chapter 5 determinants of ipo underpricing in india...determinants of ipo underpricing in india ......

Chapter 5 Determinants of IPO Underpricing

in India

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CHAPTER 5 DETERMINANTS OF IPO UNDERPRICING IN INDIA

5.1 INTRODUCTION Over the last two decade, one of the issues which have got the maximum attention in international financial literature relates to underpricing of IPOs. It is perhaps one of the most widely researched and debated topic in the area of financial economics with the general consensus that on an average, IPOs are priced lower than their first day closing price. The best-known pattern associated with the process of going public is the frequent incidence of large initial returns (the price change measured from the offering price to the market price on the first trading day often also referred to as underpricing) accruing to investors in IPOs of common stock. The available IPO literature indicates that there are positive abnormal returns measured from either the opening or the closing price on the first day of trading versus the offer price on IPOs. Accordingly, this Chapter focuses on identifying factors affecting underpricing of IPOs in the Indian capital market. Theoretical explanation for underpricing can be grouped under four broad categories: asymmetric information, institutional factors, control considerations, and behavioral approaches. Although, the asymmetric information model is regarded as the most established theoretical explanation for underpricing of IPOs, other explanations are equally important. The key parties to an IPO transaction are the issuing firm, the bank underwriting and marketing the deal, and investors. Asymmetric information model assumes that one of these parties knows more than the others. Baron (1982) assumes that the bank is better informed about demand conditions than the issuer, leading to a principal-agent problem in which underpricing is used to induce optimal selling effort. According to Rock (1986) hypothesis, some investors are better informed than others and so can avoid participating in overvalued IPOs. The resulting winner’s curse experienced by uninformed investors has

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to be countered by deliberate underpricing. Welch (1989) and others assume that the issuer is better informed about its true value, leading to an equilibrium in which higher-valued firms use underpricing as a signal. Finally, Benveniste & Spindt (1989) assume that underpricing compensates better-informed investors for truthfully revealing their information/choice before the issue price is finalized, thus reducing the expected amount of money left on the table. Institutional theories focus on three features of the marketplace: litigation, banks’ price stabilizing activities once trading starts, and taxes. Control theories argue that underpricing helps widen the shareholder base so as to reduce intervention by outside investors once the company is public. The behavioral theories, inter-alia, argue that an issuer may underprice an issue to encourage the first few potential investors to buy and subsequently induce a cascading effect resulting into all subsequent investors subscribing to the issue, irrespective of their own information. 5.2 FUNDAMENTAL DETERMINANTS OF IPOs UNDERPRICING As mentioned above, since initial return on IPOs depends on factors like asymmetric information, institutional factors, control considerations, and behavioral approaches, the degree of underpricing varies from country to country depending on maturity of their respective financial market as well as the socio-economic and institutional arrangements. This is adequately reflected in US and other international markets as shown in Table 3.1 on “International Evidence on Average Initial Return” as provided in Chapter 3 earlier. The table indicates variation in average initial return ranging from 4.7% in France to an incredibly high average initial return of 388% per cent in China. 5.3 PRIOR RESEARCH AND FACTOR SELECTION

International Research As highlighted in chapter 3 of this report, an analysis of past studies on underpricing of IPOs shows that these research have mainly focused on

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variables/parameters which could broadly be classified under three categories; company/issue specific parameters, industry related parameter, market related information and country specific macro-economic parameters. The variables parameters taken into consideration in prior research/studies on initial return four IPOs are as under: Beatty & Ritter (1985) inter alia, postulated the hypothesis that greater is the ex-ante uncertainty, the higher is the expected underpricing. This propositions have been tested vis-a-vis US registered 1028 IPOs of common stock issued during 1977-1982. The authors have used (i) the log (1+no. of uses of proceeds) listed in the prospectus and (ii) 1/gross proceeds as the proxies for ex-ante uncertainties. The issues for which there is greater ex-ante uncertainty tend to have a greater number of the uses of proceeds listed. The inverse of the gross proceeds capture empirical regularity that small offerings are speculative. In the other words, both these variables are positively related to the degree of underpricing. Peter Karlis (2000) used insider retention, investment bank size, IPO deal size and dummies for middle industries (telecom, biotech, computer and software) and internet sector industries as the variables affecting initial returns on IPOs. According to this study, IT and middle industries IPOs tend to be less priced leading to higher initial return. This is based on the hypothesis that industry with longer, more informative history will be less underpriced because there is less uncertainty about the issuing firm. Further, as the percentage of issued stock detained by the original owners and the insider of the company goes up giving quality signal to the investors, the demand for stock should increase thereby raising the initial first day gains and therefore the degree of underpricing. This is based on the general opinion in the finance industry hypothesis rather than from empirical study. According to this hypothesis, the firm will intentionally underprice their issued specifically for the attention gained by the first day run-up in the stock price. This gives the firm added publicity and media exposure while simultaneously proving the firm’s value to

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investors. This technique is referred to as “grandstanding an IPO” and it would be more frequently employed by smaller, less established firms only to draw investors’ attention and whose value is considered very uncertain by potential investors. Kooli & Suret (2001) has examined ex-ante uncertainty hypothesis, underwriter reputation hypothesis and market climate hypothesis in the context of the Canadian IPO market. This study has examined the relation between the degree of underpricing, Canadian IPOs, and ex ante uncertainty, from the period 1991-1998. In this model of underpricing, the market climate variable takes a value of 1 for hot period and zero for cold period, underwriter reputation takes a value of 1 for participation of a prestigious underwriter in the IPO and 0 otherwise. The model has ranked the top 25 underwriters under prestigious and non-prestigious category. Similarly, the notion of ‘hot’ and ‘cold’ market is based on the numbers of IPOs issues and the corresponding amount raised during the reference period. The proceeds of the issue have been used as a proxy for ex-ante uncertainty. According to this study, a negative relationship exists between the level of underpricing vis-a-vis ex-ante uncertainty and reputation of the underwriter. Further, IPOs issued during an upswing in the stock market experienced a higher underpricing than IPOs issued during a falling market. Guner, Onder & Rhoades (2004) has examined the relationship between reputation of an underwriter and the initial-day IPO return in the emerging market of Turkey during January, 1993 to June, 1999. The authors have used two reputation measures: the first measures assume that two underwriters with the highest number of IPOs lead or co-lead is the prestigious and the rest are not. This variable measures the visibility of underwriters in the IPO market. The second reputation variable is a proxy for the volumes of IPO business (either in dollar amount or in number of issues) lead or co-lead by an underwriter. According to their model, a negative relationship between the initial day IPO returns and the visibility measures is found. This indicated that since these underwriters are well known by the investors, they underprice the IPOs to a

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lesser degree. On the other hand, initial day IPO returns is positively related to the volume of IPOs indicating that the more IPOs an underwriter handles, the harder would be to sell the shares. Therefore, these underwriters have to underprice the issues to a higher degree. In addition, this model also indicates that age of the company has a positive and statistically significant coefficient indicating that the older firms will be underpriced to a higher degree which is in conflict with international findings. Venkatesh & Neupane (2004) has used a unique set of IPOs data in Thailand post Asian Financial crises to identify the relationship between initial market adjusted underpricing and the ownership concentration. The study developed a regression model to identify the causes of underpricing especially the impact of ownership concentration. Ownership concentration in this model has been measured by the proportion of the outstanding shares held by the top shareholders reported post IPOs. Ownership concentration factor highlights some results which are inconsistent with the Signalling hypothesis (relationship of high ownership and high underpricing), but consistent with some other studies in the context of the emerging market. High ownership concentration is not followed by high initial underpricing. In fact the reverse took place which indicates the offer price is already set high by the large shareholders of the company so as to drive away the kind of initial high returns. The regression analysis could not identify any other specific factor affecting initial underpricing of IPOs. Chi & Padgette (2005, A) researched 340 and 40 IPOs issued during 1996 and 1997 respectively to analyse their short and long run performance. The authors have documented short-run initial return of 127.3% and 3 years Buy & Hold Adjusted Returns (BHAR) of 10.7%. In addition, they identified the initial return and three years BHAR are negatively co-related, i.e. shares that have high initial return tend to have low long run performance and vice versa. According to authors, the main cause of high initial underpricing is much larger demand than the number of shares offered.

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Chi & Padgette (2005, B) studied the initial underpricing of 668 IPOs issued in Shanghai and Shenzen between 1996 and 2000. The main explanation for the high initial return (298% for A shares and 25% for B shares) is much larger demand than the offer of the shares, in a proportion of 50: 1. The natural log of offer size is also negatively related to initial return, which is in line with the ex-ante uncertainty hypothesis, because larger IPOs are in general issued by large and old companies having longer historical data and better known to investors. High-tech dummy is related to high initial underpricings, indicating that investors consider companies that operate in high-tech industries riskier and hence demand high returns. Procianoy & Cigerza (2007) in his study on “IPOs in Emerging Markets : A comparison of Brazil, India and China” has used multivariate linear regression model using OFFER SIZE (gross proceedings), REPUTATION– proxy being calculated as the number of IPOs that each bank is coordinating divided by the total of IPOs in each country, OFFER UPPER –quotient of Offer Price / Upper Price of the price band in the Book building, HIGHTECH – dummy variable to identify companies that produce goods using high-tech content such as pharmaceutical, software, telecommunication equipment, computational hardware, semiconductors, and aerospace industry, AFTERMARKET – performance of the benchmark for each country, one month before, or after, the IPO date, INTEREST RATE –the effective rate for 91-Day Government of India T Bill rates in India, Foreign Direct Investment – FDI variation between IPO year and year before, Gross Domestic Product (GDP) annual growth, INFLATION etc. as the variables influencing underpricing in Brazil, India and China. Large offers are expected to have less initial underpricing because they tend to be better priced and are less risky. Similarly, IPOs coordinated by high-reputation banks have smaller initial returns and non-negative positive long-run performance. Investment banks define a price band – values between the lower

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and the upper prices – in the beginning of the book building process to set the IPO price. Then, the coordinating bank contact as many as possible investors in order to evaluate the demand for the shares offered and it uses this information to set the offer price. If the demand is high, the bank sets the price in the upper values of the price band; if the demand is low, the bank sets in the lower values. Thus, if the OFFER_UPPER quotient is close to one, the demand that the coordinating bank identified is high, if it is below one, the demand is lower. It is expected to find a positive relation between OFFER_UPPER and Initial Returns. Further products using High-tech industries are considered riskier than traditional ones resulting in higher initial underpricing. FDI has been used as a proxy for higher stocks and IPOs demand. Although investment in stock market assets is different from FDI, both imply different risk perception by investors causing higher demand for them. IPOs issued in years when the interest rate is higher are more underpriced. The rationale is that investor will demand higher return if government bonds are paying higher yields. Investment bank with good reputation will lose market share when their stock valuation are inaccurate. GDP growth rate may influence IPO’s short term and long term performance because its increase (decrease) influence positively (negatively) future business opportunities in the Country. Countries with high inflation rates are, in general, considered riskier by the foreign investors. At the same time, stocks are considered safe investment by the local investor to neutralise the inflationary impact. Higher inflation rate are expected to be related to higher IPO performance. INFLATION, OFFERSIZE and REPUTATION have been excluded from the reported regressions as they are not found to be statistically significant at 10 per cent. In this study, AFTERMARKET, BEFOREMARKET and HIGHTECH are the only ones that have acceptable statistical significance at 10% or below. Bundoo (2007) has inter-alia, used log value of gross proceeds and market capitalization and the return on market index (SEMDEX) as determinants initial return in his analysis of underpricing of IPOs in Mauritius. Gross

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proceeds and market capitalization are indicators of the size of the company and are expected to be positively related to underpricing as companies large in size signal their intrinsic value by underpricing by a higher margin. The coefficient of both variables is significant at 10 per cent level. The shares already listed on the stock exchanges are in direct competition with IPOs for investors’ fund. If the return on market index is going up, then it is natural to expect that to attract investors to IPOs, a higher degree of underpricing is required. The final regression model showed that the return on market index and size of the issue (measured by log of issue proceeds) are statistically significant variables affecting short run underpricing. The independent variables used in the multivariate analysis of the first day trading performance of the IPOs in the Brazilian Market between January, 2004 to April, 2007 by Faria (2007) composed of age of the firm, ratio of primary offer size to the total offer size and nine key ratios: sales, growth in sales, solvency, liquidity, fixed asset turnover, total asset turnover, return on equity, return on assets and operation profit margin. The author has observed that out of all the above independent variables, only return on equity is statistically significant with negative correlation with underpricing. While examining the determinants of initial IPO performance in Hong Kong and Taiwan, Lin & Hsu (2008) has, inter alia, regressed initial return on pricing determinants, such as allotment ratio (total IPO shares issued over the number of shares subscribed by the participants applicants), retained ownership (percentage of Directors and senior management ownership), IPO proceeds, debt ratio (proportion of bank loan over total asset), dummies for underwriters’ reputation (based on the asset size), institutional ownership (based on total shares owned by institutions), size (based on the asset size), etc. The regression result indicates that allotment ratio of the subscribed shares is the most consistent determinants for IPO underpricing in both the Hong Kong and Taiwanese market, thereby supporting Rock’s(1986) adverse

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selection theory of underpricing, which argues that IPO shares are underpriced so as to reduce winner’s curse for the uninformed investors. However, the model finds no relationship between IPO underpricing vis-à-vis IPO proceeds, ownership retention rate, underwriters’ reputation, institutional ownership and debt ratio thereby not supporting the ex-ante uncertainty hypothesis. Studies in the Indian Context

Madhusoodanan & Thiripalraju (1997) analysed the Indian IPO market for the short term as well as long term underpricing. They have also examined the impact of issue size on the extent of underpricing in these offerings and the performance of merchant banker in pricing these issues. The study indicates that, in general, the underpricing in the Indian IPOs in the short run is higher than the experiences of other countries. The study indicates that in the long run, Indian offerings have given high returns compared to negative returns reported from other countries. The study also reveals that none of the merchant bankers showed any better pricing capabilities. While analysing 386 IPOs issued between 1992 and 1994 in the Bombay Stock Exchange, Krishnamurti & Kumar (2002) in their study, they have, inter alia, documented time lag between the closing date and the listing date of IPOs as one of the important reasons for underpricing of IPOs in India as it increases the perceived risk of the investors and hence they demand more return. They also suggested but not tested that higher IPOs underpricing in India because of the presence of individual and small investors, who are less informed than the large investors. Presence of a large number of uninformed investors would require the issuers to underprice their IPOs to a large extent to induce these investors to invest in IPOs (Rock 1986). Saurabh Ghosh (2002) has examined the uncertainty and signalling models of underpricing in the Indian context over the last decade. The empirical

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findings show that there exists positive relationship between IPO underpricing and ex-ante measures of risk proxies. It also shows that a subset of companies’ decision to raise funds subsequently depended on the initial returns and/or on the aftermarket returns. The relationship between underpricing and age of the company in a simple OLS framework show that the age of the company could not explain the variations in the initial returns. This might be because of the fact that most of the companies that went public during the last decade were young, with an average age of seven and half years (and a low variance). Since most of the companies that taped the capital market were young in terms of their age, it seems that the Indian investors’ did not frame their opinion about the viability of a corporate from their age profile. Thereafter, the size of the project was taken as a proxy for the risk content of an issue. As expected the coefficient of SIZE turned out to be negative and was significant at 1 per cent level. This shows underpricing was less for the issues that collected large amount from the public than for the smaller issues. The Indian investors seemed to consider larger issues to be less risky. Next, In order to examine whether the sector specific risk could explain underpricing for India, this study divided all new companies into primary sector (Pri), manufacturing sector (Mfg), Software (Soft) and Services Sector (Ser). The regression result of underpricing as dependent variable vis-a-vis dummy variables for manufacturing, services, and software sectors shows that while the coefficients of manufacturing sector and service sector dummies are not significant, the coefficient of software dummy is positive and significantly different from zero at one per cent level. So the investors’ concerns (that got reflected in high underpricing) about such new issues are justified. Arwah (2003) in his paper on “Investments in IPOs in the Indian Capital Market” has considered the impact of factors like Issue Size, Age, Foreign Equity, Issue Rating, and Issued Capital on the level of underpricing.

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According to this study, a negative relationship exists between return on listing and the issue price i.e. lower the issue price higher is the return accrued. The relationship is found to statistically significant at 1% level of significance. It is further observed that there is a negative relation that exists between return on listing and the issue size which is statistically significant at 10% level. The negative relationship also holds vis-à-vis age of the company at the time of issue and is statistically significant at 1% level. As far as foreign equity is concerned, a positive relation is established between return on listing and the foreign equity holding present in the total equity of the company. The relationship has been found to be statistically significant (0.03 level). Return are found to be higher for the companies with foreign equity holding of 26% & above; and very low in case of the companies with foreign equity holding of below 26%.There is a negative relation that exists between return on listing and the issued capital of the company at the time of issue. The relationship is found to be statistically insignificant. Listing delay and the return on listing exhibit a negative relation i.e. less the amount of time taken to list an issue at the stock exchange, higher is the initial return and vice versa. This relationship is also found to be statistically significant at 1% level. Jaitly & Sharma (2004) have studied Indian IPOs after the end of Controller of Capital Issues (CCI) regulation by testing and confirming the ex-ante uncertainty hypothesis. The authors have used age and size of the companies as independent variables and offer price as dependent variable in their multivariate linear regression model, the authors observed a positive relationship between them, indicating that older and larger companies had higher IPO prices. They tested and accepted the information asymmetry hypothesis because they found that offer prices are higher when promoters (initial owners) keep more shares, as a signal of more commitment to the company and reduction of the asymmetric information gap.

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S.S.S. Kumar (2007) has analysed the short run and long run performance of Book built IPOs in India by performing a cross sectional regression with the short run initial returns as dependent variable and size (the natural log of the issue size), dummy for before market conditions ( assuming a value of zero if market has declined in at least half of the trading days in the month prior to the IPO opening and it will assume a value of 1 if the market has moved up) and quotient of offered price to the upper price as independent variables. The sample of this study includes all the new equity issues offered through book building route on the National Stock Exchange (NSE) from 1999 till May, 2007. The study is based on the presumption that larger the issue size less will be underpricing because the issues are followed and analysed by a large set of analysts. Further, if the general market conditions are buoyed the issue may draw more investors leading to a higher demand and if the demand was properly gauged during the book building process before the issue is opened then the offered price will be very close to the upper price limit. Since the number of shares is limited and the demand is not fully met, upon listing there may be lot of buying interest that may lead to the issue listing at a premium to the offer price. From the regression results it has been observed that only offer price quotient is found to be significant and the remaining variables are not statistically significant. Of course the Adj. R squared of the regression is rather low at 0.016852, which is not unusual in cross sectional regressions. Pandey & Vaidyanathan (2008) has studied the underpricing of IPOs listed at National Stock Exchange between 2004 to 2006. The multivariate regression analysis is based on factors like demand for the IPOs (which is a dummy variable which takes a value 0 if the issue is offered close to the lower end of the band and 1 otherwise), listing delay (the time lag between the closing date and listing date of an IPO), issue size and marketing expenditure (in millions of rupees) and their natural log is taken to avoid heteroscadisticity. Market change is the percentage change in the S&P 500 CNXNifty index on

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the day of listing of the issue. The result of this study shows that the coefficient of DEMAND is positive and significant at 1% indicating more underpricing if the issue is finally priced towards the higher end of the price band. Similarly, the coefficient of LISTNG_DELAY is positive and significant at the 10% level. The constant term is significant at the 5% level which indicates that\ there are some more variables to explain underpricing which were not included in our model. The coefficient of log of MARKETING EXPENSES is negative as hypothesized although not significant. It was mentioned earlier that how the listing delay affects the degree of underpricing is not clear. However from the regression results we find that such a delay increases the degree of underpricing. In fact a one day increase in listing would increase the underpricing by 2.88%. It seems that the investors demand a greater premium for their locked in money. Bansal & Khanna (2012) in their study on “Determines of IPOs underpricing: empirical evidence from Bombay Stock Exchange after Stock Market Crises”. An attempt has been in his study to design and test empirical models, which integrate theoretical, institutions and other factors which interact to explain ownership structure, ex ante information deciding the level of underpricing after the Stock Market Crises. The study is based on the IPOs that got listed at BSE during 2008-2011. Factors used in the multivariate regression are issue sizes, market capitalization, firm’s age, institutional non promoters, number of shares, private IPO firms, Indian promoters, foreign promoters, non-institutional non promoters and book build price mechanism have been used in this study. The results of the study shows that number of share offered, issue size, market capitalization, institutional non-promoters, and private IPO firms are statistically significant vis-à-vis the level of underpricing. The result exhibits a negative relationship between the numbers of shares offered, issue size and private IPOs vis-à-vis the level of underpricing. At the same time market capitalization is positively related to the level of underpricing. However, timing of IPOs, Firm’s age, Indian promoters, foreign

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promoters, non-institutional non-promoters and book build price mechanism are not found to be statistically significant indicating hardly relationship with the level of underpricing. 5.4 RATIONALE OF THE STUDY The objective of this chapter is to construct a model which could explain the level of possible underpricing for Indian IPOs. It is observed from the past international studies that they mainly focus on testing various theoretical explanation/hypothesis for short run underpricing of IPOs as well as identifying the main determinants for initial returns in the IPO market. Even in case of India, the studies mainly focus on identifying determinates for the short run performance of the IPOs, comparative studies of underpricing under different price regime, namely, fixed price and book building methods, etc. No attempt has been made so far to broadly cover all major factors significantly influencing underpricing by presenting a composite model in a multivariate regression analysis framework. Similarly, the essence of the time-frame with latest data on IPOs underpricing is also missing in the past studies. Even the latest study by Bansal & Khanna (March, 2012) on “Determinants of IPO Underpricing: An Empirical Evidence from Bombay Stock Exchange after Stock Market Crisis” is based on the IPOs that got listed on BSE during 2008 to 2011 and focused on limited variables like issue sizes, market capitalization, institutional non promoters, number of shares and private IPO firms only. Since IPOs are now a major source for investment especially by the Indian retail investors, and have gradually emerged as one of the important source for raising fund in the Indian primary market, it is important that the pricing of IPOs truly reflects the intrinsic value of the company. This will inculcate a fair degree of confidence among the potential investors and enable them to make informed investment decisions vis-à-vis offerings in the Indian IPO market. With strong market fundamentals and good prospect for growth, a sound capital market with a transparent mechanism for price discovery process will go a long way in leveraging India’s potential as a preferred destination for investment by both domestic as well as

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international investors. Hence from the policy perspective, an attempt has been made in this chapter to develop a composite model for explaining the possible level of short run underpricing in India by considering companies/issue specific factors, market specific factors, industry specific factors and country specific macro parameters. 5.5 METHODOLOGY Multivariate linear regression model (OLS framework) has been used in this study to identify variables that may explain the level of underpricing. To start with, initial return (dependent variable) has been regressed vis-à-vis 20 independent variables identified on the basis of the past research. Based on the results of bivariate regression analysis, 13 variables significantly influencing short run underpricing at 20% level of significance or below are identified in the first stage as factors affecting short run initial return on Indian IPOs. Since there is prior results hypothesising and explaining the relationship of the shortlisted variables vis-à-vis short run underpricing of IPOs and the direction of relationship, one tail test has been applied to test the level of significance of the short listed variables. The 13 variables identified at the first stage as detailed above are then regressed vis-à-vis initial return in within the framework of multivariate regression analysis. Thereafter, the pair-wise cross correlation coefficients are analysed to identify some of the overlapping independent variables which could be dropped so that no multicollinearity is encountered while performing the multivariate regression analysis. After identifying the overlapping independent variables, the multivariate regression analysis has been undertaken to identify factors which significantly influences the short run underpricing of Indian IPOs. The White test has been performed on the residuals to check the presence of Heteroscedasticity in the model suggested for predicting the possible level of underpricing. It is observed that no significant Heteroscedasticity was detected and hence the OLS estimation of the proposed model is satisfactory.

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5.6 DATA AND THEIR SOURCES Basic data for companies issuing IPOs from March, 2000 to December, 2011, have been obtained from Prime Database containing information, such as opening and closing date of issue, price band, offer price, employees share, date of listing, closing price at the end of 1st day, 7th day, 1 month, 3 months, 6 months, 1 year, 2 years and 3 years, details of the lead manager/co-manager, industry/sector, uses, etc. Thereafter, the details of income of the company, industry P/E ratio, date of certificate of incorporation, etc. are obtained from the draft prospectus filed by each of these issuing companies with SEBI. Some of the details about market values of IPOs at different moments, especially 1 year, 2 years, 3 years are accessed at www.moneycontrol.com. However, since there are a lot of missing data in respect of the IPOs issued between April, 2000 to March, 2010 especially in regard to the listing and closing price details for different moments the reference period for this study has subsequently been taken from April, 2002 to December, 2011 thereby covering 432 IPO issues. The details of GDP, Wholesale Price Index (WPI) and Index of Industrial Production (IIP) for the reference period have been obtained from the Central Statistical Organisation (CSO), Ministry of Statistics and Programme Implementation (www.mospi.nic.in) Department of Industrial Policy and Promotion (DIP&P), Ministry of Commerce and Industry website (www.dipp.nic.in). Both the WPI & IIP have been used to calculate and the time series data for inflation and rate of growth of industry. The details of the implicit yield at cut-off price for the 91 days Treasury Bills in the last week of the month immediately preceding the month in which the issue has been closed is obtained from RBI monthly bulletin as provided on its website (www.rbi.org.in). The Put-Call Ratio of NIFTY index option as a proxy for investors’ sentiment is sourced from National Stock Exchange (NSE). 5.7 EMPIRICAL RESULTS Based on past studies, it is observed that the variables affecting IPOs underpricing could broadly be classified into the following four categories and the variables for the present studies has accordingly been selected as under:

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IR Initial return (IR) or the first day return defined as the ratio between the first day (listing day) closing price of the securities and the offer price. It is calculated as the difference between the closing price of the share on the listing date of IPO and the offer price divided by the offer price.

A. Company/issue related variables IGP Inverse of the Gross Proceeds -Gross Proceeds being defined

as the total number of shares issued multiplied by the final offer price.

Uses Log (1+no. of uses uses). No. of uses as indicated in the draft prospectus.

CS Proxy for Company size /IPO Deal Size – defined in terms of the log value of the proceeds raised through the IPO route.

IRR Insider Retention – The proportion of issued stock retained by the original owners and/or reserved for the employees of the company as indicated in the draft prospectus.

TS Times Subscribed – The number of times an issue has been subscribed by all class of investors.

LD Listing Delay – Defined in terms of time lag between the closing date of the offer and listing of the issue at the Stock Exchange.

Age Age of the Company – log value of number of years calculated from the date of certificate of incorporation of the company to the offer date of the issue.

Offer Price

Dummy for Offer Price D1 If the final offer price is nearer to the lower end of the price band of the IPO, the dummy will take a value of 1 otherwise 0. D2 If the final offer price is nearer to the upper end of the price band of the IPO, the dummy will take a value of 1 otherwise 0.

Public Sector IPO

Dummy for public sector companies issuing IPO in the market. It takes a value of 1 for the private company issuing IPO, otherwise 0.

Income Total Income of the company – log value of the total income of the company as reported in the prospectus for the year immediately preceding the IPO issuing year.

B. Industry specific information Industry PE ratio

Industry’s Price to Earning (P/E) Ratio – Taken as the proxy for the overall growth potential of the industry.

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C. Market related information Investor sentiment

Proxy for Market Investment Sentiment –The put-call ratio of NIFTY index option has been taken as proxy for investor’s sentiment in the markets. When the number of traded call options outpaces the number of traded put options, this would signal a bullish sentiment and vice versa.

Market Climate

Dummy for market performance: If the market return (return on NIFTY index) during the month immediately preceding the date of issue of IPO is issued is greater than the average of the last three months (including the immediate preceding month), then the dummy variable takes a value of 1 otherwise 0.

Cos representing new economies

Dummy for the companies representing new economy: Biotech, pharma, telecom media, entertainment, IT/ ITES) takes a value of 1 otherwise 0.

IBRP IBRI

Proxy for the Investment Bank Reputation – The proxy being defined in terms of share in the value of IPO business (in rupee amount) managed or co-managed by an underwriter during the reference period divided by the total value of the IPOs business during the reference period. Proxy for the Investment Bank Reputation – The proxy being defined in terms of share in IPO business defined in terms of no. of issues managed or co-managed by an underwriter during the reference period divided by the total no. of IPO issues amount

Country Specific Macro Variables GDP Growth GDP annual growth Net FII Net Foreign Institutional Investment (FIIs) Inflow – Net FIIs

flows during the month immediately preceding the month in which the IPOs are issued

Inflation Inflation – Change in Wholesale Price Index during the month immediately preceding the month in which the IPOs are issued.

IIP Industrial Growth – Represented by the IIP figures released by the Ministry of Statistics & Programme Implementation/ Department of Industrial Production and Policy (DIP&P), Govt. of India during the month immediately preceding the month in which the IPOs are issued

CDROI Interest Rate - The yearly effective rate in percentage points for the 91 days Treasury Bills issued by the RBI on behalf of the Government of India in the last week of the month immediately preceding the month in which the IPOs are issued

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As a first step the dependent variable i.e. the initial return (IR) is regressed vis-à-vis each of the 20 variables one at a time (bivariate regression) to analyse their significance in explaining the level of underpricing in Indian IPO market. The result of the bivariate regression analysis is reported in Table 5.1 of this chapter. Based on the result of the bivariate regression analysis, all dependent variables significant at 20% and below level are initially shortlisted in the first stage for multivariate regression analysis. As mentioned above, since there are prior result hypothesising and explaining the relationship of the shortlisted variables vis-à-vis short run underpricing and direction of relationship, one tail test has been applied to test the level of significance of the short-listed variables. Based on these criteria, the independent parameters which qualify for multivariate modelling exercise includes Times Subscribed (TS), Company Size (CS), Listing Delay (LD), Interest Rate (CDROI), log value of inverse of gross proceeds (IGP), USES, Put- Call ratio taken as proxy for I_Sentiment, Inflation (INF), Industry PE ratio (IPE), Proxy for an Investment bank reputation in terms of value of IPO business (IBRP), Dummies for (i) Offer Price (D1) (ii) companies representing new economy (D4) and private companies IPOs (D5). Thereafter, 13 variables identified at the first stage as detailed above are then regressed vis-à-vis initial return within the framework of multivariate regression analysis. It is then observed that factors like CDROI, D1, IGP, and INF, becomes insignificant even at 20% level because of their multicollinearity with some of the identified variables. The result of the multivariate regression analysis with a respect to the 13 significant variables identified in the first stage of this analysis is provided in Table 5.2 of this chapter. An analysis of pairwise co-relation coefficient as provided in Table 5.3 of this chapter indicates that: (i) CDROI has a correlation coefficient of 0.19 and -0.11 vis-à-vis I_sentiment and LD respectively (ii) IGP has a correlation

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coefficient of 0.90 and -0.18 with CS and D5 respectively (iii) D1 has correlation coefficient of -0.35 and -0.18 vis-a-vis LD and D5 respectively. It also has correlation coefficient of 0.14 with respect to USES (iv) IBRP has a correlation coefficient of 0.23 and 0.24 vis-à-vis I_sentiment and TS respectively. It also has correlation coefficient of 21.2% with respect to different. After taking into consideration the pair-wise correlation and further filtering of variables, the model becomes more robust with TS, CS, I_Sentiment, Industry PE ratio, uses, D4 and D5 at 20% level of significance and below. Thereafter, variables relating to CDROI, D1, IBRP, IGP, INF, LD are added one at a time to see their likely impact on the overall robustness of the model. It is observed that after incorporating CDROI, D1, IGP, INF, one at a time, there is no change in the statistical parameters of the significant variables already present in the model and overall performance of the model. As the significance of variables have been tested at 20% level of significance and below (one tail test), It is observed that when IBRP and LD with ‘t’ value of -1.12 and 1.15 respectively are added to the multivariate regression model, both the variables also exhibit significant relationship vis-à-vis short run underpricing at 20% and below (one tail test). Further, overall of performance of the model also improves in terms of explanatory power of the model. Apart from these 9 significant factors, additional factor(s) do not contribute to augment the explanatory power of the model. The final result of the multivariate regression analysis is summarised in Table 5.4 of this chapter.

The sign of the co-efficient of the significant variables of this model is also found to be in conformity with the findings of international/ Indian studies on underpricing of IPOs. A comparative chart on the findings of the international/ Indian studies vis-à-vis the present study is provided in Table 5.5 of this Chapter.

Times Subscribed: It is observed that TS is the most important factor affecting short run underpricing of IPOs. This variable is positively related with short run underpricing of IPOs with a ‘t’ value of 11.68961. The TS ratio

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indicating the number of times an issue is subscribed is regarded as one of the important indicator of uncertainty in the IPOs’ literature on IPOs. Higher the extent to which an issue is subscribed, higher is the uncertainty about getting the share allotted in oversubscribed issues. Hence, a representative investor will submit purchase order if more money is “left on the table” in the form of higher discount resulting into higher underpricing.

Company Size: The variable CS representing company size is found to be positively related to short run underpricing with ‘t’ value of -4.788974. The positive relationship is explained by the facts that large IPO offers in India are expected to have less initial underpricing because they tend to be better priced and a less risky.

Investor Sentiment: The proxy for investor sentiment (defined in terms of put-call ratio of NIFTY index option ) and industry Price Earnings (PE) ratio and covered in the present study are not found to be considered as variables which affects short run underpricing in any of the International/Indian studies reviewed and discussed in Chapter-3 of this report. The investor sentiment represented by the put-call ratio is negatively related to the short run underpricing with a ‘t’ value of -2.632723. This relationship is explained by the fact that a bullish trend in the stock market represented by high put call ratio results into higher demand for IPOs and hence lower underpricing of IPOs. Uses: The log value of (1+ number of uses of IPO proceeds) listed in the prospectus have been taken as one of the important proxy for ex-ante uncertainty for an IPO issue. The greater the number of uses listed in the prospectus of a company, greater is the uncertainty about the end utilization of the IPO proceeds. The investor view investment opportunities in such issues risky and therefore demand higher level of underpricing. Hence, there is a demand for higher level of underpricing by the investors. Accordingly, the finding of this study is in conformity with international findings on the relationship between uses of IPO proceeds and underpricing with a ‘t’ value of 1.806345.

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Listing Delay: The LD (listing delay expressed as the time lag between the closing date and the listing date of often issue) is positively related with short run underpricing with a ‘t’ value of 1.737816. As there is a delay in listing of the issue, the market starts revising its expectation about the company resulting into higher uncertainty and the investors accordingly demanding a higher degree of underpricing. Industry PE Ratio: The Industry PE ratio is considered to be one of the most important indicators of the growth potential of an industry. The positive relationship between industry PE ratio and short run underpricing with a ‘t’ value of 1.630414 could be explained in terms of the fact that the investors is not very sure whether a company accessing the IPO market with a new issue will be able to catch up with the pace of the growth of the industry/sector expressed in terms of high PE ratio. To compensate for this uncertainty, the investors demand a higher degree of underpricing of IPOs. Investment Bank Reputation: The investment bank’s reputation defined in terms of share in the total value of IPO business managed or co-managed by an underwriter during a given reference period is found to be negatively related with the degree of underpricing with a ‘t’ value of -1.18218. When IPOs are managed/underwritten by reputed investment banks, it gives signal to the market that there has been a proper due diligence of these issues and hence their pricing truly reflects the fundamentals of the companies and the investors are accordingly willing to subscribe to these issues at less discount. Hence, an investment banks with high reputation will tend to underprice IPOs to a lesser degree. Dummy D4: The dummy D4 representing the new economy companies such as IT and ITeS, media and entertainment, telecom, biotech, Pharma etc. is found to be negatively related with the short run underpricing with a t value of 1.396525. This indicates that industries with shorter and less information history will be more under-priced as there is more uncertainty about the

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issuing companies. Further, products using hi-tech industry are considered risky than the traditional industry resulting in higher initial underpricing. The ‘high risk high growth’ nature of these companies gives rise to higher uncertainty resulting into higher degree of underpricing. Dummy D5: The negative relationship between the dummy D5 (representing private companies IPOs) and short run underpricing (with ‘t’ value of -2.60366) indicates that there will be less underpricing for private companies’ IPOs vis-à-vis the public sector IPOs as the private companies are perceived to be better managed with good growth potential. The majority share holdings of the Government in the public sector IPOs gives the impression that there will be more interference by them in the day to day operation of such companies and as such, the management will have less financial and operational autonomy. This may adversely affect the future growth potential of such public sector companies. The stated policy of the disinvestment of public sector undertakings further gives impression that Government is not able to meet its expenditure out of its own revenue resources and hence resorting to divestment of their share in these companies to meet the shortfall. All these factors give rise to uncertainty and hence demand for a higher degree underpricing by the investor. It is observed from the model that R square and adjusted R square in this model is low at 38.02% and 36.30% respectively which are in conformity with ex-ante uncertainty hypothesis of underpricing. In the other words if the R square was high, it would imply that the actual initial return on an offering is predictable. The theory states that there is a positive relation between ex-ante uncertainty and expected initial return. The reason for this positive relation is that it is difficult for investors to predict the actual initial return for an issue coming to the market, giving rise to the winner’s curse problem, even though the average initial return in a large sample can be predicted with reasonable accuracy. Accordingly, the R and adjusted R square ratio arrived at in the final model of this study is consistent with the proposition that the greater is

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the ex-ante uncertainty about the value of an issue, the greater is the expected underpricing. 5.8 SUMMARY AND CONCLUSION An attempt has been made to present a composite model on underpricing after broadly covering all major factors covering companies/issue related parameters, market related information and macro-parameters which could possibly affect underpricing in the Indian IPOs. Based on the multivariate regression model developed for determining the possible level of short run underpricing, the predicted short-run underpricing comes out to be 26.11 % which is higher than actual short-run underpricing of 24.93%. This shown that the market for Indian IPOs is overpriced and the difference of (-) 1.18 is recovered through price correction over a 6 months when the return on IPOs becomes (-) 1.21%.

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Table 5.1: Results of Bivariate regression analysis The Table below shows the result of the bivariate regression analysis with IR as the dependent variables.

Variables Co-efficient (t statistics)

CDROI -0.029323 (-1.515098*)

CS -0.130401 (-3.567408*)

I_Sentiment -0.382349 (-2.508626*)

IBRP -0.005595 (-1.332057*)

IBRI 0.005123 (0.734003)

IGP 0.063896 (3.585411*)

IIP 0.003436 (0.522147)

IPE

0.003618 (2.231194*)

Income -0.096729 (-0.417389)

Age 0.039093 (0.423853)

TS 0.011147 (11.84548*)

USES 0.193183 (1.475995*)

LD 0.019239 (3.749942*)

Net _FII 8.98E-06 (0.642232)

INF -0.026800 (-2.793067*)

IIP 0.003436 (0.522147)

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IRR 0.005035 (0.698123)

GDP_Growth -0.003452 (-0.178378)

D1 -0.295059 (-3.564244*)

D2 0.046116 (0.851441)

D3 0.005035 (0.698123)

D4 0.209422 (3.663342*)

D5 -0.190367 (-1.534628*)

IR- Initial Return; CDROI – interest rate expressed in terms of 91 days GoI T – bill, CS – Proxy for company size defined in terms of log value of proceeds raised, I_Sentiment – investors sentiment expressed in terms of put/call ratio, IBRP – proxy for investment bank reputation in terms of proceeds raised ; IBRI - proxy for investment bank reputation in terms of no. of issues managed/co-managed ; IGP – log value of inverse of gross proceeds, IPE – industry PE ratio, Income – log value of total income of the company, Age – log value of the age of company expressed in terms of no. of years, TS - time subscribed, Uses - Log (of 1 + no. of uses), LD – Listing Delay, Net _FII - net foreign institutional inflows, INF – inflation, IIP- industrial growth, IRR – insider retention by employees/ original owner, GDP_growth – annual growth rate of GDP, D1 – dummy for final offer price in the lower end of the price band, D2 - dummy for final offer price in the upper end of the price band, D3 – dummy for market performance, D4 – dummy for companies representing new economy, D5 - dummy for private companies IPO; *Variables significant at 20% level and below (One tail test).

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Table 5.2: Results of the Multivariate regression analysis with variables found to be significant in the bivariate analysis

The Table below shows the result of the multivariate regression analysis with IR as the dependent variable vis-a-vis variables found to be significant in the bivariate analysis


Intercept 2.031027 (4.329678)

CDROI -0.013881 (-0.732420)

CS -0.176134 (-4.628401*)

D1 -0.077810 (-0.915552)

D4 0.076793 (1.342067*)

I_Sentiment -0.374624 (-2.165885*)

IBRP -0.000996 (-1.121935)

IGP -6.65E-05 (-0.246922)

INF 0.000914 (0.083374)

IPE 0.002371 (1.754017*)

D5 -0.281783 (-1.992651*)

TS 0.010225 (10.96944*)

USES 0.240909 (1.800642*)

LD 0.006848 (1.158885)

R Squared 0.382896 Adj. R-Squared 0.357669

IR- Initial Return ; CDROI – interest rate expressed in terms of 91 days GoI T – bill, CS – Proxy for company size defined in terms of log value of proceeds raised, D1 – dummy for final offer price in the lower end of the price band D4 – dummy for companies representing new economy, I_Sentiment – investors sentiment expressed in terms of put/call ratio, IBRP – proxy for investment bank reputation in terms of proceeds, IGP-log value of inverse of gross proceeds, INF – inflation, IPE – industry PE ratio, D5 - dummy for private companies IPO. TS - Time subscribed, Uses - Log (of 1 + no. of uses), LD – Listing Delay, *Variables significant at 20% level and below (One tail test).

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Table 5.3: Pairwise correlation between variables found significant in the first stage of multivariate regression analysis

CDROI CS D1 D4 I_SENTIMENT IBRP IGP INF IPE D5 TS USES LD

CDROI 1 -0.07619 0.035123 -0.03149 0.191211 -0.05489 0.105696 0.286417 0.010925 0.092337 -0.05938 0.057765 -0.11019

CS -0.07619 1 0.071122 -0.11796 0.061239 0.001335 -0.9031 -0.0452 0.011149 -0.15396 0.143529 -0.16479 -0.22238

D1 0.035123 0.071122 1 -0.01247 0.044616 -0.00897 -0.11439 0.124261 0.08794 0.061748 -0.16094 0.027418 -0.20962

D4 -0.03149 -0.11796 -0.01247 1 -0.06675 0.060296 0.154566 -0.06811 0.033867 0.109231 0.16059 0.094776 0.045226

I_SENTIMENT 0.191211 0.061239 0.044616 -0.06675 1 -0.2312 -0.04551 0.045454 0.147312 0.211686 0.093207 0.219737 -0.03132

IBRP -0.05489 0.001335 -0.00897 0.060296 -0.2312 1 0.00071 -0.07864 -0.07873 -0.17035 -0.02393 -0.01026 0.071672

IGP 0.105696 -0.9031 -0.11439 0.154566 -0.04551 0.00071 1 0.062248 -0.02345 0.213153 -0.17522 0.184565 0.251051

INF 0.286417 -0.0452 0.124261 -0.06811 0.045454 -0.07864 0.062248 1 -0.04505 0.090511 -0.18164 -0.14042 -0.35234

IPE 0.010925 0.011149 0.08794 0.033867 0.147312 -0.07873 -0.02345 -0.04505 1 0.014994 0.101511 0.021046 0.108089

PVTIPO 0.092337 -0.15396 0.061748 0.109231 0.211686 -0.17035 0.213153 0.090511 0.014994 1 -0.0881 0.269157 -0.07596

TS -0.05938 0.143529 -0.16094 0.16059 0.093207 -0.02393 -0.17522 -0.18164 0.101511 -0.0881 1 -0.02164 0.024527

USES 0.057765 -0.16479 0.027418 0.094776 0.219737 -0.01026 0.184565 -0.14042 0.021046 0.269157 -0.02164 1 0.111024

LD -0.11019 -0.22238 -0.20962 0.045226 -0.03132 0.071672 0.251051 -0.35234 0.108089 -0.07596 0.024527 0.111024 1

CDROI – interest rate expressed in terms of 91 days GoI T – bill, CS – Proxy for company size defined in terms of log value of proceeds raised, D1 – dummy for final offer price in the lower end of the price band D4 – dummy for companies representing new economy, I_Sentiment – investors sentiment expressed in terms of put/call ratio, IBRP – proxy for investment bank reputation in terms of proceeds, IGP-log value of inverse of gross proceeds, INF – inflation, IPE – industry PE ratio, D5 - dummy for private companies IPO. TS - times subscribed, Uses - Log (of 1 + no. of uses), LD – Listing Delay,

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Table 5.4: Final results of Multivariate regression analysis with factors shortlisted for short run underpricing model

The Table below shows the result of the multivariate regression analysis with IR as the dependent variable

Variables Co-efficient

(t statistics)

Intercept 1.942443 (4.540695)

CS -0.176552 (-4.788974)

D4 0.079010 (1.396525)

I_Sentiment -0.415502 (-2.632723)

IPE 0.002170 (1.630414)

D5 -0.289732 (-2.603667)

TS 0.010435 (11.68961)

USES 0.236813 (1.806345)

LD 0.008974 (1.737816)

IBRP -0.001041 (-1.182188)

R Squared 0.380261 Adj. R-Squared 0.362993

IR- Initial Return ; CS – Proxy for company size defined in terms of log value of proceeds raised through IPOs, D4 – dummy for companies representing new economy, I_Sentiment – proxy for investor sentiment expressed in terms of put-call ratio, IPE – industry PE ratio, D5 - dummy for private companies IPO, TS - time subscribed, Uses - Log (of 1 + no. of uses), LD – Listing Delay, IBRP – proxy for investment bank reputation in terms of proceeds; *Variables significant at 20% level and below (One tail test).

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Table 5.5: Summary of the past studies/research vis-a-vis findings of present study on underpricing of IPOs S.No. Variables Direction of

relationship Explanation International/Indian Studies Present study*

Coefficient (t statistics)

1. Proxies for ex-ante uncertainty: (i) the log (1+no. of uses of

proceeds) listed in the prospectus and

(ii) 1/gross proceeds as the proxies for ex-ante uncertainties.

Positive

Positive

(i) The issues for which there is greater ex-ante uncertainty tend to have a greater number of the uses of proceeds listed.

(ii) The inverse of the gross proceeds captures the empirical regularity that small offerings are more speculative.

Both these variables are positively related to the degree of underpricing.

� Beatty & Ritter (1985) – USA � Kooli & Suret (Jan 2007) –

Canada

0.236813 (1.806345)

2. IPO Deal Size used as a proxy for company size/market capitalisation

Negative The dollar value of the no. of shares issued multiplied by the IPO price. Large offers are expected to have less initial underpricing because they tend to be better priced and are less risky.

� Peter Karlis (April, 2000) – USA � Saurabh Ghosh (October, 2002) –

India � Arwah (January, 2003) – India � Bansal & Khanna (March, 2012) –

India

-0.176552 (-4.788974)

3. Age of the Company Positive The period between the date of incorporation of the company and the date of date of issue of IPOs expressed in number of years. A positive relationship between age and underpricing, indicating that older and larger companies had higher IPO prices and hence less underpricing.

� Guner, Onder & Rhoades (January 2004) – Turkey � Arwah (January, 2003) – India

4. Insider Retention Positive

(i) The percentage of the issued stock retained by the original owners and insider of the company. As this percentage go up, by way of a quality signal to the investors, they will tend to keep the price low and higher underpricing to facilitate higher demand for future public offerings.

(i) Peter Karlis (April, 2000) – USA (ii) Venkatesh & Neupane (2004) –

Thailand

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S.No. Variables Direction of relationship

Explanation International/Indian Studies Present study* Coefficient (t statistics)

Negative

(ii) Ownership concentration measured by the proportion of the outstanding shares held by the top shareholders reported post IPOs. Results inconsistent with the Signalling hypothesis (relationship of high ownership and high underpricing), but consistent with some other studies in the emerging market.

The opposite relation shows that the offer price was already set high by the large shareholders of the company so as to drive away the kind of initial high returns.

5. Investment Bank Reputation Negative Positive Positive

Proxy for IBR- in terms of share in IPO business (either in dollar amount or in no of issues) managed or co-managed by an underwriter; (i) An Investment Banker with high

reputation will tend to underprice an IPO issues to a lesser degree.

(ii) The more IPOs an underwriter handles, the harder would be to sell the shares.

(iii) Dual affect – motivation of an investment bank to preserve their reputation -information and signaling -Limiting legal liability

� Guner, Onder & Rhoades (January 2004) – Turkey � Peter Karlis(April,2000) – USA

Investment Bank Reputation defined in terms of share in IPO business (in rupees) managed/co-managed by an investment bank,

-0.001041 (-1.182188)

6. Allotment ratio Negative Total IPO shares issued over the number of shares subscribed by the investors. Allotment ratio of the subscribed shares is the most consistent determinants for IPO underpricing thereby supporting Rock’s (1986) adverse selection theory of underpricing, which argues that IPO shares are underpriced so as to reduce winner’s curse for the uninformed investors.

� Lin and Hsu (2008) – Hong Kong and Taiwan

Times subscribed (TS) which is inverse of the allotment ratio

0.01035 (11.68961)

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7. Listing Delay Positive Listing delay (time lag between the closing date and listing date of IPOs) More the delay in listing, there will be more uncertainty leading to higher underpricing. It seems that the investors demand a greater premium for their locked in money.

� Arwah (January, 2003) – India � Pandey & Vaidynathan

(December 2008) – India

0.008974 (1.737816)

8. GDP Growth Negative GDP annual growth may influence IPOs performance. A better growth potential may improve the overall business climate resulting into competing demand for investible funds. Hence to attract more funds, the IPOs may have to offer large discount resulting into higher degree of underpricing.

� Procianoy & Cigerza (August 2007) –Brazil, India and China.

9. Interest Rate Positive There is a positive relation between interest rates and asset pricing. In a period of high interest rate regime, the price for bonds fall, and in order to hedge the return on their investment, investors are willing to move to the stock market. As the stock market and the IPO segment compete with each other for the investable funds, the issuers may resort to a higher degree of underpricing to attract more funds for IPOs.


10. Inflation Positive Countries with high inflation rates are, in general, considered riskier by the investors. The period of high inflation results into lower return on hedging instruments. At the same time, stocks are considered safe investment to hedge against the inflationary impact. As a result return investors are willing to move to the stock market resulting into higher underpricing of IPOs.


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11. Foreign Direct Investment Positive FDI variation between IPO year and year before. FDI has been used as a proxy for higher stocks and IPOs demand. Although investment in stock market assets is different from FDI, both imply different risk perception by investors causing higher demand for them. A positive relation between FDI variation and IPO underpricing is expected


12. Offer Price Negative

Negative

(i) if the demand is low, the bank sets the price in the lower values of the price band (D1). Alternatively, if the demand is high, the I Banker sets the price in the upper values of the price band (D2); It is expected to find a negative relation between the offer price and underpricing.

(ii) Indian investors consider the offer with premium to be less risky and therefore resulting underpricing to be significantly less for such issue.

� Procianoy & Cigerza (August 2007) –Brazil, India and China. � Saurabh Ghosh (October, 2002) –

India � Arwah (January, 2003) – India

13. Dummy for IT/Middle Industries Positive Industries with a shorter and less informative history will be more underpriced as there is more uncertainty about the issuing firm. Further products using high-tech industries are considered riskier than traditional ones resulting in higher initial underpricing.

� Peter Karlis (April,2000) – USA � Procianoy & Cigerza (August

2007) –Brazil, India and China. � Saurabh Ghosh (October, 2002)

– India

0.079010 (1.396525)

14. Market Climate Positive

The market climate variable takes a value of 1 for hot period and zero for cold period. The notion of ‘hot’ and ‘cold’ market is based on the numbers of IPOs and the corresponding amount raised during a given year under the reference period. During a hot period, there is an overall demand for stocks in the secondary market hence to attract investors in the IPO market the issuer

� Kooli & Suret (January 2007) - Canada � Bundoo (2007)- Mauritius

Put-call ratio of NIFTY index taken as proxy for Investor sentiment is negatively related to Underpricing

-0.415502 (-2.632732)

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must keep the price low and hence higher degree of underpricing. In the other words, if the return on market index goes up, it is natural to expect that in order to attract the investors to the IPOs market a higher degree of underpricing is required as IPOs are in direct competition with the securities market for attracting investment.

15. Dummy for Pvt. Cos IPOs/ PSUs IPOs

Negative There is a more demand for private companies IPOs vis-à-vis public sector IPOs resulting into less underpricing. Due to more operational and financial autonomy, private companies have better growth opportunities.

(i) Bansal & Khanna (March, 2012) – India

-0.001041 (-1.182188)

*Two of the variables found significant in the multivariate regression model developed in this chapter, namely, industry PE ratio and investor sentiment (defined in terms of put call ratio in the stock option segment of the market) are not found to be considered in any of the International/Indian studies covered in Chapter 3 on “Underpricing of IPOs: Theory and Empirical Study”.

chapter 5 determinants of ipo underpricing in india...determinants of ipo underpricing in india ......

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