Analysis of factors affecting short term performance IPOs in India
Dr. Pritpal Singh Bhullar
Assistant Professor
Department of Humanities and Management,
Giani Zail Singh PTU Campus Bathinda
Dr. Dyal Bhatnagar
Assistant Professor
University School of Business Studies,
Punjabi University, Guru Kashi Campus, Talwandi Sabo
ABSTRACT
Initial Public Offer (IPO) plays a role of new blood in the nerves of firms as the firms try to raise funds for their forthcoming ventures through IPOs. This paper examines the one year and six month performance of IPOs launched by companies of various sectors during year 2007 to year 2012. The study comprises of comparative analysis of the performance of the IPOs in terms of average return to that of Sensex pertaining to all companies of various sectors of Indian economy. Multiple regression has been used to analyze the impact of various independent variables on the IPO return for 6 months as well as 1 year. The study has been done to analyse the factors affecting the performance of IPOs. Independent variables like Oversubscription of IPOs, time delay in IPO listed, IPO offer Price, Market return in terms of Sensex return for the same time period have been considered to gauge their impact on IPO performance. Attempt has been made to weigh the macro as well as micro economic factors and also market trend during the specified period. The analysis highlights the impact of various factors on IPO performance on short term basis.
Keywords – IPO performance, Stock return, Stock Volatility, Sensex return, Sensex Volatility, Multiple regression, Micro economic factors
JEL Code – G1 – General Financial Markets
Introduction
An IPO acts the same way for company as blood acts for a human body. Through IPO, companies can estimate their brand value in investors’ mind. Undervalue and overvalue of IPO depends upon the investors’ perception about a company’s performance and its future. Credit rating agencies also play a vital role as they assign ratings to the IPO of company on the basis of various criteria including fundamental factors, past performance, future prospects. However, once the company is listed, its performance is affected by various factors. The volatility of company’s share varies with volatility of various macro and micro economic factors. Factors like globalization, liberalization and privatization, have made the economies dependent on each other. Political instability and fragile economic, crisis in any part of world have direct or indirect effect on the performance of economic sectors of home country. Mauner and Sanbet (1992) analyzed IPOs of 1002 companies traded on NASDAQ, NYSE. Pearson correlation coefficient has been used for analysis. Negative relationship between IPO return and offer size has been revealed in the analysis. Shah (1995) analyzed Indian IPO market from 1991-1995 with time series regression statistical technique. He found that listing delay and issue size affects the IPO performance. Alwarez and Gonzalez (2001) analyzed Spanish IPO market from 1987-1997 with sample size of 56 companies. They found that IPO size, reputation of underwriters have not significant influence on stock return of firm for short term. Chen et al (2000) investigated post issue performance of 277 A shares and 65 B- shares listed in China from 1992-1995. The results revealed that macro economic factors significantly affect the IPO short term performance. Krishnamurti (2002) analyzed 386 Indian IPO’s from July 1992- December 1994. The findings from the empirical analysis suggested that time delay between IPO offer closing date and listing date, offer price and size of firm are important factors and affect the IPO performance. Vaidyanathan (2007) investigated IPOs of 55 Indian companies from March 2004 to October 2006 and found that listing delay has positive impact on the first day performance of IPO and money spent on marketing has insignificant impact on IPO performance. Kumar (2007) analyzed short term performance of 156 Indian companies from 1999 to May 2007. He took 2 years from the listing date for the performance analysis. Regression technique has been applied for the analysis. The results of the study suggests that larger the issue price lesser is the under price of IPO.
In this research paper, IPO’s of companies, between 2007 and 2012, associated to all sectors of the Indian economy have been considered. Their six months and one year performance in terms of return has been compared to performance of Sensex for the same period. Various micro and macro economic factors have also been pointed out which were supposedly the cause of major fluctuation in the stock market on particular day.
Research Methodology
For the research, 265 companies (Sample size) have been considered which have launched their IPOs in 6 years from year 2007 to year 2012 (time period of research study). The companies for the research have been selected across all the sectors of Indian economy on the basis of their IPOs. 5 independent variables (Market return for 6 months and 1 year from date of listing, No. of times IPO is subscribed, IPO Issue Size, Time delay between IPO offer closing date and listing date, IPO offer Price) have been considered whereas 2 dependent variables (IPO return for 6 months and IPO return from 1 year from date of listing) have been considered.
For the analysis, statistical techniques like multiple regression and rate of return have been used to analyze the impact of independent variables on dependent variables.
Return – One year return of companies as well as Sensex has been calculated by following
formula
((Today’s closing price – Yesterday’s closing price) / Yesterday’s closing
price)*100
Hypothesis
H1: IPO issue size has no significant impact upon IPO performance
H2: IPO subscription has no significant impact upon IPO performance
H3: Time delay between IPO offer closing date and listing date has no significant impact upon IPO performance
H4: IPO offer price has no significant impact upon IPO performance
H5: Market return has no significant impact upon IPO performance
SHORT TERM PERFORMANCE ANALYSIS
6 Months IPO return analysis
Table 1 - Model Summary
Parameters |
Values |
F - Values |
4.305 |
R- Square |
0.077 |
Sign F Change |
0.001 |
Durbin Watson |
2.019 |
Durbin Watson test has been performed to analyze the auto correlation in residuals during regression analysis. The value of 2.019 from output of Durbin Watson test shows that there is no auto correlation among residuals of regression analysis.
Table 2 - Collinearity Test analysis
Variables |
VIF values |
Issue Size |
1.040 |
Over Subscription |
1.174 |
Time Delay |
1.010 |
Offer Price |
1.213 |
Market return |
1.010 |
VIF test has been performed to examine the collinearity among independent variables in 6 months IPO return. The existence of multi collinearity among independent variables puts a question mark on the reliability of the final results. The above statistical results shows that the values under VIF column for all the independent variables have values lower than 10 which signifies that multi collinearity does not exist and confirms the reliability of final output
Residual Normality Test
Normal P-P plot has been used to test the normal distribution of residuals.
Figure 1 – P-P plots of residual normality
The above graph shows that all the data points are coincide with the straight line that shows that residuals are normally distributed in the regression model.
Table 3 - Regression Coefficients
Variables |
Coefficients |
Issue Size |
0.001 |
Over Subscription |
-0.033 |
Time Delay |
-1.015 |
Offer Price |
-0.029 |
Market return |
1.904 |
Constant |
19.419 |
Regression Equation
IPO return for 6 months = 19.419 +0.001*size of IPO-0.033*number of times the issue subscribed-1.015*Time delay between IPO offer and Listed date-0.029*offer Price+ 1.904*market return in 6 months
Hypotheses Analysis Test
Table 4 – Hypothesis Testing
Hypotheses |
Variable |
Significant Value |
Conditional value test |
Hypothesis Accepted or Rejected |
Interpretation |
H1 |
Issue Size |
0.891 |
0.891>0.05 |
Rejected |
IPO issue size has significant impact upon IPO performance |
H2 |
Oversubscription |
0.920 |
0.920>0.05 |
Rejected |
IPO Oversubscription has significant impact upon IPO performance |
H3 |
Time Delay |
0.583 |
0.583>0.05 |
Rejected |
IPO time delay has significant impact upon IPO performance |
H4 |
Offer Price |
0.540 |
0.540>0.05 |
Rejected |
IPO Offer Price has significant impact upon IPO performance |
H5 |
Market Return |
0.000 |
0.00<0.05 |
Accepted |
Market Return has no significant impact upon IPO performance |
The impact of independent variables on the dependent variable (Whether significant or non significant) has been examined by the values under significant column. The independent variables having values higher than 0.05, have significant effect on the IPO return for six months.
All the variables except market return have significant impact upon the performance on the IPOs. But there are some other macroeconomic factors which also have significant impact upon the performance of IPO except these factors.
1 year IPO Return
Table 5 - Model Summary
Parameters |
Values |
F - Values |
2.785 |
R- Square |
0.051 |
Sign F Change |
0.018 |
Durbin Watson |
1.987 |
Auto correlation among residuals in regression analysis has been tested by performing Durbin Watson test. The value of 1.987 from output of Durbin Watson test shows that there is no auto correlation among residuals of regression analysis
Table 6 - Collinearity Test
Variables |
VIF values |
Issue Size |
1.041 |
Over Subscription |
1.238 |
Time Delay |
1.009 |
Offer Price |
1.206 |
Market return |
1.078 |
Multi collinearity among variables for One year market return has been tested by performing VIF (Variance Inflation Factor) test. The VIF values for all the independent variables are higher than 10 which shows that all the independent variables are free from threat of existence of multi collinearity. Non existence of collinearity in independent variables shows that the results of research study would be reliable and valid.
Residual Normality Test
Normal P-P plot has been used to test the normal distribution of residuals
The above graph shows that all the data points are coincide with the straight line that shows that residuals are normally distributed in the regression model.
Regression Coefficients
Variables |
Coefficients |
Issue Size |
0.002 |
Over Subscription |
0.195 |
Time Delay |
-1.042 |
Offer Price |
-0.064 |
Market return |
0.392 |
Constant |
3.969 |
Regression Equation
IPO return for 1 year = 3.969 +0.002*size of IPO+0.195*number of times the issue subscribed-1.042*Time delay between IPO offer and Listed date-0.064*offer Price+ 0.392*market return in 1 year
Hypothesis Analysis
Table 8 – Hypothesis Testing
Hypotheses |
Variable |
Significant Value |
Conditional value test |
Hypothesis Accepted or Rejected |
Interpretation |
H1 |
Issue Size |
0.579 |
0.579>0.05 |
Rejected |
IPO issue size has significant impact upon IPO performance |
H2 |
Oversubscription |
0.235 |
0.235>0.05 |
Rejected |
IPO Over Subscription has significant impact upon IPO performance |
H3 |
Time Delay |
0.241 |
0.241>0.05 |
Rejected |
IPO Time delay has significant impact upon IPO performance |
H4 |
Offer Price |
0.006 |
0.006<0.05 |
Accepted |
IPO Offer Price has no significant impact upon IPO performance |
H5 |
Market Return |
0.000 |
0.030<0.05 |
Accepted |
Market return has no significant impact upon IPO performance |
All the variables except market return and IPO offer price have significant impact upon the 1 year performance on the IPOs . Oversubscription of IPO and Issue size influenced the most on the short term performance (1 year) of IPOs. But there are some other macroeconomic factors which also have significant impact upon the performance of IPO except these factors.
Macro-economic factors
There are various macro economic factors that influence the performance of IPOs irrespective of their issue size, industry associations. Various global financial, political scenarios also have positive as well as negative impact upon the IPO performance.
On June 30th, 2010 Indian stock market gained as European banks obtained loan from their central bank and gradually the financial health of euro zone sector became better. RBI had to tighten its monetary policy, as on 25th June, 2010, Indian Government hiked the petrol price, diesel price, kerosene oil price and LPG price. Indian IT Sector stock price fell as US economy doomed further.
October 2010 was month of positive rally in the stock market as the purchase made by FII’s was of Rs 11,215 crores. Energy companies gave better results in that quarter.
On November 24th, 2010, share price of Indian construction and real estate companies fell because loan scam was disclosed. IT stocks crashed due to fragile US economy
On February 9th, 2011, FIIs sold stocks worth Rs 609 crores whereas they invested only Rs 115 crore in Indian stocks. The total outflow of foreign funds touched a significant figure of Rs 10,740 crore within starting months of year 2011. Due to increase in key policy rates by RBI in starting months of year 2011, Interest rate increased.
On 9th February 2011, 2G scam was unearthed in India which affected the sentiments of Indian investors. Due to high interest cost, property cost and decrease in demand of residential units, the share price of real estate stocks crashed.
On February14th, 2011 US stock market and other major economies of world gained as Egyptian President resigned that reduced the political unrest around the region.
Conclusion
In nutshell, we can say that short term performance of IPO influenced by no. of times IPO subscribed, time delay between offer losing date and listing date and size of IPO issue. Macroeconomic factors like Euro debt crisis, Political unrest in Egypt, US’s fragile economy, increase in commodity prices were the major global factors that dent the performance of different Indian sectors during the study period. Indian macroeconomic factors which affected the performance were food inflation, hike in oil prices, increase in policy rates by RBI, FII flow in stock market, Rupee depreciation, financial scams and sentiments of Indian investors etc.
References
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