Retail Investor Participation In Initial Public Offerings: An Empirical Analysis Of Decision-Influencing Factors

The Indian capital market has witnessed significant growth supported by a buoyant IPO market, rising demat accounts, digitisation of public infrastructure and the availability of low-cost broking and investment platforms. The research study places the growth of retail participation in the context of the increasing number of investors and the large number of IPO applications. An Initial Public Offering is the offering of shares of a company to the public for the first time and their subsequent listing on stock exchanges.

The study focuses on the individual investor decision-making process rather than relying only on macro-level indicators such as demat accounts and subscription multiples. It examines what motivates or deters retail investors from participating in IPOs, where they obtain information, the role of financial literacy and the behavioural biases that may affect subscription and post-allotment decisions.

The research identifies retail participation as an important feature of the changing Indian primary market. The RII category provides a relatively low barrier to entry into the capital market through a capped application size and lottery-based allotment in case of oversubscription. The study notes that primary-market fundraising and retail subscription activity have increased, but high subscription levels do not by themselves reveal whether retail investors are adequately informed.

The research also highlights financial literacy and behavioural issues. The study cites the SEBI Investor Survey and the SEBI research note on large individual investors to show differences in market participation, financial-market knowledge and post-listing selling behaviour. Flipping and the disposition effect are identified as important behavioural concerns. These observations form the background for examining retail investors at the individual decision-making level.

BACKGROUND AND CONTEXT OF THE STUDY

The capital markets of India have witnessed significant growth over the years due to a buoyant IPO market, rising demat accounts and growing derivatives trading. The research records that the market capitalisation of the Bombay Stock Exchange increased from around ₹101 lakh crore in financial year 2014–15 to ₹4,701 lakh crore as of October 2025, while mutual fund assets increased around 6.5 times from ₹12 lakh crore in 2015 to almost ₹79 lakh crore as of September 2025. The research attributes this growth to the deepening of the formal financial sector, digitisation of public infrastructure such as UPI and Aadhaar-based e-KYC, and the availability of low-cost broking and investment platforms that reduced barriers to market entry.

The rise in demat accounts is used in the research as an indicator of deepening retail participation. There were around 21 crore demat accounts in India in 2025, with Karnataka accounting for around 9.14% of the total. The combined number of accounts held by NSDL and CDSL crossed 210 million as of October 2025. The research further reports that by May 2026 CDSL had 183.8 million accounts and NSDL had 45.1 million accounts, taking the combined total to 228 million. This growth in demat accounts provides the infrastructure through which a large number of retail investors can apply for IPOs.

An IPO is the offering of shares of a company to the public for the first time and their subsequent listing on stock exchanges. The research describes the book-built issue allocation under SEBI’s Issue of Capital and Disclosure Requirements framework as 50% for Qualified Institutional Buyers, at least 15% for Non-Institutional Investors or High Net Worth Individuals, and 35% for Retail Individual Investors. An RII is a resident individual, NRI or Hindu Undivided Family applying for shares up to ₹2 lakh in a given issue. Where the retail portion is oversubscribed, allotment is made through a computer-generated lottery, creating a relatively low barrier to entry but also a strong possibility of non-allotment.

The research records strong primary-market activity. In 2025, 103 companies raised around ₹1.76 lakh crore through mainboard IPOs, compared with 91 companies raising around ₹1.6 lakh crore in 2024. Including SME-platform issues, fundraising reached ₹1.95 lakh crore through 373 issues. The median subscription multiple for the year was reported at 22 times. The ₹11,605-crore IPO of LG Electronics India received more than 65 lakh applications. At the same time, median listing-day return for mainboard issues was reported at 3.8% compared with 15.2% in 2024, and some heavily subscribed issues listed at a discount to their issue price. The research therefore highlights a gap between enthusiasm at the subscription stage and the eventual listing performance.

The study also uses SEBI’s Investor Survey 2025 to show that market participation remains limited relative to awareness. The survey was based on 91,950 households and reported that 63% of India’s approximately 33.72 crore households were aware of at least one securities-market product, but only 9.5% of total households invested in at least one and 8.5% held a demat account. Urban household penetration was reported at 15% compared with 6% for rural households; male participation was 11% compared with 7% for females; and penetration for the top socio-economic group was 24% compared with 2% for the NCCS C/D/E category. Only 36% of participating households were reported to have high or medium financial-market knowledge.

The financial-literacy context is further supported in the research through National Centre for Financial Education data indicating that 27% of Indians were financially literate, with urban residents at 33% and rural residents at 24%. The research notes that India’s composite score of 11.9 was below the G20/OECD group score of 12.7 in the cited survey. These findings provide the background for examining whether retail IPO decisions are based on financial understanding or alternative information cues.

The behavioural dimension is particularly important. The research cites SEBI’s 2024 analysis of 144 mainboard IPOs listed between April 2021 and December 2023. Individual investors sold 50.2% of their shares by value within one week of listing and 70% within one year. The same research reported that individuals sold 67.6% of shares within a week when listing return exceeded 20%, while only 23.3% were sold within a week when the listing return was negative. Almost half of the demat accounts applying for IPOs during this period were newly opened in 2021–23. These patterns motivate the study’s focus on flipping, the disposition effect, financial literacy and the difference between subscription decisions and post-allotment decisions.

PROBLEM STATEMENT

• Though IPO markets in India are experiencing record fundraising and oversubscription, it does not necessarily mean that retail investors are well-read and well-informed before investing in initial public offers.

• SEBI findings indicate that many families do not have adequate financial literacy and only a proportion invest in IPOs.

• Retail investors exhibit behavioural biases including flipping and the disposition effect in IPOs.

• There is a dichotomy between macro-level metrics such as subscription multiples and demat accounts and the micro-level decision-making process.

• Existing literature describes investor awareness and literacy to an extent, but the research attempts to consider demographics, financial and non-financial indicators, information sources and behavioural biases together in the IPO context.

RESEARCH OBJECTIVES

1. To identify the demographic and socio-economic characteristics of retail investors in IPO.

2. To determine the factors, both financial and non-financial, influencing the retail investor’s participation in IPO.

3. To assess the role played by information sources in case of retail investor IPO subscription.

4. To analyse the behavioural biases, influencing subscription decisions for IPO, in case of retail investors.

RESEARCH QUESTIONS

1. What demographic factors (age, gender, educational attainment, occupation and income) and socio-economic status (urbanization level, investing experience and portfolio concentration) are associated with typical retail IPO investors?

2. What financial (subscription price, valuation, subscription level, grey-market premium, anchor investors’ subscription and fundamental value) and non-financial (brand image, promoter reputation, peer effects and media coverage) factors have the most significant impact on retail investors’ IPO subscription choices?

3. What information sources do retail investors use to make IPO subscription decisions, and how does their financial literacy affect both the information they use and the quality of their subscription decisions?

4. What behavioural biases do retail IPO investors exhibit, and how do these biases differ between IPO subscription and post-allotment decision-making?

SCOPE OF THE STUDY

• The study is confined to Retail Individual Investors (RIIs) who have applied for shares of up to ₹2 lakh in a given IPO.

• The study focuses on main board IPOs, as opposed to SME-platform IPOs.

• The study uses questionnaire data from investors who have applied for at least one IPO and uses secondary data for background and variable exploration.

• The scope is limited by respondent availability, research geography, time, resources and the requirements of completing an MBA dissertation.

• The study focuses on demographic, financial and non-financial factors, information sources, financial literacy and behavioural biases influencing retail IPO participation.

SIGNIFICANCE OF THE STUDY

The research is relevant to individual investors, regulators and market infrastructure institutions, issuers and merchant bankers, broking houses and financial technology companies, researchers and policymakers. For individual investors, the study identifies issues such as herd mentality, quick-sale behaviour and loss persistence. Regulators and market institutions can use the findings for investor education and awareness. Issuers and merchant bankers can identify factors that attract or repel individual investors, while brokers and fintech companies can use the findings to improve digital platforms and advisory services in line with investor literacy and information needs.

REVIEW OF LITERATURE

The reviewed studies collectively emphasise that IPO participation is influenced by pricing, market sentiment, risk perception, financial self-efficacy, social influence, GMP and behavioural tendencies. The literature also points to differences between retail and institutional investors in terms of information, investment horizon and reliance on fundamentals.

REVIEW OF LITERATURE

RESEARCH GAP

• Existing literature provides risk perception and literacy, but there is a need to develop a profile of retail IPO investors using characteristics such as age, income, occupation and experience.

• Previous studies examine pricing, GMP and herding independently; this research considers financial and non-financial factors together.

• Studies on financial literacy or information sources separately do not explain how these factors relate to social media, herding, personal networks and IPO subscription.

• Existing research considers subscription but does not go as deeply into post-allotment holding and exit strategies; this study considers post-allotment behaviour.

THEORETICAL FRAMEWORK

HYPOTHESES DEVELOPMENT

H1 (Financial factors): At least one of GMP, perceived valuation and company fundamentals significantly influences investor satisfaction in IPO decision-making.

H0 (Financial factors): GMP, perceived valuation and company fundamentals have no significant influence on investor satisfaction in IPO decision-making.

H1 (Digital factors): At least one of recommendations, access to IPO data in real time and mobile trading applications significantly influences investor satisfaction in IPO decision-making.

H0 (Digital factors): Recommendations, access to IPO data in real time and mobile trading applications have no significant influence on investor satisfaction in IPO decision-making.

H1 (Income groups): There are significant differences in IPO participation behaviour across annual income groups.

H0 (Income groups): There are no significant differences in IPO participation behaviour across annual income groups.

H1 (Correlation): There are significant positive correlations between institutional investor subscription, social recommendations, financial influencers and overall investor sentiment.

H0 (Correlation): There is no significant correlation between institutional investor subscription, social recommendations, financial influencers and overall investor sentiment.

RESEARCH METHODOLOGY

Research Design

The study employed a descriptive research design with an analytical component. It is descriptive because it describes the profile of respondents and their overall attitude towards IPOs. It is analytical because it attempts to establish relationships between selected variables such as behavioural tendencies, information sources, demographic profile and IPO purchasing intention using inferential statistics. The study is cross-sectional and does not make causal inferences.

Methodological Approach

The study is quantitative in nature. Data were collected through a close-ended questionnaire using a five-point Likert scale to measure investor attitudes, perceptions and behaviour towards IPOs. Statistical data were coded and entered for analysis using SPSS and descriptive analysis was also performed using MS Excel.

Population and Sampling Frame

The population comprised retail investors who make investments with personal savings and have applied, or are eligible and willing to apply, for an IPO. It covers past applicants and potential applicants with a demat and trading account and knowledge about IPO investing. Since there is no comprehensive database tracking every retail investor and new investors are continuously added, the population was treated as unknown/infinite.

The sampling frame consisted of retail investors contacted through online brokerage and trading platforms, investment-related social media groups and forums, and personal and professional networks. A screening question confirmed whether respondents invest or have ever invested in an IPO.

Sampling Technique and Sample Size

Probability sampling was not used because the complete population list was not accessible. Convenience sampling was combined with snowball sampling. The minimum sample size was calculated using Cochran’s formula for an infinite population: n = Z²pq/e². The study selected a 90% confidence level (Z = 1.645), p = 0.5, q = 0.5 and a 7% margin of error (e = 0.07), producing a minimum sample size of 138. The final analysis contained 141 responses.

Sampling Unit

The sampling unit was an individual retail investor, an adult person aged 18 years or older with a demat and trading account who had applied for an IPO in the past or was likely to apply in the future. Each completed questionnaire represented one sampling unit.

VARIABLES AND MEASUREMENT FRAMEWORK

The research integrates demographic, financial, non-financial, informational and behavioural dimensions. Demographic and socio-economic variables include age, gender, educational attainment, occupation, annual income and investment experience. IPO-specific financial variables include perceived valuation, QIB subscription, company fundamentals, GMP and firm size. Non-financial and digital variables include social recommendations, consumer-brand influence, mobile trading applications, real-time IPO information and overall investor sentiment. Behavioural dimensions include herding, overconfidence, risk perception, flipping and the disposition effect.

The dependent outcomes considered in the analysis include investor satisfaction, IPO participation behaviour, investment decision-making and post-allotment behaviour. The research does not treat these outcomes as causal consequences of the independent variables; rather, it uses descriptive and inferential analysis to identify associations and significant predictors within the sample.

The questionnaire used a five-point Likert scale to capture attitudes, perceptions and behaviour. This allowed the study to convert respondents’ perceptions into quantitative observations that could be summarised using frequencies, percentages and inferential tests. The reliability test was conducted before hypothesis testing, supporting the internal consistency of the scale.

For the financial-factor hypothesis, GMP, perceived valuation and company fundamentals were treated as explanatory variables and investor satisfaction as the outcome. For the digital-factor hypothesis, peer/influencer recommendations, real-time IPO information and mobile trading applications were treated as explanatory variables. Annual income groups were compared for differences in IPO participation behaviour using one-way ANOVA. Correlation analysis examined the relationships among institutional investor subscription, social recommendations, financial influencers and overall investor sentiment.

The operational structure ensures that each research objective is connected to an observable set of variables. The first objective is addressed through respondent characteristics and descriptive statistics. The second objective is addressed through financial and non-financial factor analysis. The third objective is addressed through information-source and digital-factor analysis. The fourth objective is addressed through behavioural and post-allotment questions together with inferential analysis.

DATA COLLECTION AND ANALYSIS

Data Collection

Primary data were collected through a structured questionnaire distributed through online sources. The questionnaire was circulated through brokerage and trading platforms, investment-related social media groups and forums, and personal and professional networks. No secondary data were gathered for hypothesis testing; secondary information was used for background and variable exploration.

Research Instrument

• Demographic profile: age, gender, income, education and investment experience.

• IPO-specific factors: grey market premium, subscription level, issue price, company reputation and anchor investor participation.

• Behavioural factors: herd behaviour, overconfidence and risk perception.

• Information sources: broker advice, financial media, social media, friends/family and related information channels.

• A screening question was used to confirm respondent relevance.

Ethical Considerations

• Informed consent: participants were made aware of the research objectives.

• Voluntariness: participants could withdraw or decline to answer.

• Anonymity and confidentiality: identifiers were kept confidential and data were analysed only for research purposes.

• No coercion or inducement was used.

• Data were used only for research purposes.

Data Analysis Plan

Descriptive statistics including frequency, percentage, mean and standard deviation were used to describe respondent characteristics and general information. Inferential statistics were used to examine the hypotheses and relationships between variables. The analysis followed the research objectives.

Reliability Analysis

The Cronbach’s Alpha value of 0.834 indicates high internal consistency. The research therefore considered the measurement scale reliable for further analysis.

HYPOTHESIS TESTING AND DECISION SUMMARY

For the financial-factor model, the regression analysis examined GMP, perceived valuation and company fundamentals as predictors of investor satisfaction. GMP had a coefficient of β = 0.205 with p < 0.05 and was therefore identified as a significant predictor. The overall model was significant with F = 4.837 and p < 0.01. The research consequently treats GMP as the significant financial factor among the variables examined in the model, while perceived valuation and company fundamentals were not significant predictors in that regression.

For the digital-factor model, peer/influencer recommendations had β = 0.487 with p < 0.001 and real-time IPO information had β = 0.371 with p < 0.001. Both therefore had significant positive relationships with investor satisfaction. Mobile trading applications had β = −0.168 with p < 0.05 and showed a negative coefficient in the regression model. The overall model was significant with F = 29.249 and p < 0.001.

The one-way ANOVA examined whether IPO participation behaviour differed across annual income groups. The result, F(3,137) = 9.720, p < 0.001, indicates statistically significant differences. The reported effect sizes, η² = 0.175 and ω² = 0.156, indicate that income-group differences account for a meaningful proportion of the observed variation in IPO participation behaviour within the sample.

The correlation analysis identified positive relationships among the social and institutional variables. Family/friends/colleagues were positively correlated with financial influencers at r = 0.548, p < 0.001. QIB subscription was positively correlated with overall investor sentiment at r = 0.245, p = 0.003. These results support the research emphasis on social networks, institutional cues and market sentiment in retail IPO decision-making.

Taken together, the inferential results show that not all factors included in the questionnaire have the same statistical importance. The descriptive results demonstrate broad investor attention to fundamentals, valuation, GMP, digital access and sentiment, but the regression and ANOVA analyses identify a smaller set of statistically significant relationships. This distinction is important in interpreting the study because perceived importance and statistical significance are not identical.

RESULTS AND DISCUSSION

Respondent Profile

The respondent profile is concentrated among younger and highly educated participants. Male respondents constitute 63.12%, while female respondents constitute 36.17%. The largest age group is 18–25 years (55.32%), followed by 26–35 years (23.40%). Postgraduate respondents form 51.77% and undergraduate respondents 42.55%. Private-sector employees account for 47.52% and students for 31.91%. More than half of respondents are below ₹6 lakh in annual income, with 36.17% below ₹3 lakh and 34.04% between ₹3–6 lakh.

IPO Application Behaviour

The largest group applies for 1–3 IPOs annually (40.43%). Short-term listing gain is the most common stated objective (37.59%), followed by long-term wealth creation (34.04%). Half of the respondents invest up to ₹50,000 per IPO application. Online brokers and trading applications are the dominant application channel, accounting for 69.50%.

DETAILED INTERPRETATION OF RESPONDENT CHARACTERISTICS

The demographic results indicate that the sample is concentrated among younger retail investors. Respondents aged 18–25 constitute 55.32% of the sample, while those aged 26–35 account for 23.40%. Together, these two groups represent the majority of respondents. The age distribution is relevant to the study because the research examines the role of digital applications, social recommendations and real-time IPO information, all of which are prominent channels considered in the questionnaire.

Educational attainment is also relatively high in the sample. Postgraduate respondents account for 51.77% and undergraduate respondents for 42.55%. This provides a substantial base for examining the relationship between educational attainment, financial literacy and IPO knowledge. The research nevertheless distinguishes education from financial literacy because a formal qualification does not by itself establish knowledge of IPO-specific concepts such as DRHP, price band, cut-off price and allotment.

Occupation and income indicate variation in the economic profile of respondents. Private-sector employees constitute 47.52%, students 31.91%, self-employed respondents 11.35% and public-sector employees 9.22%. Annual income is distributed across four categories, with 36.17% below ₹3 lakh and 34.04% between ₹3–6 lakh. The ANOVA result later confirms that annual income groups differ significantly in IPO participation behaviour.

INTERPRETATION OF IPO PARTICIPATION PATTERNS

The frequency of IPO applications indicates that 40.43% of respondents apply for one to three IPOs per year, while 30.50% apply for less than one IPO. A smaller group applies for three to five IPOs (12.77%) or more than five IPOs (16.31%). This distribution shows that the sample includes both relatively occasional participants and more active retail investors.

The stated investment objective is divided mainly between short-term listing gain and long-term wealth creation. Short-term listing gain is selected by 37.59% and long-term wealth creation by 34.04%. Medium-term capital gain accounts for 24.11%, while portfolio diversification accounts for 4.26%. The coexistence of short-term and long-term objectives is important because the research subsequently examines post-allotment selling and holding behaviour.

The amount invested per IPO is relatively concentrated in lower application sizes. Up to ₹50,000 is reported by 50.35% of respondents and ₹50,001–₹1,00,000 by 29.08%. The remaining respondents report amounts between ₹1,00,001–₹2,00,000 or above ₹2,00,000. Online brokers and trading applications account for 69.50% of application channels, demonstrating the importance of digital access in the sampled investors’ IPO participation.

FACTORS INFLUENCING IPO PARTICIPATION

The descriptive findings show that financial and non-financial factors operate together. Company fundamentals have the highest agreement among the financial items, while mobile trading applications and real-time IPO information show strong digital influence. QIB subscription, firm size and overall investor sentiment also have high levels of agreement. Social recommendations and consumer-brand influence show a more moderate but still substantial role.

Information Sources and Final Subscription Decision

Thorough personal research involving the DRHP and financial analysis is the largest reported final decision driver at 39.01%. A combination of factors accounts for 17.73%, while trusted financial advisors account for 14.89%. Social media/finfluencer recommendations account for 10.64% and word of mouth for 12.77%. Thus, the respondents report a substantial role for personal research even though social and market cues remain present.

DIGITAL ACCESS, FINANCIAL LITERACY AND POST-ALLOTMENT BEHAVIOUR

Post-Allotment Behaviour

The post-allotment results show different holding and exit patterns. The largest category is long-term holding of one year or more (26.95%), followed by decisions depending on listing-day market sentiment (24.11%) and selling only when listing gains exceed a stated level (21.99%). The research also identifies flipping and the disposition effect as behavioural patterns among retail investors.

INFERENTIAL ANALYSIS