Globally, startups are recognized as the primary forces behind economic expansion. They are also expected to usher in a new era of economic prosperity and innovation in India. This study aims to assess the market performance of initial public offerings of eight Indian startups launched in the year 2021. It helps investors and researchers to see beyond the initial market frenzy and also determine an appropriate exit strategy.
The performance is measured on the listing date as well as one year ahead, using stock trading prices. The securities are analyzed using the Sharpe ratio, t-test, year-to-date comparisons and correlation tests. The analysis has been done on a comparative basis.
It revealed that these initial public offerings were majorly underpriced upon issue and opened up to high listing gains for the investors. However, the price run was short termed as the stocks underperformed as compared to the bullish market. This was accompanied by a dramatic fall in share prices and erosion of investor wealth. Further, correlation tests revealed the inverse correlation between underpricing and stock performance.
The investors are thus advised to study the key financials of the company as many times as possible, as the current market price might be a result of over-favored market sentiment and deliberate underpricing. Such a bubble burst in the future may result in investor wealth erosion. Investors trying to navigate the erratic nature of these offers must comprehend the dynamics of underpricing in startup initial public offerings. Understanding the connection between underpricing and long-term performance can help practitioners develop more effective initial public offering (IPO) pricing and marketing plans. Getting a hold of the dynamics may also help policymakers, who have the power to shape laws pertaining to investor protection and initial public offerings. Future research must consider market evolution, technological effects on investor behavior and how global market trends affect startup initial public offerings. The research is also based on a small sample size and focussed on a short time period. The research does not account for rapidly changing market conditions, such as technological advancements or shifts in regulatory environments, which can have significant implications for IPO performance and investor behavior. Further research can be conducted keeping these factors in mind.
The investors are thus advised to study the key financials of the company as many times as possible, as the current market price might be a result of over-favored market sentiment and deliberate underpricing. Such a bubble burst in future may result in investor wealth erosion. Investors trying to navigate the erratic nature of these offers must comprehend the dynamics of underpricing in startup initial public offerings. Understanding the connection between underpricing and long-term performance can help practitioners develop more effective IPO pricing and marketing plans. Getting a hold of the dynamics may also help policymakers, who have the power to shape laws pertaining to investor protection and initial public offerings. Future research must consider market evolution, technological effects on investor behavior and how global market trends affect startup initial public offerings.
The investors are thus advised to study key financials of the company as many times as possible, as the current market price might be a result of over-favored market sentiment and deliberate underpricing. Such a bubble burst in future may result in investor wealth erosion. Investors trying to navigate the erratic nature of these offers must comprehend the dynamics of underpricing in startup initial public offerings. Understanding the connection between underpricing and long-term performance can help practitioners develop more effective IPO pricing and marketing plans. Getting a hold of the dynamics may also help policymakers, who have the power to shape laws pertaining to investor protection and initial public offerings. Future research must consider market evolution, technological effects on investor behavior and how global market trends affect startup initial public offerings.
The study is significant, as there are only a handful of studies focused on the comparative analysis of startup stocks. It will be beneficial in helping the investors in better analysis and stock selection. It will prevent them from falling into the trap of opaque valuations and market-created sentiments.
Introduction
An initial public offering (IPO), which is the primeval time a company’s shares are offered for sale to the general society on the primary market, is a significant milestone for any kind of business. It is a common notion that an IPO is an inevitable part of a firm’s lifecycle. A startup firm is no different. For a startup too, an IPO can be a source of finance or a way of expansion. Often, it is viewed as a sign of success for a startup.
The success of any IPO depends on the firm’s financial performance, its’ marketing strategy and market as well as investor sentiment. It may become difficult for the investors to predict the performance of an IPO as the existence of little amount of historical data makes it difficult to carry out technical analysis. The problem is intensified in the case of startup IPOs due to a limited period of historical financial data and opaque valuations.
The year 2021 is regarded as the year of the IPO rush. IPO rush is a term used to denote increased capital market activity in the form of a rise in the number of public issues. The effect of the pandemic and ease of regulations created a favorable market and investor sentiment. It was observed that even loss-making firms went public in the hopes of greater subscriptions and chances of premium listings. The year 2021 was thus a year of bull run and a hot market period. In the same train were some homegrown new-age startups. As many as eight new-age technology-based startups went public in the year 2021. Their public issue was hailed in the media as the break of a new dawn for the Indian startup and corporate sector. The study was conducted to analyze the pre- and post-IPO performance of these startups and derive relevant conclusions for investors. This is particularly true in a scenario where around 40 Indian new-age startups are expected to be ready to trade their shares or even go public by FY 2025. (Redseer Strategy Consultants, 2023).
Literature review
Theoretical perspectives on the underpricing phenomenon
In the financial literature, underpricing in IPOs has received a lot of attention. Setting an IPO price below the market value is known as underpricing, and it is frequently viewed as a calculated move. Studies on IPO underpricing have predominantly focused on theories that strive to explain why issuers leave money on the table. Scholars have put forward numerous reasons for underpricing. Pioneering researchers like Ibbotson and Jaffe (1975), plus Ritter (1984), trail-blazed the concept named “hot markets” characterized by higher IPO quantity (underpricing). The inference is that the concept of market timing is foremost in the minds of issuers when benefiting from market sentiment during such periods. Loughran et al. (1994) argued that issuers timed the IPOs such that they coincided with spells of excessive market optimism. However, none of the research could predict the correct time to go public for optimal share performance (Pagano et al., 1998).
Periods of hot markets are characterized by the prevalence of information asymmetry among the investors. Initial investigations found information asymmetry to be the reason for share underpricing (Baron, 1982; Welch, 1992). Baron (1982) postulated information asymmetry between underwriters and issuers, with underwriters being well-informed and capable of taking advantage of superior information. Benveniste and Spindt (1989) revealed underpricing to be a way to talk knowledgeable investors into disclosing private information that would affect the stock demand during the pre-selling period. Additionally, the other investors and middlemen used this knowledge to ascertain the offer price. Chemmaneer (1993) brought an information–theoretic framework of IPOs pricing where insiders sold stock in primary as well as secondary markets and had expensive private information regarding the firm’s performance. High-value organizations, which were aware of pooling with organizations of low value, compelled insiders to take part in information generation through underpricing, which rewarded the outsiders for the fee of information generation. In that way, underpricing stemmed from the inducement of information generation by insiders to have an accurate valuation of the entity in the secondary market. Rock (1986) constructed a model to study underpricing. The model examined a preexisting investor cluster whose information was superior in contrast to the firm and other investors. If the pricing of the IPOs was at the anticipated valuation, the advantaged investors crowded out the disadvantaged investors in the event of good issues being presented and vice versa. Hence, underpricing was an outcome of the “winner’s curse” or adverse selection to the unenlightened investors. Alti (2005) developed a template according to which organizations that were highly expected to unearth projects generally lead the “hot markets”. The companies’ valuations resulted in a spillover of information which led to larger quantity of IPOs.
In a market where information asymmetry prevails, firms often use underpricing to signal credibility. Allen and Faulhaber (1989), posit that firms intentionally underprice their shares to signal quality to the market. Ting and Tse (2006) documented the “winner’s curse’ to be the main reason for underpricing in China. However, they eliminated signaling theory as a possible cause of underpricing.
Derrien and Kecskes (2007) held market sentiment and excitement responsible, whereas Lee and Wahal (2004) found that greater venture capital (VC) backing resulted in greater underpricing. Reilly and Hatfield (1969); Beatty and Ritter (1986) concluded that underwriters were chiefly responsible for share underpricing. The reasons varied from uncertainty regarding public valuation, risk reduction and deliberate underpricing for a successful launch. Underpricing comes across as a complex phenomenon as researchers have identified varied reasons as determinants of underpricing of shares.
Empirical evidence on underpricing in the Indian initial public offering market
Empirical studies prove that in the context of Indian stock markets, IPOs are recurrently characterized by significant underpricing. Chandrasekhar and Kumar (2002) furnished evidence of the pervasive underpricing of IPOs in India. By using raw returns accompanied by market-adjusted returns, his study established that the phenomenon of underpricing prevailed in the Indian market. He enumerated the reasons liable for the tenacious occurrence of IPO underpricing. Chopra (2009) investigated NSE-listed IPOs’ price performance. IPOs on the NSE between 1999 and 2008 were used as a sample for this purpose. Both short- and long-term analyses of pricing performance cementing on one week, one month, three months, six months, one year and three years were included in the study. The effect of variables such as level of subscription, lead time of listing, issue size, etc. over price-performance was considered. The analysis uncovered the IPO underpricing on the Indian financial markets during the short run. Baluja (2013) stated that the investors in India were unenlightened about capital markets. The information asymmetry fostered riskiness of the firm’s value amongst the issuers and investors, which resulted in underpricing.
Impact of underpricing on long-term initial public offering performance
Researchers have tried to establish the relationship between underpricing and its effects on companies’ performance. But the literature is still divided on the long-term effects of underpricing. It documents both underperformance and overperformance post-listing. Ibbotson and Jaffe (1975) and Ritter (1984) noted that hot market periods were followed by spells of underperformance. Ritter (1991) registered that underpricing and performance over a longer duration were inversely correlated. Field and Hanka (2001) noticed a decline in prices after the expiration of the lockup period. Kumar (2008) studied the performance of the Indian IPOs between 1999 and 2006, which were issued by the book-building process. Upon listing, these IPOs offered positive returns to investors on average. On the listing day, a huge portion of the closing day returns was taken care of through the embryonic returns on the opening day. Over a longer duration, they underperformed the market later, although they provided positive returns for the first 24 months. Studies have shown that companies with substantial underpricing may experience negative stock performance over time, particularly if initial excitement fades (Brau and Fawcett, 2006). This raises questions about the sustainability of initial returns and the role of market correction.
Chemmanur and He (2011) prepared a model according to which entities that went public first during the IPO wave were foretold to have loftier profitability and productivity post-IPO. Krigman et al. (1999) found a direct correlation between underpricing and long-term performance. The firm’s post-issue share price is positively correlated with the extent of underpricing, which can be deduced from observable data (Grinblatt and Hwang, 1989). These tendencies fluctuated over the duration, with both the early run-up of price as well as subsequent performance dependent on “hot” as well as “cold” market periods [Ritter (1984, 1991)]. Some researchers also documented no correlation between the underpricing of stocks and their performance later on. Jain and Kini (1994) examined the variations in the operating performance of organizations transforming from private to public limited companies. However, no relationship was found between operating performance post-IPO and the initial level of underpricing. The disparity in results could be the result of variations in post-IPO investor behavior and economic conditions. This suggests that differences persist in the relationship between underpricing and long-term performance, leading to room for more empirical research in this arena.
Research gaps and rationale for the present study
Even though our understanding of the elements that lead to underpricing has advanced significantly, more study is required to fully comprehend the intricate relationship between initial pricing methods and long-term performance consequences. Moreover, empirical research on the Indian IPO market is fragmented and is frequently limited to well-established corporations. Through the given study, an attempt has been made to unravel findings in the domain of startups in the Indian market.
Methodology
The study is based on the stock market performances of eight new-age Indian startups that debuted in the year 2021. Stocks are analyzed for a period of one year since the IPO and to facilitate comparison the period of 31 December 2021–31 December 2022 has been selected as the period of one year since issues. The risk-free rate of return is assumed to be the 91-day T-bill yield over the period of study.
For the study, secondary data about historical stock prices has been collected from free-of-cost databases of investing.com and nseindia.com. The data collected has been statistically evaluated using a paired t-test and the Sharpe ratio/Sharpe performance index using MS Excel and PSPP software.
Paired t-test
It was introduced by W.S. Gossett. It deals with small samples and determines if they came from the same population. The paired t-test checks if the population means estimated by dependent samples differ significantly. It is calculated by:
Listing gain: It refers to the positive difference between the listing price and the issue price of shares. It results in profits for investors. If the difference is negative, it spells losses:
Daily return: It is computed using the following equation:
where R = return of stock or market index for period “t” Closing Price “t” and “t – 1” = closing price for current and previous period respectively
Sharpe ratio
The Sharpe ratio was developed by William F. Sharpe in 1966. It computes the stock’s excess return per unit of risk. The excess return of the stock is the risk premium, which is the additional return of the stock over the risk-free return, and the risk is the total risk of the stock, which is expressed as standard deviation. Equation is as follows:
where:
S p = Sharpe ratio of the portfolio;
R p = average return on portfolio;
R f = average risk-free rate of return; and
p = total risk or standard deviation.
Standard deviation measures the dispersion of the data set of returns. Higher the value of standard deviation higher will be the risk.
Decision rule: If the Sharpe ratio attributed to the stock is greater than the Sharpe ratio of the market, it shows superior performance of the stock and vice versa.
Empirical analysis
A. Listing analysis
An analysis of listing gain of the IPOs is made through the following table.
Comparison of mean value of issue and closing prices reveals a trend of underpricing of IPOs. However, if an individual comparison reveals that overpricing also exists, though on a minor scale. CarTrade and Paytm were the only stocks to be overpriced.
Majority of stocks were able to list at a gain with the highest performer being Nazara Technologies. Two stocks CarTrade and Paytm listed at a loss with Paytm being the least performing stock.
B. Post listing analysis
Sharpe ratio of all stocks except EaseMyTrip is negative in the period of the study. Sharpe ratio of the benchmark index is positive. EaseMyTrip also has a positive Sharpe ratio and has been able to outperform the market making it the highest performing stock. Nykaa is the least performing stock.
Sharpe ratio is negative when excess return is negative. By an inspection of the stocks having negative Sharpe, it is evident that all such stocks have average returns which are negative and less than the positive average risk-free rate.
From the above table, it can be noticed that all stocks except EaseMyTrip closed at the end of the period at a price considerably less than the closing price at the beginning. The highest fall was noted in Paytm.
A paired sample t-test was carried out to check if any significant differences exist between the closing prices at beginning and end of the period. The test showed that there was a significant decrease in closing prices before (M = 809.42, SD = 588.57) to after (M = 417.01, SD = 329.85), t (7) = 3.87, p = 0.006. The mean decrease in closing price was 392.41 with a confidence interval of 95% ranging from 152.46 to 632.36.
It is observed that all the stocks closed at lesser than the listing price at year end with Nykaa emerging to be the biggest loser. Paired t-test was conducted to verify the statistical significance of this decline.
The test showed that there is significant decrease in closing prices before (M =1325.13, SD = 772.45) to after (M = 417.01, SD = 329.85), t (7) = 3.96, p = 0.005. The mean decrease in closing price was 908.12 with a confidence interval of 95% ranging from 365.47–1450.77.
After measuring the listing and post-listing performance of stocks, a correlation test was conducted to find the relation between underpricing and share performance. The findings are summarized in the following table:
The above table shows that underpricing is negatively correlated with both the Sharpe ratio and YTD percentage change
Discussion
A. Listing analysis
The public issue of homegrown startups was in the form of hot startups garnering significant interest from the media and the public adding to their hype and demand. Many stocks were underpriced upon issue (Table 1). The IPOs were also underpriced which means that despite mandatory information disclosure norms, information asymmetry exists which provides incentives to companies for underpricing. So, despite weak financials, the stocks were able to list at a profit. The issues also opened to significant listing gain. At the time of listing investors were able to secure profits through most of them in the form of listing gain. Listing gain was recorded as high as 80.745% as in case of Nazara Technologies (Table 2). Listing loss was also observed though on a minor scale. The stocks were initially able to generate wealth for the investors.
Share pricing
| Company | Issue price | Listing day closing price | Pricing | Underpricing (%) |
|---|---|---|---|---|
| Zomato | 76.00 | 126.00 | Underpricing | 65.8 |
| Nazara technologies | 1101.00 | 1592.00 | Underpricing | 44.6 |
| Nykaa | 1125.00 | 2205.80 | Underpricing | 96.1 |
| CarTrade | 1618.00 | 1501.05 | Overpricing | −7.2 |
| EaseMyTrip | 187.00 | 208.45 | Underpricing | 11.5 |
| Policybazaar | 980.00 | 1202.30 | Underpricing | 22.7 |
| Paytm | 2150.00 | 1560.80 | Overpricing | −27.4 |
| MapmyIndia | 1033.00 | 1393.65 | Underpricing | 34.9 |
| Mean | 1033.75 | 1223.76 | Underpricing | 65.8 |
Comparative analysis of listing gain
| Company | Issue price | Listing price | Listing gain (%) |
|---|---|---|---|
| Zomato | 76.00 | 116.00 | 52.632 |
| Nazara technologies | 1101.00 | 1990.00 | 80.745 |
| Nykaa | 1125.00 | 2018.00 | 79.378 |
| CarTrade | 1618.00 | 1599.80 | −1.125 |
| EaseMyTrip | 187.00 | 212.25 | 13.503 |
| Policybazaar | 980.00 | 1150.00 | 17.347 |
| Paytm | 2150.00 | 1950.00 | −9.302 |
| MapmyIndia | 1033.00 | 1565.00 | 51.500 |
B. Post listing analysis
In stark contrast to the promising initial performance, post-listing analysis reveals a troubling trend. It is observed that the year-end closing price is significantly lower than both listing price and closing price at the beginning of the period studied (Tables 3 and 4). Later, a paired sample t-test was also used to compare data as groups in Tables 5 and 6. It was revealed that there was a significant difference between closing price at the end of the period and listing price or closing price at the beginning. The IPOs registered lower year-end gains compared to listing gains. The year-end price prediction proved to be difficult as after listing the stock prices were affected by several factors, after the initial market hype and investor sentiments waned.
Year-to-date comparison
| Company | Closing price as on December 31, 2021 | Closing price as on December 30, 2022 | % change |
|---|---|---|---|
| Zomato | 137.45 | 59.35 | −56.821 |
| Nazara technologies | 1144.55 | 580.70 | −49.264 |
| Nykaa | 350.26 | 154.85 | −55.790 |
| CarTrade | 848.30 | 468.65 | −44.754 |
| EaseMyTrip | 33.70 | 52.70 | 56.380 |
| Policybazaar | 950.30 | 448.30 | −52.825 |
| Paytm | 1334.55 | 531.00 | −60.211 |
| MapmyIndia | 1676.25 | 1040.55 | −37.924 |
Year-to-date comparison
| Company | Listing price | Closing Price as on December 30, 2022 | % change |
|---|---|---|---|
| Zomato | 116.00 | 59.35 | −48.84 |
| Nazara technologies | 1990.00 | 580.70 | −70.82 |
| Nykaa | 2018.00 | 154.85 | −92.33 |
| CarTrade | 1599.80 | 468.65 | −70.71 |
| EaseMyTrip | 212.25 | 52.70 | −75.17 |
| Policybazaar | 1150.00 | 448.30 | −61.02 |
| Paytm | 1950.00 | 531.00 | −72.77 |
| MapmyIndia | 1565.00 | 1040.55 | −33.51 |
Source(s): Computation of the author
Paired samples t-test
| Description | Mean | SD | Paired difference | t | df | Sig. | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| 95% Confidence interval of the difference | ||||||||||
| Mean | SD | Std. Error mean | Lower | Upper | ||||||
| Before | 809.42 | 588.57 | 392.41 | 287.02 | 104.48 | 152.46 | 632.36 | 3.87 | 7 | 0.006 |
| After | 417.01 | 329.85 | ||||||||
Source(s): Computation of the author
Paired samples t-test
| Description | Mean | SD | Paired difference | t | df | Sig. | ||||
|---|---|---|---|---|---|---|---|---|---|---|
| 95% confidence interval of the difference | ||||||||||
| Mean | SD | Std. Error mean | Lower | Upper | ||||||
| Before | 1325.13 | 772.45 | 908.12 | 649.08 | 229.49 | 365.47 | 1450.77 | 3.96 | 7 | 0.005 |
| After | 417.01 | 329.85 | ||||||||
Sharpe ratios too showed that most of the stocks have underperformed in the reported period, with all except one having a negative ratio in Table 7. Sharpe ratio is negative when excess return is negative. By an inspection of the stocks having negative Sharpe, it is evident that all such stocks have average returns that are negative and less than the positive average risk-free rate. This means that as the initial hype and market attention (Levis, 1993) subsided for these hot IPOs, the share value dropped drastically, suggesting that the initial gains were not indicative of sustainable value creation. Such practices create a precarious environment where investor wealth is at risk of erosion when the market corrects itself. Initial listing success in the case of startup IPOs did not guarantee investor wealth creation later on. Thus, the stock holding strategy resulted in the erosion of wealth. In the case of these IPOs, sales on listing day itself can be concluded to be an efficient exit strategy for investors rather than long-term holding to reduce losses.
Comparative analysis of Sharpe ratio
| S.No. | Name | Average return Rp | SD σp | Excess return | Sharpe ratio |
|---|---|---|---|---|---|
| 1 | Zomato | −0.603 | 0.823 | −0.654 | −0.794 |
| 2 | Nazara technologies | −0.558 | 0.651 | −0.608 | −0.935 |
| 3 | Nykaa | −0.644 | 0.623 | −0.695 | −1.115 |
| 4 | CarTrade | −0.521 | 0.561 | −0.571 | −1.019 |
| 5 | EaseMyTrip | 1.556 | 0.748 | 1.505 | 2.013 |
| 6 | Policybazaar | −0.584 | 0.714 | −0.635 | −0.89 |
| 7 | Paytm | −0.684 | 0.681 | −0.735 | −1.08 |
| 8 | MapmyIndia | −0.444 | 0.521 | −0.494 | −0.966 |
| 9 | NIFTY 50 | 0.09 | 0.231 | 0.039 | 0.185 |
The average risk-free rate is computed to be 0.051
Pearson’s correlation test (Table 8) revealed that initial underpricing is inversely related, albeit to a lower degree, with both Sharpe ratio and YTD percentage change. Hence, underpricing is negatively correlated with share performance later. These results are on the same page as results of other researchers like Ritter etc. However, these relations are not statistically significant. This could also be attributed to the small data size as n = 8.
Pearson’s correlations
| Description | Pearson’s r | p |
|---|---|---|
| Sharpe ratio – underpricing % | −0.173 | 0.682 |
| Sharpe ratio – Percentage change | 0.979 *** | < 0.001 |
| Underpricing % – Percentage change | −0.198 | 0.637 |
*p < 0.05, ** p < 0.01, ***p < 0.001
Conclusion and implications
The findings of this study provide a critical insight into the trajectory of homegrown startups post-IPO, highlighting that the initial exuberance surrounding these offerings is often short-lived. Though many stocks were listed at a profit, yet within a year of their listing, the stocks witnessed a steep decline in prices. The stocks that initially listed at a profit, later underperformed in the market and generated negative returns. The underpricing of shares was found to be inversely correlated to stock performance. The investors are thus advised to study the key financials of the company as many times; the current market price might be a result of over-favored market sentiment and deliberate underpricing. Such a bubble burst in the future may result in investor wealth erosion. Investors trying to navigate the erratic nature of these offers must comprehend the dynamics of underpricing in startup initial public offerings.
Understanding the connection between underpricing and long-term performance can help practitioners develop more effective IPO pricing and marketing plans. Getting a hold of the dynamics may also help policymakers, who have the power to shape laws pertaining to investor protection and initial public offerings. Future research must consider market evolution, technological effects on investor behavior and how global market trends affect startup initial public offerings.
The research is also based on a small sample size and focused on a short time period. The research does not account for rapidly changing market conditions, such as technological advancements or shifts in regulatory environments, which can have significant implications for IPO performance and investor behavior. Further research can be conducted, keeping these factors in mind.
This is to acknowledge that this work has not been supported by any external research funding.
