IPO Underpricing across Different Sectors in India from 2010-2020

 

Lakshay Khandelwal, Aditi Agarwal

Student, Symbiosis Centre for Management Studies, Pune, Symbiosis International University Pune.

 

ABSTRACT:

In this paper, underpricing of Initial Public Offerings across thirteen different sectors in the Indian stock market have been analyzed, during the period 2010–2020 (Data available till 31st October 2020). A sample of 129 companies, having an issue size greater than INR 100 crores, was examined and analyzed through IPO listing gains, weighted mean, standard deviation and coefficient of variation. The study shows that Retail, FMCG and Consumer Durables industry was underpriced the most while Engineering, Construction and Infrastructure industry issues were underpriced the least or overpriced. It was also found that Initial Public Offerings (IPOs) could be a window to make immediate gains in a very short period of time if thorough analysis of the issues and the market conditions is performed. Furthermore, it was observed that the first day return of the companies varies highly and cannot be fairly predicted by the weighted average first day return of the respective sector.

 

 

 

INTRODUCTION:

The process of offering the shares of a private company to the general public for the first time in exchange for ownership (in form of equity shares) is called Initial Public Offering (IPO). Primarily, there are two reasons for which firms go public (McConaughy, Dhatt, & Kim, 1995). One, it helps to diversify the shareholders base of the company on offer. Second, is to assist the management in acquiring funds to pursue growth opportunities, either by entering a new product line, or expanding the current production capacities. Another reason to go public could be to reduce the cost of funds (A. Ljungqvist, 2007).

 

Underpricing is estimated as the percentage difference between the price at which the IPO shares were sold to investors (the offer price) and the price at which the shares subsequently trade in the market.

 

In well-developed capital markets, the full extent of underpricing is evident fairly quickly, certainly by the end of the first day of trading, and so most studies use the first-day closing price when computing initial underpricing returns (A. Ljungqvist, 2007). Using prices at the end of the first week of trading or at the end of the month, typically makes little difference. Listing Gains, is also expressed as a percentage difference of the price by which the shares of the company trade higher on the bourses over its issue price. Therefore, there is no difference between these two terms except for the fact the word ‘Underpricing’ is more often used by the issuer (issuing company) and the underwriter (or investment banker), whereas the term ‘Listing Gain’ is more used by the investors.

 

Process of IPO:

In an IPO, the issuing firm hires an investment bank or underwriter. The under-writers assist firms’ managers in preparing the extensive paperwork involved in complying with the SEBI guidelines. The company involved must submit a registration statement to the SEBI, which includes a detailed report of its fiscal health and business plans. SEBI scrutinizes this report and does its own background check of the company. While awaiting the approval, the company, with assistance from the underwriters, creates a preliminary 'Red Herring' prospectus, containing detailed financial information of the past years, different business risks, future plans, price range, etc. for prospective investors who would be interested in buying the stock. This is followed by IPO Roadshows, which involve the lead underwriters marketing the firm to prospective institutional investors like mutual funds, hedge funds, HNIs, etc. typically through presentations and one on one meetings. This helps the underwriters to gauge the demand for the issue from different investors and determine the final issue price. It is this price that forms the basis for underpricing. Upon the satisfaction of SEBI with the registration documents, a period has to be fixed (typically 2-4 days) during which the public can subscribe to these shares.

 

However, it is argued that in the process of offering its shares to the public a lot of money is left on the table (Dilesha Nawadali Rathnayake, 2019). This implies that the underwriters or investment bankers deliberately undervalue the companies at the time of Initial Public Offering (IPO). Theories of underpricing can be grouped under four broad headings: Information Asymmetry, Investment Banker Monopoly Power, Lawsuit Avoidance, Signalling (as a party of long-term strategy) and Ownership Dispersion. The most widely acknowledged Asymmetric information model is Rock’s (1986) Winner’s Curse Model. According to this, investors come in two categories: informed and uninformed. Rock assumes that informed investors are better informed about the true value of the shares on offer than are investors in general, the issuing firm, or its underwriting bank. Informed investors will bid only for those IPO which are priced attractively, whereas the uninformed investors bid indiscriminately. This imposes a ‘winner’s curse’ on uninformed investors: in unattractive offerings (where a listing loss is expected), they receive all the shares they have bid for, while in attractive offerings, their demand is partly crowded out by the informed. Thus, their average returns are most likely to be negative as they generally don’t receive all the shares, they have bid for in those companies which are likely to offer high returns on debut.

 

If the expected returns are negative, then the uninformed investors will not bid, and the market will be left only with the informed investors to bid, whose demand will be insufficient to take up all the shares on offer, even in attractive offerings, Rock assumes. Therefore, expected returns should be non-negative so that the uninformed at least break even. In other words, all IPOs must be underpriced in expectation. Another assumption made by Rock’s model is that collectively, firms seeking to go public benefit from underpricing, because it is the key to ensuring the continued participation in the IPO market of the uninformed, whose capital is needed by assumption.

 

Accordingly, to Investment Banker Monopoly Power theory, the investment banker advises on the subscription price. This can create a potential conflict for at least 2 reasons: (i) Underpricing can reduce their own (marketing) costs. (ii) Underpricing can be unethically used to develop relationships with other clients, since they guarantee immediate return. This practice is called IPO Spinning and it is illegal in most jurisdictions. Another reason for Underpricing is Lawsuit Avoidance. The prospectus is in large part a marketing document. So, there is a chance that some of the forecasts might be a little biased. Underpricing ensures that investors enjoy quick gain from their subscription. So, this provides protection to directors, who otherwise might be sued for misstatement. IPO is just one stage in a multi-stage strategy for expansion. By offering underpriced shares one time, the investors might get lined the next time the shares are offered. This is called ‘Signalling’. Finally, higher underpricing will draw higher interest by more and more investors, leading to a more dispersed ownership base. Broader the shareholder base, more difficult it is for them to get organized and influence the management. More diverse shareholder base also leads to higher liquidity.

 

REVIEW OF LITERATURE:

The phenomenon of IPO underpricing isn’t a recent one. The practice of valuing the issuer company below than what its fair value is exists from as early as 1960s, as documented by (Ljungqvist, 2009) in the study titled ‘IPO Underpricing.’ A. Ljungqvist reviewed the principle theories that have been proposed to explain the phenomenon of IPO underpricing and the huge jump that the stock prices see on the day of listing on stock exchange. These principles or reasons can be categorized into four broad groups: Asymmetrical Information, Institutional, Control and Behavioral.

 

(Ritter, 1991) documents that underpricing and long-run performance are negatively related, while Krigman, Shaw, and Womack (1999) found a positive relation. (Laurie Krigman, 2002) demonstrated that the Hot-IPOs (IPOs with listing gains between 10% and 60%) outperformed the other categories and continued to rise in the twelve months following the third after listing. This was followed by cool-IPOs (IPOs with listing gains between 0 - 10%), cold IPOs (IPOs opening below the issue). Surprisingly, Extra-Hot IPOs (IPOs with listing gains over 60%) showed the worst performance with average returns plummeting to -12% in the twelve months following the third day of listing. In addition, they linked flipping (the practice of selling shares within 2 days of a company making debut on an exchange) to the performance of stock over the long term.

 

(Tim Loughran, 2004) used three hypotheses (the changing risk composition, the realignment of incentives, and the changing issuer objective function) for understanding the change in underpricing over a period of time, that is the IPO underpricing doubled from 7% during 1980- 1989 to almost 15% during 1990-1998, and then to 65%, during the internet bubble period. (Dilesha Nawadali Rathnayake, 2019) used as many as thirteen variables including offer risk, investor sentiment, firm size, market volatility prior to the IPOs, the time lag between IPO issue date and CSE listing date, and hot-issue periods to explain how these factors affect IPO returns. (Schwert, 2010) provide empirical evidence to suggest that complexity of the pricing problem is also sensitive to market-wide conditions which sometimes makes accurately evaluating the IPOs a daunting task for underwriters and investors.

 

(Shiller, 1988) conceived the hypothesis that underwriters deliberately underprice to achieve publicity and promote enthusiasm using questionnaire surveys of investors in IPOs. Other hypotheses suggested by the results are an investor risk perception hypothesis and a fairness-relationship hypothesis. Providing an extension to Shiller’s work, (Lawrence M. Benveniste, 1989) explore how investment bankers act upon the interest taken by the clients (mainly institutional investors) in the deal to readjust the price at ‘Offer Stage’ from ‘Preliminary Filing’ stage and allocate new issues. While (Michelle Lowry, 2004) results do not ‘reject’ any of the existing theories of IPO pricing, they show that no single existing theory comes close to explaining the numerous biases that exist. They also held the hypothesis that positive information learned during the registration period is not incorporated into the pricing of an IPO in the same manner as negative information.

 

In their study, (Michelle Lowry S. S., 2002) worked exhaustively on understanding how underpricing is one of the ways to reduce the probability of litigation, thus riskier IPOs are even more underpriced. (Aissia, 2014) found that IPOs with high initial returns have higher idiosyncratic skewness, turnover and momentum. Also, skewness preference and investor sentiment are stronger during the periods of favorable market conditions. (Hanley, 1993) on the basis of his empirical works suggested that issues that have final offer prices which exceed the limits of the offer range have greater underpricing than other IPOs, and are also more likely to increase the number of shares issued. (Daniel J. Bradley, 2002) examined the extent to which offer prices reflect public information for 3,325 IPOs over the period 1990-199 by focusing on four important variables namely:  share overhang, file range amendments, venture capital backing, and previous issue underpricing.

 

(Gongmeng Chen, 2004) investigates the pricing of initial public offerings of (i) shares sold to domestic investors and (ii) shares sold to foreign investors. Risk, high government and legal entity shareholdings are also associated with underpricing of shares sold to domestic investors. (Thomas J Boulton, 2010) using 4462 IPOs across 29 countries from 2000 to 2004 reviewed how differences in country-level governance can affect the underpricing. Other authors like Thomas J. Boulton, Scott B. Smart, Chad J. Zutter, 2011 have tried to establish a link of underpriced stocks with quality earnings.  (Catherine M. Daily, 2003) in their research suggested there exists a little evidence to support the notion that underpricing can be attributed to the ‘dot-com’ crisis.

 

(Garfinkel, 1993) has examined the relationship between underpricing and subsequent equity issuance and open market insider sales. It is the first paper to examine the job of open market insider sales to recoup the losses caused during underpricing. (Schenone, 2003) tested whether a company’s banking relationships established before the firm’s IPO solve or at least reduce asymmetric information problems behind high underpricing. (S Banerjee, 2011) investigated how country-level characteristics, namely differences in level of information asymmetry, investors’ home-country bias, effectiveness of contract enforcement mechanisms, and accessibility of legal recourse influence IPO underpricing. (L. Cassia, 2006) through their works confirmed the hypothesis put forward by other authors across the countries that shows that IPOs are intentionally underpriced, excluding both public and private information while pricing them.

 

In Australian context, (Luke Bayley, 2006) attributed ‘Flipping’ to underpricing as one of the causes, enabling retail investors to make a quick handsome gain, especially in the Hot-market period. (Deb, 2009) used a sample of 189 IPOs to observe that the mispricing adjusts very quickly and no excess returns are available to investors in the aftermarket in the short run which is consistent with the notion of Efficient Market Hypothesis. (Alok Pande, 2007) sought to empirically explain the first day underpricing in terms of the demand generated during the book building of the issue. (Ghosh, 2005), on the contrary to the global evidence, pointed out that underpricing was more prevalent during the slump period than the high volume (hot) period in the Indian context.

 

Research Gap:

Most of the researches have used empirical findings to support their hypothesis or to validate the existing hypothesis, others have contradicted the existing widely accepted theories. However, except few, most of these explain results with respect to particular geographies or countries. Second, most of the authors, in their work, have selected the IPOs of the companies randomly and the time period under study is quite large. Hence, a proper methodology of sample selection is lacking. Third, the number of studies within the Indian context is much smaller as compared to studies at Global level, or in American or European context.

 

Research Objective:

The research aims to (i) examine and understand the Phenomenon of Underpricing of IPOs across Different Sectors in India and (ii) check whether or not the first day return of the companies can be fairly predicted by the weighted average first day return of the respective sector. (iii) test the hypothesis that IPO is, as reckoned by many in the financial markets, especially the retail investors, a window to rapid profits in a short time period.

 

RESEARCH METHODOLOGY:

A quantitative research is undertaken to observe, analyze and interpret the phenomenon of underpricing in Indian IPOs and understand the extent of gains investors can achieve through investing in shares across various sectors in the Indian stock market. Secondary Data is collected for various Initial Public Offerings in the Indian stock market across sectors from FY 2010 to FY 2020. All the data has been collected through online research wherein various reliable financial and stock market websites have been referred to, like moneycontrol.com, chittorgarh.com, NSEindia.com, investorzone.in, business-standard.com, economictimes.com, financialexpress.com, dnaindia.com, livemint.com to gather information pertaining to issue price (or offer price), closing price on the day of listing, date of listing, the sector to which the company belongs to and issue size on the selected IPOs.

 

Assumptions undertaken for the study are as follows:

In order to study IPO Underpricing in the Indian Financial Markets, the market has been segmented into 13 different industries; namely: Banking, Financial Services Companies (Non-Banking), Information Technology and Consulting, Pharmaceuticals and Healthcare, Oil & Gas Production and Marketing, Renewables and Metals & Mining, Chemicals, Retail, FMCG & consumer durables, Commerce and services, Agriculture and Agri inputs, Foods Processing and marketing, Automobile and Auto Components, Engineering, Construction and Infrastructure, Real Estate and Defense. In each of these sectors, a sample of minimum 7 companies have been taken to ensure adequate representation of the respective industry. A total of 129 companies which have launched its offering have been chosen for research.

 

It is a common knowledge that retail investors subscribe to IPOs with caution. Therefore, a company’s IPO with a big issue size (for example INR 500 crores) is more likely to be considered safer and attract more public interest than one with smaller issue size (for example INR 5-10 crores).

 

In line with the above assumption, only the IPOs with issue size of more than INR 100 crores have been chosen for the data set of public issue.

 

The data set consists of Initial Public Offerings (IPOs) for a period of 11 years from 2010 - 2020. The rationale behind this is that the second decade of the 21st century has been characterized by a period of economic stability notwithstanding the period of minor economic slowdown in the beginning of 2014.

 

The closing price has been taken to measure the listing gains as opposed to the listing price.

 

Data Analysis and Interpretation:

Table 1: Company IPOs and Listing Gains across Sectors

Sector	Company	Listing Date	Issue Price	Close on Listing Day	Listing Gain	Issue Size (INR crores)	Weights	Weights*Listing Gains
Banking	United Bank of India IPO	18-Mar-2010	66	68.8	4.24	325	0.027	0.1145
	Standarad Chartered PLC IDR	11-Jun-2010	104	106	1.92	2486	0.206	0.3971
	Punjab and Sind Bank	30-Dec-2010	120	127.05	5.88	470.82	0.039	0.2299
	RBL Bank Ltd	31-Aug-2016	225	273.7	21.64	1213	0.101	2.1806
	AU Financiers India Ltd.	10-Jul-2017	358	541.2	51.17	1912.5	0.159	8.1286
	Bandhan Bank	27-Mar-2018	375	477.2	27.25	4473	0.372	10.1249
	CSB Bank Ltd.	4-Dec-2019	195	300	53.85	409.68	0.034	1.8322
	Ujjivan Small Finance Bank Ltd.	12-Dec-2019	37	55.9	51.08	750	0.062	3.1820
						12040		26.1899
Financial Services Companies (Non-Banking)	Land Finance Holdings	29-Jun-2011	52	49.95	-3.94	1245	0.018	-0.0719
	Muthoot Finance Ltd IPO	6-May-2011	175	176.25	0.71	901.25	0.013	0.0094
	PTC India Financial Services Ltd	30-Mar-2011	28	24.9	-11.07	438.76	0.006	-0.0711
	Repco Home Finance	1-Apr-2013	172	164.7	-4.24	270.39	0.004	-0.0168
	Equitas Holdings	21-Apr-2016	110	136	23.64	2175	0.032	0.7529
	Ujjivan Financial Services Ltd	10-May-2016	210	231.9	10.43	887.69	0.013	0.1356
	ICICI Prudential Life Insurance Co	29-Sep-2016	334	330	-1.20	6056.79	0.089	-0.1062
	PNB Housing Finance Ltd	7-Nov-2016	775	860	10.97	3000.75	0.044	0.4820
	ICICI Lombard General Insurance Company	27-Sep-2017	661	681.55	3.11	5700.94	0.083	0.2596
	SBI Life Insurance Company Ltd	3-Oct-2017	700	708	1.14	8400	0.123	0.1406
	Reliance Nippon Asset Management	6-Nov-2017	252	284	12.70	1542.24	0.023	0.2868
	MAS Financial Services Ltd	10-Oct-2017	459	654.75	42.65	460.04	0.007	0.2873
	General Insurance Corporation of India	25-Oct-2017	912	870.4	-4.56	11175.84	0.164	-0.7466
	HDFC Standard Life Insurance	17-Nov-2017	290	345	18.97	8695	0.127	2.4151
	IndoStar Capital Finance Limited	21-May-2018	572	600.6	5.00	1844	0.027	0.1350
	HDFC Asset Management Company	6-Aug-2018	1100	1726.25	56.93	2800	0.041	2.3346
	CreditAccess Grameen Limited	23-Aug-2018	422	420.8	-0.28	1131.19	0.017	-0.0047
	Spandana Sphoorty Financial Ltd	19-Aug-2019	856	848	-0.93	1202.34	0.018	-0.0165
	SBI Cards and Payment Services	16-Mar-2020	755	682.05	-9.66	10354.77	0.152	-1.4653
						68281.99		4.7398
Information Technology and Consulting	Persistent Systems Limited	6-Apr-2010	310	404	30.32	168.01	0.024	0.7178
	Quick Heal Technologies	8-Feb-2016	321	254.45	-20.73	451.25	0.064	-1.3182
	Quess Corp Ltd.	29-Jun-2016	317	503	58.68	400	0.056	3.3069
	LandT Infotech Ltd	21-Jul-2016	710	697.65	-1.74	1236	0.174	-0.3029
	LandT Technology Services Ltd	23-Sep-2016	860	920	6.98	894.4	0.126	0.8792
	Endurance Technologies Ltd	19-Oct-2016	472	654.4	38.64	1161.73	0.164	6.3256
	Dixon Technologies (India) Ltd	18-Sep-2017	1766	2903	64.38	600	0.085	5.4429
	Newgen Software Technologies	29-Jan-2018	245	253	3.27	424.62	0.060	0.1954
	Affle India	8-Aug-2019	745	858	15.17	459	0.065	0.9810
	Happiest Minds Ltd.	17-Sep-2020	166	371	123.49	702.2	0.099	12.2185
	Route Mobile	21-Sep-2020	350	650	85.71	600	0.085	7.2463
						7097.21		35.6925
Pharmaceuticals and Healthcare	Claris Lifesciences	24-Nov-2010	228	224.4	-1.58	300	0.034	-0.053
	Parabolic Drugs	17-Jun-2010	75	64.8	-13.60	200	0.022	-0.304
	Syngene International Ltd	11-Aug-2015	250	310.4	24.16	550	0.061	1.485
	Alkem Laboratories Limited	23-Dec-2015	1050	1382	31.62	1349.61	0.151	4.769
	Dr. Lal Path Labs	23-Dec-2015	550	825	50.00	638	0.071	3.565
	Healthcare Global Enterprises	30-Mar-2016	218	171	-21.56	649.64	0.073	-1.565
	Thyrocare Technologies Ltd	9-May-2016	446	665	49.10	479.21	0.054	2.630
	Laurus Labs Ltd	19-Dec-2016	428	480.5	12.27	1331.8	0.149	1.826
	Eris Lifesciences Limited	29-Jun-2017	603	601.05	-0.32	1741.16	0.195	-0.063
	Shalby Hospitals	15-Dec-2017	248	239.7	-3.35	504.8	0.056	-0.189
	Metropolis Healthcare Ltd.	15-Apr-2019	880	959.55	9.04	1204.29	0.135	1.217
						8948.51		13.3165
Oil and Gas Production and Marketing, Renewables and Metals and Mining	JSW Energy	4-Jan-2010	115	102.55	-10.83	3016.52	0.110	-1.194
	Orient Green Power Company Ltd	8-Oct-2010	55	45.5	-17.27	900.00	0.033	-0.568
	Coal India	4-Nov-2010	245	343	40.00	15199.44	0.556	22.222
	MOIL Ltd.	15-Dec-2010	375	466.5	24.40	1237.51	0.045	1.104
	Inox Wind Ltd.	9-Apr-2015	325	438.4	34.89	1020.52	0.037	1.302
	Mahanagar Gas Ltg.	1-Jul-2016	421	519.9	23.49	1039.64	0.038	0.893
	HPL Electric and Power Co.	4-Oct-2016	202	189	-6.44	361	0.013	-0.085
	Indian Energy Exchange	23-Oct-2017	1650	1626.45	-1.43	1000.73	0.037	-0.052
	Mishra Dhatu Nigam Ltd.	4-Apr-2018	90	89.65	-0.39	438.38	0.016	-0.006
	Sterling and Wilson Solar	20-Aug-2019	780	700	-10.26	3145.16	0.115	-1.179
						27358.9		22.4359
Chemical	Sharda Cropchem	23-Sep-2014	156	231.2	48.21	351.86	0.105	5.072
	S H Kelkar and Company Ltd	16-Nov-2015	180	210	16.67	508.17	0.152	2.533
	Galaxy Surfactants Ltd	8-Feb-2018	1480	1698	14.73	937.09	0.280	4.128
	Fine Organic Industries Ltd	2-Jul-2018	783	822.8	5.08	600.2	0.179	0.912
	Neogen Chemicals Ltd	8-May-2020	215	263.55	22.58	132.35	0.040	0.894
	Rossari Biotech Ltd	23-Jul-2020	425	742.4	74.68	496.49	0.148	11.088
	Chemcon Ltd	23-Sep-2020	340	584.8	72.00	318	0.095	6.847
						3344.16		31.472
Retail, FMCG and consumer durables	Future consumer	10-May-2011	11	8.25	-25.00	750	0.176	-4.388
	Tribhovandas Bhimji Zaveri	9-May-2012	126	111	-11.90	200	0.047	-0.557
	PC Jeweller Ltd.	27-Dec-2012	135	148.8	10.22	609.3	0.143	1.458
	Vmart Ltd	20-Feb-2013	215	203.3	-5.44	94.42	0.022	-0.120
	SP Apparels	12-Aug-2016	268	295	10.07	239.13	0.056	0.564
	Sheela Foam	9-Dec-2016	730	1032	41.37	510	0.119	4.938
	DMart	21-Mar-2017	299	640.75	114.30	1870	0.438	50.022
						4272.85		51.9157
Commerce and services	Justdial*	22-May-2013	477	612.35	28.38	919.14	0.618	17.522
	Infibeam	23-Mar-2016	432	445.55	3.14	450	0.302	0.948
	Security and Intelligence Services India Ltd.	2-Aug-2017	815	757.05	-7.11	779.58	0.524	-3.724
	Matrimony	13-Sep-2017	985	901.2	-8.51	496.88	0.334	-2.840
	MSTC	29-Mar-2019	128	113.8	-11.09	212	0.142	-1.580
	IndiaMART	26-Jun-2019	973	1302.55	33.87	475.59	0.320	10.822
						1488.46		21.1480
Agriculture and Agri inputs, Foods Processing and marketing	Godrej Agrovet Ltd.	16-Oct-2017	460	595.8	29.52	1157.31	0.224	6.602
	Advanced Enzyme Technologies Ltd.	1-Aug-2016	896	1178	31.47	411.49	0.080	2.503
	Prataap Snacks Limited	5-Oct-2017	938	1180.65	25.87	481.56	0.093	2.407
	Apex Frozen Foods Ltd	4-Sep-2017	175	209.85	19.91	152.25	0.029	0.586
	Parag Milk Foods Ltd	19-May-2016	215	248	15.35	751.78	0.145	2.230
	Prabhat Dairy Limited	21-Sep-2015	115	114.8	-0.17	356.19	0.069	-0.012
	Varun Beverages Ltd	8-Nov-2016	445	461.9	3.80	1112.5	0.215	0.816
	Manpasand Beverages Ltd	9-Jul-2015	320	326.1	1.91	400	0.077	0.147
	Sharda Cropchem	23-Sep-2014	156	231.45	48.37	351.86	0.068	3.289
						5174.94		18.5680
Automobile and Auto Components	Varroc Engineering Ltd	6-Jul-2018	967	1037.35	7.28	1945.77	0.413	3.005
	Sandhar Technologies Ltd	2-Apr-2018	332	321	-3.31	565.6	0.120	-0.398
	Garden Reach Shipbuilders and Engineers Ltd	10-Oct-2018	118	102.65	-13.01	344.69	0.073	-0.952
	Endurance Technologies Ltd	19-Oct-2016	472	647.7	37.22	1161.73	0.247	9.179
	GNA Axles Ltd	26-Sep-2016	207	245.15	18.43	130.41	0.028	0.510
	Precision Camshafts Ltd	8-Feb-2016	186	177.25	-4.70	410	0.087	-0.409
	Commercial Engineers and Body Buildeers Co Ltd	18-Oct-2010	127	119	-6.30	153	0.032	-0.205
						4711.2		10.7305
Engineering, Construction and Infrastructure	Hathway Data and Telecom	25-Feb-2010	265	207.65	-21.64	666	0.049	-1.067
	ILandFS Transportation Networks	30-Mar-2010	258	277	7.36	700	0.052	0.382
	Ramky Infrastructure	8-Oct-2010	468	411.85	-12.00	530	0.039	-0.471
	Ashoka Buildcon Ltd	14-Oct-2010	324	330.75	2.08	225	0.017	0.035
	Bharti Infratel	28-Dec-2012	240	191	-20.42	4155.8	0.308	-6.282
	VRL Logistics	30-Apr-2015	205	292.5	42.68	473.88	0.035	1.497
	MEP Infrastructure	6-May-2015	65	58.4	-10.15	324	0.024	-0.244
	PNC Infratech Ltd.	26-May-2015	378	360.5	-4.63	488.44	0.036	-0.167
	Power Mech Projects Ltd	26-Aug-2015	640	580	-9.38	273.22	0.020	-0.190
	Sadbhav Infrastructure Projects Ltd.	16-Sep-2015	103	106.2	3.11	491.6	0.036	0.113
	Dilip Buildcon	11-Aug-2016	219	251.75	14.95	653.98	0.048	0.724
	PSP Projects	29-May-2017	210	199.5	-5.00	211.68	0.016	-0.078
	Tejas Networks	27-Jun-2017	257	263	2.33	776.69	0.058	0.134
	GTPL Hathway Ltd.	4-Jul-2017	170	171.65	0.97	484.8	0.036	0.035
	Bharat Road Network	18-Sep-2017	205	208.45	1.68	600.65	0.044	0.075
	Capacite Infraprojects	25-Sep-2017	250	342.6	37.04	400	0.030	1.097
	Amber Enterprises	30-Jan-2018	859	1135	32.13	600	0.044	1.427
	IRCON International Limited	28-Sep-2018	475	416.65	-12.28	470.49	0.035	-0.428
	Rail Vikas Nigam Limited IPO	11-Apr-2019	19	19.05	0.26	481	0.036	0.009
	Prince Pipes and Fittings Ltd	30-Dec-2019	178	166.6	-6.40	500	0.037	-0.237
						13507.23		-3.6351
Real Estate	Godrej Properties^	5-Jan-2010	490	534	8.98	468.85	0.065	0.585
	DB Realty Ltd	29-Jan-2010	486	456.2	-6.13	1500	0.208	-1.278
	Jaypee Infratech Ltd	21-May-2010	102	91	-10.78	1650	0.229	-2.472
	Oberoi Realty Ltd IPO	20-Oct-2010	260	282.9	8.81	1028	0.143	1.258
	Prestige Estates Projects Ltd	27-Oct-2010	183	193.15	5.55	1200	0.167	0.925
	NBCC Ltd.	12-Apr-2012	106	96.95	-8.54	127	0.018	-0.151
	HUDCO	19-May-2017	60	72.55	20.92	1224.35	0.170	3.558
						7198.2		2.4247
Aerospace and Defense	Cochin Shipyard	11-Aug-2017	411	522	27.01	1442.01	0.202	5.449
	Apollo Microsystems	22-Jan-2018	263	441.75	67.97	156	0.022	1.484
	Bharat Dynamics	23-Mar-2018	428	397	-7.24	960.94	0.134	-0.974
	Hindustan Aeronautics Ltd	28-Mar-2018	1240	1133.1	-8.62	4144.06	0.580	-4.999
	Mazagon Dock Shipbuilders	12-Oct-2020	145	171.95	18.59	443.69	0.062	1.154
						7146.7		2.1140

*At the upper price band, Just Dial was price at 543, but the retail investors were allotted the shares at a lower price band 470.

^At the upper price band, Godrej Properties was price at 530, but the retail investors were allotted the shares at a lower price band 490.

Cochin Shipyard was offered to the employees and retail investors at a discount of Rs. 21 to the upper price band.

 

Underpricing across different sectors is represented by the weighted average of first day return for each sector. The weights for each company have been determined by dividing the issue size of the company by the total issue size of all the companies in that respective sector. The weight of each company is then multiplied by its listing gain percentage. Listing Gain percentage has been calculated as follows:

 

 

The underpricing for each sector has been calculated as a sum of weighted average listing gains of all the companies in that respective sector.

 

Table 2: Sector-wise Underpricing and Dispersion

Sectors	Under - pricing (%)	Standard Deviation	Coefficient of Variation
Banking	26.19	20.96	0.80
Financial Services Companies (Non-Banking)	4.74	17.29	3.65
Information Technology and Consulting	35.69	40.99	1.15
Pharmaceuticals and Healthcare	13.31	22.81	1.71
Oil and Gas Production and Marketing, Renewables and Metals and Mining	22.43	24.79	1.10
Chemicals	31.47	26.90	0.85
Retail, FMCG and consumer durables	51.91	54.47	1.05
Commerce and services	21.15	23.30	1.10
Agriculture and Agri inputs, Foods Processing and marketing	18.56	15.23	0.82
Automobile and Auto Components	10.73	17.16	1.60
Engineering, Construction and Infrastructure	-3.63	18.11	4.98
Real Estate	2.42	10.71	4.42
Aerospace and Defense	2.11	32.96	15.59

 

Graph 1: Sector-wise Underpricing (in percentage)

 

It can be observed that on an average companies in Retail, FMCG and Consumer Durables are underpriced the most (51.91%), followed by Information Technology and Consulting (35.69%), Chemicals (31.47%), Banking (26.19%), Oil and Gas Production and Marketing, Renewables and Metals and Mining (22.43%), Commerce and Services (21.15%), Agriculture and Agri inputs, Foods Processing and Marketing (18.56%), Pharmaceuticals and Healthcare (13.31%), Automobile and Auto Components (10.73%), Financial Services Companies (Non-Banking) (4.74%), Real Estate (2.42%), Aerospace and Defense (2.11%) and Engineering, Construction and Infrastructure (-3.63%).

 

The standard deviation and coefficient of variation for Retail, FMCG and Consumer Durables sector is 54.47% and 1.05, Information Technology and Consulting sector is 40.99% and 1.15, Chemicals sector is 26.90% and 0.85, Banking sector is 20.96% and 0.80, Oil and Gas Production and Marketing, Renewables and Metals and Mining is 24.79% and 1.10, Commerce and Services is 23.30% and 1.1, Agriculture and Agri inputs, Foods Processing and Marketing is 15.23% and 0.82, Pharmaceuticals and Healthcare is 22.81% and 1.71, Automobile and Auto Components is 17.16% and 1.6, Financial Services Companies (Non-Banking) is 17.29% and 3.65, Real Estate is 10.71% and 4.42, Aerospace and Defense is 32.96% and 15.59, Engineering, Construction and Infrastructure is 18.11% and 4.98, respectively.

 

It can be observed that all the sectors have a coefficient of variation greater than 0.80, implying that the first day return of the companies varies highly and cannot be fairly predicted by the weighted average first day return of the respective sector. This can be a result of the prevailing market conditions as even highly priced companies can give handsome (or at least positive) return in the periods of ‘Bull Run’ whereas as attractively priced or underpriced companies may give a negative return (or no return) during the period of ‘Bear Run’. Alternatively, ‘market inefficiencies’ can also be a factor to blame.

 

The listing gains of all companies in the Banking sector have shown a positive trend wherein the percentages range from 1.92% to maximum of 53.85%. Moreover, the listing gains have seen to have increased over the time period under study. Although all companies have resulted in positive gains with a weighted average of 26.19%, the range is quite wide to state that this sector is highly favorable for investing.

 

Out of 19 companies taken under the Financial Services Companies sector, 8 companies have shown negative gains or losses (the maximum loss being 11.07%). The remaining companies showing positive gains range from 0.71% to 56.93%. It can be said that the listing gains from this industry are highly unstable and inconsistent which makes it risky for retail investors to invest in this particular sector.

 

Under the Information Technology and Consulting industry, 2 out of 11 companies show loss (maximum 20.73%) and all of the rest show positive gains. Moreover, the industry gives a weighted average listing gain of 35.69% which is quite favorable. However, the spread of the listing gains which ranges from 3.27% to a maximum of 123.49% shows existence of outliers in the data and inconsistency of listing gains in the industry.

 

The gains in the Pharmaceuticals and Healthcare sector spread from a loss of 21.56% to a gain of 49.10% with 5 companies showing losses out of 11. Similarly, the gains in the Oil and Gas Production and Marketing, Renewables and Metals and Mining sector spread from a loss of 17.27% to a gain of 40% with 6 companies out of 10 showing losses.

 

All 7 companies in the Chemical industry have given positive listing gains ranging from 5.08% to 74.48% with a favorable weighted average of 31.47%, which makes this industry pretty attractive for investors.

 

Retail, FMCG and Consumer durables sector has 3 companies out of 7 with losses (maximum 25%) and the rest range from 10.07% to 114.30%. Here, DMart with listing gains of 114.30% is an outlier which has performed exceptionally well in its IPO. Although, the weighted average listing gains of this sector i.e. 51.91% is the highest of all sectors under study, investing in this industry may not be as fruitful for the retail investors as it may seem.

 

The companies in the Commerce and Services industry are moderately spread with a range of -11.09% to 33.87% with 3 companies with listing losses. If investors invest in the IPO of this sector, they would be taking a moderate to high risk.

 

All companies except one in the Agriculture and Agri-inputs, Foods Processing and Marketing sector have shown positive listing gains with a highest of 48.37%. Investing in this industry seems considerably safer and less risky.

 

The sector of Real Estate shows the range of listing gains from -10.78% to 20.92% with 3 companies out of 7 showing losses. This industry's listing gains has a narrow spread and the weighted average listing gains of 2.42%. Similarly, 2 companies out of 5 in the Aerospace and Defense industry show losses (maximum of 8.62%) and an outlier with 67.97% gains. The weighted average of this industry is 2.11%. These figures depict that both of these industries are comparatively unattractive to the investors.

 

In the Engineering, Construction and Infrastructure industry, 9 out of 20 companies show negative returns with a maximum of 21.64%. The remaining companies show positive gains ranging widely from 0.26% to 42.68% and the industry gives a negative weighted average of 3.6%. Hence it can be stated that investing in this sector can be highly risky and unfruitful because of its inconsistency and negative average.

 

The returns from issues in the Automobiles and Auto Components industry are highly spread with a range of -13.01% to 37.22%. Here, Endurance Technologies Ltd. is an outlier with 37.22% gains and the sector gives gains of 10.73% on an average. If investors invest in the IPO of this sector, they would be taking a high risk with 4 companies with listing losses.

 

CONCLUSION:

Underpricing across different sectors in the Indian Stock market was analyzed in the research. The study depicted that Retail, FMCG and Consumer Durables industry was underpriced the most (51.91%) while Engineering, Construction and Infrastructure industry issues were underpriced the least (-3.63%), or overpriced, out of all the 13 sectors analyzed.

 

On the basis of samples undertaken in the study, issues of banks and chemical companies are the safest option in the primary market for retail investors, with all the companies in these two sectors giving a positive return, enabling them to make immediate gains. This is followed by issues of Agriculture and Agri Inputs, Foods Processing and Marketing (except one company opening flat) and Information Technology and Consulting (except for 2 companies with negative listing) with all companies registering a positive gain on the debut on the bourses.

 

Therefore, if investors investing in IPOs perform thorough analysis of the issues and the market conditions during the IPO, then it could generate positive (or even handsome) returns in a very short period of time. Hence, investing in an IPO could be a window to make quick and easy profits. It can be further concluded that, the first day return of the companies varies highly and cannot be fairly predicted by the weighted average first day return of the respective sector.

 

LIMITATIONS:

This research, however, is subject to several limitations which should be borne in mind while considering the results. First, the Open Price of any Initial Public Offering is determined by its Premium in the Grey market which is affected by the investors’ sentiments. Moreover, any IPO and its valuation is subjected to the phase of business cycle and the Bull run or Bear run for IPO in the primary market for the particular year in which each offer was launched. These factors have not been considered for the study undertaken. Third, the data collected does not show any underpricing trend over the years of study for any selected sector because stock market condition and tendencies for the chosen years have not been taken into account. Fourth, most of the attractively priced IPOs witness oversubscription, sometimes even more than 100 times (or 10,000%), leaving retail investors with no shares being allotted.

 

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