautions):

  • No Guarantee of Listing Profits: Subscription is an observational summary of submitted bids, not a guarantee of listing-day capital gains.
  • General Investment Considerations (Not tested in Study A): Company valuation, business fundamentals, balance sheet health, promoter governance, and broader stock market sentiment remain essential investment considerations that can influence post-listing performance regardless of initial subscription multiples.
  • Retail Allotment Reality: Very high subscription generally reduces the probability that an individual retail application receives an allotment. Applying for heavily oversubscribed IPOs involves lottery allocation risk.

7. Study Methodology & Limitations

Methodology Framework

  • Study Cohort: 30 Mainboard IPOs in the frozen Study A 2025 cohort listed on NSE between January 1, 2025, and July 30, 2025.
  • Exclusions: SME IPOs, REITs, InvITs, debt public issues, and follow-on offers (FPOs).
  • Data Provenance: 100% verified against official NSE Bhavcopy trade records and registrar Basis of Allotment filings.
  • Quartile Computation: Quartiles were computed using the study's predefined discrete rank-index rule without interpolation.

Boundary Conditions & Limitations

  1. Sample Size (N=30): While finite-sample permutation tests confirm statistical robustness, the sample reflects 30 issues within a specific 7-month calendar period.
  2. Market Regime Exposure: The findings reflect Indian equity market liquidity and market conditions during early 2025. Results may vary under protracted bear market regimes.
  3. Observational Association (Non-Causal): Statistical correlation does not establish causality. Unobserved factors (e.g., sector momentum, brand recognition) may simultaneously drive both subscription and listing performance.
  4. Mainboard Specificity: Findings apply strictly to the analyzed Mainboard sample and cannot be generalized to SME IPOs.
  5. Single-Day Time Horizon: Evaluates initial listing-day returns only (Open and Close). Does not evaluate medium- or long-term post-listing holding returns.

Research & Regulatory Disclaimer: This article is for educational and research purposes only and is not investment advice. Past listing-day performance does not guarantee future results. Securities investments are subject to market risks. Investors must review the official Red Herring Prospectus (RHP) filed with SEBI and consult a registered investment advisor before making financial decisions.

Frequently Asked Questions (FAQ)

Q1: Does high IPO subscription guarantee a positive listing gain?
No. While high subscription was strongly associated with positive listing returns in this 30-IPO sample, subscription multiple is an observational measure of submitted bidding volume and does not guarantee listing-day profit.

Q2: Which investor category had the strongest correlation with listing performance?
In this 30-IPO cohort, QIB demand outside Anchor allocations showed the strongest observed rank association with listing returns (Spearman ρ = 0.7468 for Open Return and ρ = 0.7677 for Close Return).

Q3: How did IPOs with less than 2x subscription perform on listing day?
In the sample of 30 IPOs, all 3 IPOs in the < 2x demand bucket closed below their issue price on listing day, recording a median close return of -5.83%.

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Partner Disclosure: Some account-opening links on this page are referral links. Digital Arthalaya may receive a referral benefit if you use them. This does not affect the research findings presented above. Apply for Mainboard & SME IPOs on Upstox Explore IPO Hub Portal