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152

CHAPTER 7

FACTORS AFFECTING PERFORMANCE OF INITIAL PUBLIC OFFERINGS IN INDIA

The present chapter analyses various factors affecting

underpricing of IPOs using the regression technique. For this

purpose this chapter has been divided into two parts. The first part

covers determinants of short run price performance and the other

part covers the determinants of medium and long run share price

performance of Indian IPOs.

PART I DETERMINANTS OF SHORT RUN PERFORMANCE OF IPOS

Some important variables have been identified to investigate

their impact on underpricing of IPOs in India. Table 7.1 enlists those

variables along with their description. Such factors include the size

of the issue, amount of the issue, industry sector, oversubscription,

reputation of the advisers, age of company etc. One or all of these

factors may influence the underpricing of IPOs. Attempt has been

made to evaluate the importance of these factors in explaining the

observed cross sectional variations in underpricing. Some variables,

which have been examined in other studies, have been excluded from

the present study because of the non-availability of data. The well-

known variables with their labels that have been used to explain

cross sectional differences in IPO initial return are given in the Table 7.1.

Model

In order to find out the determinants of underpricing, the

following model has been employed.

R1/R2 = 0+ 1(S1)+ 2(S2)+ 3(S3)+ …. + 19(S19)+e

The above stated regression model has been computed using

SPSS version 14.0 software package. Stepwise ordinary least square

regression has been used by specifying the criteria of entry of

independent variable at 5 percent level of significance and removal of

independent variables at 10 percent level of significance. 0 is the

constant term, 1, 2………… 19 are coefficients of independent

variables while e indicates error term in the model.

Statistical Results

As customary, prior to regression results, the inter

relationships among variables have been analysed through

153

correlation matrix presented in Table 7.2. Table 7.2 reveals that

several statistically significant correlations exist among variables

affecting underpricing and underpricing (measured by R1 and R2).

Table 7.1 Description of Variables Affecting Underpricing for Regression Analysis

Labels Dependent Variables

Name Definitions

R1 Raw Return It is measured as the difference between the closing price on the first day of trading and the offer price, divided by the offer price.

R2 Market Adjusted Excess Return It is measured as the difference between raw return and market return (measured using nifty as the market index).

Independent Variables

S1 Natural log of Age The natural log of the number of calendar days from the date of incorporation to the date of listing

S2 Natural log of the Issue Size The natural log of the proceeds of the issue

S3 Listing Delay The number of calendar days from the issue date to the listing date.

S4 Reciprocal of the IPO price Reciprocal of the issue price of IPO.

S5 Reputation of Lead Manager

It is measured in terms of ranks assigned in the ascending order on the basis of issue amount lead managed during the sample period.

S6 Oversubscription No. of times an issue is subscribed

S7 IPO Year Dummy for the IPOs issued in 1994













S20 Nature of the Industry Dummy for the IPOs in Manufacturing Industries

S21 Nature of the Industry Dummy for the IPOs in Service Industries

S22 Activity based Classification of the

Industry

Dummy for the firms in the Chemical Industry


Industry

Dummy for the firms in the Communicationl

Industry


Industry

Dummy for the firms in the Financial Service

Industry


Industry

Dummy for the firms in the Food Processing

Industry


Industry

Dummy for the firms in the Machinery Industry


Industry

Dummy for the firms in the Metal and Metal

Product Industry


Industry

Dummy for the firms in the Software Industry


Industry

Dummy for the firms in the Textile Industry


Industry

Dummy for the firms in the Transport Equipment

Industry

154

R1 (underpricing measured by initial raw return) is

significantly and positively associated with S4 (reciprocal of price of

the IPO) and S6 (Oversubscription) S28 (Dummy for the firms in the

software industry). Table 7.2 also reports correlations between

dummy variables and underpricing. Significant correlations exist

between IPOs issued in particular years and underpricing. The

correlation between S14 and R1 is 0.214, indicating that average

underpricing of IPOs issued in 2001 is significantly greater from the

average underpricing of IPOs issued in all other years.

The analysis of correlations among different variables and R2

(underpricing measured in terms of market adjusted excess return)

reveals somewhat different picture. R2 is found to be significantly

and negatively associated with S2 (log of Issue Size) and significantly

and positively associated with S4 (reciprocal of price of the IPO), S6

(Oversubscription) S28 (Dummy for the firms in the software industry)

and R1 (Initial Return). As far as dummy variables are concerned,

IPOs issued in 2001 are more underpriced than the IPOs issued in

other years.

The above discussion reveals that S4 and S6 are correlated

with underpricing. The underpricing of IPOs issued in 2001 is

significantly different from average underpricing of IPOs issued in

other years. In activity based classification software industries is also

significantly associated with underpricing. Quality of lead managers,

age of company, and listing delay is not significantly associated with

underpricing.

155

Table 7.2

Pearson Correlations Matrix of Variables Affecting Underpricing

Correlations

S1 S2 S3 S4 S5

S7 S6 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30 R1 R2

S1 Age 1

S2 Issue Size 0.276* 1

S3 Listing Delay -0.099 -0.446* 1

S4 Price of IPO -0.221* -0.438* 0.242* 1

S5 Quality of lead Manager 0.124 0.360* -0.142 -0.148 1

S6 Over subscription -0.053 0.029 -0.008 -0.088 0.172 1

S7 IPO Year-1994 0.062 -0.038 0.109 -0.006 -0.038 -0.012 1

S8 IPO Year-1995 0.063 -0.048 0.169 -0.003 -0.028 -0.031 -0.030 1

S9 IPO Year-1996 -0.050 -0.054 0.230* 0.015 -0.053 0.123 0.163 -0.114 1

S10 IPO Year-1997 -0.041 0.054 -0.019 -0.027 -0.010 0.033 0.023 -0.079 -0.039 1

S11 IPO Year-1998 -0.134 -0.077 0.125 -0.003 -0.008 0.069 0.059 -0.064 -0.032 -0.022 1

S12 IPO Year-1999 -0.045 0.161 0.013 0.016 0.119 0.011 0.021 -0.119 -0.059 -0.041 -0.033 1

S13 IPO Year-2000 0.008 0.039 -0.098 -0.023 0.022 -0.002 -0.001 -0.169 -0.084 -0.059 -0.048 -0.088 1

S14 IPO Year-2001 -0.009 -0.133 -0.017 0.170 -0.123 -0.039 -0.079 -0.056 -0.028 -0.019 -0.016 -0.029 -0.041 1

S15 IPO Year-2002 0.058 -0.010 -0.051 -0.057 -0.010 -0.004 -0.006 -0.079 -0.039 -0.027 -0.022 -0.041 -0.059 -0.019 1

S16 IPO Year-2003 0.018 -0.104 -0.052 0.096 -0.203** -0.046 -0.048 -0.092 -0.046 -0.032 -0.026 -0.048 -0.068 -0.022 -0.032 1

S17 IPO Year-2004 -0.066 0.063 -0.069 0.026 -0.018 -0.054 -0.051 -0.150 -0.074 -0.052 -0.042 -0.077 -0.110 -0.036 -0.052 -0.060 1

S18 IPO Year-2005 0.023 -0.040 -0.121 -0.113 0.087 0.056 0.057 -0.230* -0.114 -0.079 -0.064 -0.119 -0.169 -0.056 -0.079 -0.092 -0.150 1

S19 IPO Year-2006 -0.035 0.031 -0.047 0.051 0.053 -0.052 -0.042 -0.195** -0.097 -0.067 -0.055 -0.101 -0.144 -0.047 -0.067 -0.078 -0.127 -0.195** 1

S20 Manufacturing Industries -0.161 -0.222* 0.010 -0.095 -0.143 0.044 0.042 0.031 -0.009 -0.006 0.019 -0.119 -0.034 0.079 0.053 0.079 0.111 0.080 -0.079 1

S21 Service Industries 0.152 0.186** -0.022 0.155 0.222* -0.053 -0.073 0.008 0.011 -0.025 -0.074 0.135 0.007 -0.064 -0.091 -0.048 -0.097 -0.100 0.139 -0.807* 1

S22 Chemical Industry 0.092 -0.083 0.072 -0.089 -0.098 -0.074 -0.054 0.040 0.058 0.003 -0.059 -0.056 -0.039 0.055 -0.072 0.113 -0.051 0.040 -0.004 0.296* -0.239* 1

S23 Communication 0.006 0.013 -0.051 -0.039 0.085 -0.038 -0.068 -0.030 -0.046 -0.032 -0.026 0.055 0.008 -0.022 -0.032 -0.037 -0.060 0.031 0.059 -0.283* 0.350* -0.084 1

S24 Financial Services 0.164 0.193** 0.044 0.249* 0.274* -0.082 -0.072 0.053 0.066 0.007 -0.057 0.161 -0.031 -0.049 -0.070 -0.081 -0.088 -0.138 0.112 -0.621* 0.770* -0.184 -0.081 1

S25 Food Processing -0.039 -0.083 0.071 0.015 0.015 -0.039 -0.049 0.111 -0.043 -0.030 -0.024 -0.044 -0.063 -0.021 0.129 -0.034 -0.056 0.046 0.000 0.122 -0.098 -0.078 -0.034 -0.076 1

S26 Machinery Industry 0.042 0.024 -0.009 -0.056 0.027 -0.045 -0.025 0.003 -0.076 -0.053 0.072 -0.014 0.081 -0.037 0.137 -0.062 0.061 -0.036 -0.043 0.218* -0.176 -0.140 -0.062 -0.135 -0.057 1

S27 Metal and Metal Products -0.161 -0.079 -0.099 0.189** -0.176 -0.104 -0.114 -0.128 -0.063 0.177 -0.036 0.010 0.132 -0.031 -0.044 0.045 -0.083 0.055 -0.007 0.181 -0.147 -0.117 -0.051 -0.113 -0.048 -0.086 1

S28 Software Industry -0.126 -0.037 -0.033 -0.175 0.002 0.012 0.262* 0.106 0.066 -0.087 -0.071 0.008 -0.118 -0.061 -0.020 0.015 0.062 0.024 0.032 0.358* -0.289* -0.230* -0.101 -0.223* -0.095 -0.169 -0.141 1

S29 Textile Industry -0.120 -0.093 0.053 0.064 -0.034 0.023 0.033 -0.109 -0.054 -0.038 0.281* -0.056 -0.015 0.153 -0.038 0.068 0.146 -0.003 -0.092 0.154 -0.124 -0.099 -0.044 -0.096 -0.041 -0.073 -0.061 -0.120 1

S30 Transport Equipment 0.025 -0.029 -0.027 0.029 -0.039 -0.034 -0.094 -0.072 -0.036 -0.025 -0.020 -0.037 -0.053 -0.018 0.162 -0.029 0.059 0.160 -0.061 0.102 -0.083 -0.066 -0.029 -0.064 -0.027 -0.048 -0.040 -0.080 -0.034 1

R1 Initial Raw Return -0.131 -0.176 0.092 0.210** -0.071 0.002 0.482* -0.039 0.075 -0.057 0.059 0.003 -0.026 0.214* 0.039 -0.051 -0.017 -0.022 0.026 0.037 -0.031 -0.118 -0.059 -0.006 -0.036 -0.084 -0.013 0.214* 0.022 -0.040 1

R2 Initial Market Adjusted Return

-0.137 -0.189** 0.090 0.209** -0.063 0.007 0.487* -0.032 0.069 -0.060 0.066 0.003 -0.026 0.221* 0.039 -0.060 -0.011 -0.020 0.015 0.036 -0.024 -0.120 -0.056 0.001 -0.031 -0.078 -0.025 0.212* 0.021 -0.039

0.99

6* 1

**Correlation is significant at the 0.01 level (2-tailed).

*Correlation is significant at the 0.05 level (2-tailed).

15

5

156

Following the correlation matrices, Table 7.3 examines the individual

contribution of each variable with underpricing measured in terms of R1 and

R2 as dependent variable. All the Six independent determinants have been

entered individually and regression coefficients and contribution of each

variable has been reported in the Table 7.1.

Table 7.3

Individual Relationships of Determinants of Underpricing with Underpricing

Determinants Underpricing (R1) Underpricing (R2)

Standardised

t R2 Adjusted R2

F Change

Standardised

t R2 Adjusted R2

F Change

S1 -.131 -1.980 .017 .013 3.919 -.137 -2.071 .019 .014 4.290

S2 -.176*** -2.672 0.31 .027 7.142*** -.189** -2.874 .036 .031 8.262**

S3 .092 1.384 .009 .004 1.916 .090 1.346 .008 .004 1.812

S4 .210** 3.213 .044 .040 10.326** .209** 3.189 .044 .039 10.169*

*

S5 -0.71 -1.070 .005 .001 1.145 -.063 -.937 .004 -.001 .878

S6 .482* 8.223 .233 .229 67.619* .487* 8.331 .237 .234 69.400*

* Significantly different from zero at 1 percent level

A perusal of the Table 7.3 reveals that S2, S4 and S6 are significant

determinants of underpricing measured in terms of initial raw return. When

market adjusted excess return (R2) is considered as dependant variable, S2, S4

and S6 are found to be significant determinants of underpricing. It implies

that issue size, IPO price and oversubscription are significant determinants of

underpricing. Further, quality of lead managers, nature of Industry, age of

company, listing delay are not found to be statistically significant

determinants of underpricing.

After examining the individual contribution of determinants, Stepwise

Regression analysis has been performed to find out the major determinants of

underpricing. Table 7.4 and Table 7.5 contain the results of stepwise

regression analysis, which seeks to decompose variations in underpricing in

terms of issue and firm specific characteristics. These two tables summarise

the results using initial raw return and market adjusted return as dependent

variables. Both set of regressions find same five significant determinants of

underpricing. These five determinants viz. S6, S4, S14, S28 and S5 together

157

explains 35.6 percent of variation in initial raw return and four determinants

viz. S6, S14, S4 and S28 explains 35.6 percent of variation in market adjusted

excess return.

Table 7.4

Determinants of Underpricing: A Step-wise Regression Analysis

(Dependent Variable: Initial Raw Return -R1) Variables Entered R2 Adjusted

R2

R2

Change F

Change F Partial

Correlations

t Value

S6 .233 .229 .233 67.619 67.619

S6, S4 .297 .291 .064 20.345 46.915

S6, S4, S14 .343 .334 .046 15.341 38.411

S6, S4, S14, S28 .361 .350 .018 6.353 31.094

S6, S4 , S14, S28, S5 .370 .356 .009 3.151 25.749

Variables Excluded

S1 -.031 -.458

S2 -.033 -.493

S3 .046 .686

S7 .048 .662

S8 -.037 -.547

S9 -.023 -.347

S10 -.061 -.897

S11 .053 .788

S12 .007 .105

S13 .009 .132

S15 .077 1.137

S16 -.085 -1.264

S17 -.001 -.008

S18 -.010 -.142

S19 .059 .877

S20 -.057 -.849

S21 .061 .906

S22 -.079 -1.175

S23 .014 .205

S24 .058 .853

S25 .005 .072

S26 -.032 -.477

S27 .012 .181

S29 -.036 -.539

S30 .014 .210

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Table 7.5

Determinants of Underpricing: A Step-wise Regression Analysis

(Dependent Variable: Market Adjusted Excess Return-R2)

Variables Entered R2 Adjusted R2

R2

Change F

Change F Partial

Correlations t

Value

S6 .237 .234 .237 69.400 69.400

S6, S14 .305 .299 .068 21.569 48.685

S6, S14, S4 .350 .341 .045 15.406 39.698

S6, S14, S4 S28 .368 .356 .018 6.125 31.995

Variables Excluded

S1 -0.77 -0.05

S2 -1.33 -0.09

S3 0.86 0.06

S5 -1.62 -0.11

S7 0.56 0.45

S8 -0.36 -0.02

S9 -0.32 -0.02

S10 -0.90 -0.06

S11 0.97 0.07

S12 -0.10 -0.01

S13 0.12 0.01

S15 1.18 0.08

S16 -1.06 -0.07

S17 0.14 0.01

S18 -0.23 -0.02

S19 0.56 0.04

S20 -0.60 -0.04

S21 0.58 0.04

S22 -1.02 -0.07

S23 0.11 0.01

S24 0.37 0.03

S25 0.15 0.01

S26 -0.38 -0.03

S27 0.24 0.02

S29 -0.54 -0.04

S30 0.29 0.02

The regression results can be stated in the following two equations.

R1 = -28.777 +2.453 (S6) +730.109 (S4)+201.231(S14)+36.004 (S28) – 21.565 (S5)

R2 = -41.000 + 2.370(S6) +214.623 (S14) +752.083 (S4) + 36.533 (S28)

The above two equations can be interpreted as follows:

1. Larger the oversubscription, larger the underpricing.

159

2. Higher the issue price, higher the extent of underpricing.

3. The IPOs issued in 2001 are more underpriced than the IPOs in other

years.

4. The IPOs in the software industry are more underpriced than other

industries.

5. The reputation of lead manager is negatively related to the IPO initial

return, more reputed lead managers resort to less underpricing.

Both the models present a clear idea about the determinants selected

for analysis. But the explanatory power of these models is observed to be low.

An investment in IPOs depends on many quantitative and qualitative factors

such as EPS, gestation period of the project, post issue equity holding

patterns, foreign technical/ financial collaboration, underwriter’s reputation

etc.

Using correlation matrix, and univariate and multivariate regressions,

the chapter finds that a number of factors including oversubscription, inverse

of IPO price, year dummy for 2001, activity based industry dummy for

software and reputation of lead manager have significant impact on under

pricing. While the first four are positively related, the last variable is

negatively related with under pricing. Also, the last variable is significant in

case of MAER only.

Therefore, we may conclude in light of results obtained above that the

issues which are oversubscribed often tend to emerge as highly underpriced.

It could be possible that somehow; the markets work out the extent of

underpricing and therefore subscription of issues with greater underpricing

increases. Also, the results indicate that issues with lower price seem to

involve greater underpricing. Issues in software industry are also more

underpriced, perhaps because of the fact that it is a relatively new industry

and issuing companies could underprice their issue to generate greater

interest in their issues. Finally, issues in 2001 are more underpriced. On the

other hand, reputed and experienced lead managers seem to be more fairly

pricing the IPOs.

160

PART II DETERMINANTS OF MEDIUM AND LONG-RUN SHARE

PRICE PERFORMANCE OF IPOS

In order to assess the determinants of medium and long run

performance of Indian IPOs, multivariate regression analysis has been

undertaken. Based on the prior research, the variables have been identified

and examined to explain the variations in the share price performance of

IPOs.

Description of Variables:

The issue of performance of IPOs in the medium and long run has

generated mixed results. In India, mixed results have been reported and not

much emphasis has been made to identify the factors that may explain the

performance of IPOs in the post issue period. To investigate the possible

determinants of medium and long run performance of IPOs in India, various

variables have been identified and tested. To investigate the possible

determining factors of long run-performance of IPOs, correlations of variables

have been described in Table 7.6.

Table 7.6 Description of Variables Affecting Medium and Long run Performance for Regression

Analysis

Label Dependent Variables

Name Definitions

R1 One Year Raw Return from offer

date

It is one year raw return measured from the issue price

to the closing price at the end of one yr.

R2 Two Years Raw Returns from

offer date

It is two years raw return measured from the issue price

to the closing price at the end of two yrs.

R3 Three Years Raw Returns from

offer date

It is three yrs raw return measured from the issue price

to the closing price at the end of three yrs.

L1 One Year Raw Return from listing date

It is one year raw return measured from the first day after market closing price to the closing price

at the end of one yr

L2 Two Years Raw Returns from

listing date

It is two years raw return measured from the first day

after market closing price to the closing

price at the end of one yr

L3 Three Years Raw Returns from

listing date

It is three years raw return measured from the first day

after market closing price to the closing

Price at the end of three yrs

Independent Variables

S1 Natural log of Age The natural log of the number of calendar days from the

date of incorporation to the date of listing

S2 Natural log of the Issue Size The natural log of the proceeds of the issue

S3 Listing Delay The number of calendar days from the issue date to the

161

listing date.

S4 Reciprocal of the IPO price Reciprocal of the issue price of IPO.

S5 Reputation of Lead Manager

It is measured in terms of ranks assigned in the

ascending order on the basis of issue amount

Lead managed during the sample period.

S6 Oversubscription No. of times an issue is subscribed














S20 Nature of the Industry Dummy for the IPOs in Manufacturing Industries

S21 Nature of the Industry Dummy for the IPOs in Service Industries

S22 Activity based Classification of

the Industry

Dummy for the firms in the Chemical Industry


the Industry

Dummy for the firms in the Communicationl Industry


the Industry

Dummy for the firms in the Financial Service Industry

S25 Activity based Classification of the Industry

Dummy for the firms in the Food Processing Industry


the Industry

Dummy for the firms in the Machinery Industry


the Industry

Dummy for the firms in the Metal and Metal Product

Industry


the Industry

Dummy for the firms in the Software Industry


the Industry

Dummy for the firms in the Textile Industry


the Industry

Dummy for the firms in the Transport Equipment

Industry

Correlation Analysis

A correlation matrix is shown in Table 7.7(A), 7.7(B) 7.7(C) for all

variables which includes correlation coefficients and their associated levels of

significance. The correlation matrix reveals the direction and extent of

significant bivariate associations between various independent and dependent

variables.

From the table 7.7(A) it is clear that the IPOs in the year 1999 and that

belonging to the financial services industry have got significantly higher

162

return compared to other years and industries. Similarly, correlation analysis

between the two year long run performance and various independent

variables given in table 7.7(B) reveals that age of a company is positively and

significantly correlated with performance, irrespective of the fact that initial

returns are included or not. Issue size on the other hand, is positively and

significantly correlated with raw return measured from date of offer, but its

correlation with performance after excluding the initial return is not

statistically significant.

Further, looking at the broader classification of industries, it has been

found that the dummy for manufacturing industry is negatively related with

the long run performance of IPOs while that for services industries is

positively correlated with the performance, indicating that IPOs in the services

industry record stronger performance at the end of two years. Finally, looking

at nature of industry, the dummy for financial services industries is found to

be positively and significantly correlated with the long run performance,

irrespective of the fact that whether the initial return is included or not.

Correlation analysis for the three year long run performance is given in

table 7.2(C) which reveals that age of the company and issue size is positively

correlated with the performance. Price of the IPO is also positively and

significantly correlated with the long run performance after three years. In

none of the year dummy is significantly correlated with three year

performance but those for manufacturing and services industries under the

broader classification and for financial services under classification of IPOs

according to the nature of industry are positive and significant.

Overall, it can be concluded that factors including age of a company,

issue size, price of the IPO and nature of the industry and year of issue are

found to be significantly correlated with at least one of the measures of long

run performance at the end of various time periods considered in this study.

163

Table 7.7(A)

Pearson Correlations Matrix of Variables Affecting Performance upto One Year

R1 L1 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30

R1 Initial Raw Return

1.00

L1 Initial Market Adjusted Return

0.97** 1.00

S1 Age

-0.02 -0.04 1.00

S2 Issue Size

0.07 0.05 0.32** 1.00

S3 Listing Delay

-0.13 -0.12 -0.10 -0.42** 1.00

S4 Reciprocal of the IPO price Price of IPO 0.12 0.12 -0.21** -0.39** 0.20* 1.00

S5 Quality of lead Manager

-0.01 -0.01 0.16* 0.39** -0.18* -0.14 1.00

S6 Over subscription

0.11 0.12 -0.12 -0.03 0.05 -0.06 0.25** 1.00

S7 IPO Year-1994

0.00 -0.01 0.18* 0.06 -0.01 -0.02 0.03 -0.08 1.00

S8 IPO Year-1995

0.07 0.08 0.07 0.03 0.13** -0.05 -0.06 0.02 -0.13 1.00

S9 IPO Year-1996

0.01 0.03 -0.09 -0.07 0.31 0.06 -0.08 0.05 -0.05 -0.13 1.00

S10 IPO Year-1997

-0.07 -0.06 0.01 0.00 0.00 -0.08 0.10 0.13 -0.03 -0.06 -0.03 1.00

S11 IPO Year-1998

-0.05 -0.06 -0.14 -0.06 0.11 -0.03 -0.02 0.10 -0.04 -0.09 -0.04 -0.02 1.00

S12 IPO Year-1999

0.15 0.17* -0.03 0.16 0.03 0.04 0.06 0.02 -0.06 -0.14 -0.06 -0.03 -0.04 1.00

S13 IPO Year-2000

-0.01 -0.02 -0.05 -0.05 -0.08 0.03 -0.03 0.02 -0.07 -0.18 -0.07 -0.04 -0.05 -0.08 1.00

S14 IPO Year-2001

0.04 0.03 -0.01 -0.13 -0.04 0.17 -0.16 -0.09 -0.03 -0.08 -0.03 -0.02 -0.02 -0.03 -0.04 1.00

S15 IPO Year-2002

-0.04 -0.03 0.07 0.02 -0.09 -0.09 -0.02 0.02 -0.05 -0.11 -0.05 -0.02 -0.03 -0.05 -0.06 -0.03 1.00

S16 IPO Year-2003

-0.06 -0.12 -0.01 -0.10 -0.07 0.06 -0.22 -0.05 -0.05 -0.11 -0.05 -0.02 -0.03 -0.05 -0.06 -0.03 -0.04 1.00

S17 IPO Year-2004

-0.06 -0.03 -0.10 0.12 -0.08 0.00 0.06 -0.05 -0.07 -0.18 -0.07 -0.04 -0.05 -0.08 -0.10 -0.04 -0.06 1.00

S18 IPO Year-2005

0.02 0.02 0.07 -0.09 -0.13 -0.09 0.13 0.01 -0.10 -0.24 -0.10 -0.05 -0.07 -0.10 -0.13 -0.06 -0.08 -0.08 -0.13 1.00

S19 IPO Year-2006

-0.09 -0.09 -0.03 0.01 -0.05 0.07 0.09 -0.03 -0.09 -0.22 -0.09 -0.04 -0.06 -0.10 -0.12 -0.05 -0.08 -0.08 -0.12 -0.17 1.00

S20 Manufacturing Industries

-0.10 -0.07 -0.20* -0.20 -0.01 -0.19 -0.16 0.09 -0.17 0.00 0.02 -0.05 0.02 -0.08 -0.04 0.09 0.06 0.06 0.10 0.12 -0.12 1.00

S21 Service Industries

0.12 0.12 0.19* 0.19 -0.03 0.23 0.23 -0.08 0.14 0.00 0.01 0.07 -0.09 0.12 -0.02 -0.08 -0.11 -0.03 -0.07 -0.11 0.13 -0.86 1.00

S22 Chemical Industry

0.03 0.01 0.11 0.00 0.05 -0.15 -0.12 -0.05 -0.04 0.03 0.11 0.09 -0.08 -0.05 -0.04 0.05 -0.10 0.07 -0.10 0.06 0.00 0.31 -0.27 1.00

S23 Communication

-0.08 -0.07 0.00 -0.04 -0.05 0.00 0.02 -0.07 0.12 -0.02 -0.04 -0.02 -0.03 -0.04 -0.06 -0.03 -0.04 -0.04 -0.06 0.02 0.14 -0.28 0.33 -0.09 1.00

S24 Financial Services

0.17 0.17* 0.24** 0.28 0.01 0.25 0.32 -0.04 0.12 0.05 0.04 0.10 -0.08 0.17 -0.03 -0.07 -0.09 -0.09 -0.09 -0.11 0.06 -0.72 0.84 -0.23 -0.08 1.00

S25 Food Processing

0.00 0.00 -0.06 -0.13 0.09 0.05 0.02 -0.03 -0.04 0.15 -0.04 -0.02 -0.03 -0.04 -0.06 -0.03 0.15 -0.04 -0.06 0.02 -0.07 0.12 -0.10 -0.09 -0.03 -0.08 1.00

S26 Machinery Industry

-0.06 -0.04 0.04 0.04 -0.02 -0.07 0.05 -0.02 0.02 -0.04 -0.08 -0.04 0.08 -0.08 0.04 -0.05 0.15 -0.07 0.12 0.03 -0.07 0.22 -0.19 -0.16 -0.06 -0.16 -0.06 1.00

S27 Metal and Metal Products

0.08 0.06 -0.17* -0.13 -0.07 0.18 -0.09 -0.04 -0.05 -0.11 -0.05 -0.02 -0.03 0.09 0.29 -0.03 -0.04 -0.04 -0.06 0.10 -0.08 0.13 -0.11 -0.10 -0.04 -0.09 -0.04 -0.07 1.00

S28 Software Industry

-0.10 -0.06 -0.17* -0.01 -0.08 -0.22 -0.03 0.24 -0.13 0.08 0.01 -0.06 -0.09 0.06 -0.12 -0.08 -0.03 0.05 0.10 -0.02 0.05 0.35 -0.30 -0.27 -0.10 -0.25 -0.10 -0.18 -0.11 1.00

S29 Textile Industry -0.06 -0.08 -0.12 -0.16 0.12 0.14 -0.09 0.04 0.10 -0.11 -0.05 -0.02 0.39 -0.05 -0.06 0.21 -0.04 0.13 0.05 -0.08 -0.08 0.13 -0.11 -0.10 -0.04 -0.09 -0.04 -0.07 -0.04 -0.11 1.00

S30 Transport Equipment 0.05 0.05 0.03 0.00 -0.06 0.01 -0.06 -0.10 -0.04 -0.10 -0.04 -0.02 -0.03 -0.04 -0.06 -0.03 0.15 -0.04 0.07 0.23 -0.07 0.12 -0.10 -0.09 -0.03 -0.08 -0.03 -0.06 -0.04 -0.10 -0.04 1.00

**Correlation is significant at the 0.01 level (2-tailed). *Correlation is significant at the 0.05 level (2-tailed).

163

164

TABLE 7.7(B)

Pearson Correlations Matrix of Variables Affecting Performance upto Two years

R2 L2 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30


1.000

L2 MAER

0.977 1.000

S1 Age 0.273** 0.241*** 1.000

S2 Issue Size 0.249** 0.218 0.995 1.000

S3 Listing Delay

-0.177 -0.149 -0.086 -0.110 1.000

S4 Reciprocal of the IPO price 0.458 0.372 0.160 0.176 -0.612 1.000

S5 Quality of lead Mgr

0.085 0.072 0.159 0.155 -0.197 0.201 1.000


-0.012 0.020 -0.192 -0.197 0.113 0.005 0.175 1.000

S7 IPO Year-1994

0.103 0.123 0.222 0.212 0.031 -0.026 0.036 -0.062 1.000

S8 IPO Year-1995

0.004 -0.029 0.014 -0.002 0.130 -0.001 -0.029 0.002 -0.130 1.000

S9 IPO Year-1996

-0.074 -0.076 -0.072 -0.073 0.229 -0.012 -0.078 0.072 -0.054 -0.142 1.000

S10 IPO Year-1997

-0.059 -0.045 0.006 0.013 0.000 -0.015 0.106 0.140 -0.028 -0.074 -0.031 1.000

S11 IPO Year-1998

-0.053 -0.068 -0.091 -0.106 0.166 -0.138 -0.081 0.044 -0.035 -0.091 -0.038 -0.020 1.000

S12 IPO Year-1999

0.022 0.043 -0.020 -0.026 0.065 -0.012 0.063 -0.004 -0.054 -0.142 -0.059 -0.031 -0.038 1.000

S13 IPO Year-2000

-0.015 -0.028 -0.060 -0.044 -0.070 -0.034 -0.052 -0.005 -0.066 -0.171 -0.071 -0.037 -0.046 -0.071 1.000

S14 IPO Year-2001

-0.041 -0.032 -0.094 -0.092 -0.014 -0.051 -0.107 -0.060 -0.020 -0.052 -0.022 -0.011 -0.014 -0.022 -0.026 1.000

S15 IPO Year-2002

-0.037 -0.041 0.065 0.077 -0.106 0.145 -0.040 0.016 -0.050 -0.130 -0.054 -0.028 -0.035 -0.054 -0.066 -0.020 1.000

S16 IPO Year-2003

-0.072 -0.074 -0.031 -0.032 -0.044 -0.042 -0.186 -0.057 -0.035 -0.091 -0.038 -0.020 -0.024 -0.038 -0.046 -0.014 -0.035 1.000

S17 IPO Year-2004

-0.063 -0.050 -0.160 -0.153 -0.091 -0.052 0.019 -0.059 -0.076 -0.198 -0.082 -0.043 -0.053 -0.082 -0.100 -0.030 -0.076 -0.053 1.000

S18 IPO Year-2005

0.137 0.153 0.079 0.089 -0.130 -0.051 0.055 0.026 -0.097 -0.253** -0.105 -0.055 -0.068 -0.105 -0.128 -0.039 -0.097 -0.068 -0.147 1.000

S19 IPO Year-2006

-0.002 -0.002 0.047 0.046 -0.093 0.174 0.126 -0.022 -0.085 -0.223 -0.093 -0.048 -0.060 -0.093 -0.112 -0.034 -0.085 -0.060 -0.129 -0.166 1.000

S20 Manuf Inds

-0.266** -0.261** -0.310* -0.272** 0.047 0.009 -0.209 0.066 -0.106 -0.075 0.077 -0.060 -0.016 -0.077 -0.074 0.057 0.059 0.099 0.099 0.130 -0.075 1.000

S21 Service Industries 0.283* 0.280** 0.300* 0.256** -0.091 0.043 0.292* -0.060 0.132 0.048 -0.058 0.075 -0.089 0.103 0.037 -0.051 -0.128 -0.089 -0.073 -0.097 0.114 -0.903 1.000


-0.025 -0.046 0.066 0.078 0.087 0.042 -0.108 -0.007 -0.018 0.030 0.140 0.096 -0.078 -0.034 -0.072 -0.045 -0.111 0.053 -0.103 0.111 -0.010 0.315* -0.284* 1.000

S23 Communication

-0.001 0.002 0.031 0.039 -0.060 0.145 0.060 -0.052 0.172 -0.002 -0.044 -0.023 -0.028 -0.044 -0.053 -0.016 -0.040 -0.028 -0.061 0.045 0.067 -0.286* 0.317* -0.090 1.000

S24 Financial Services 0.316* 0.309* 0.308* 0.255** -0.065 0.006 0.336* -0.030 0.076 0.075 -0.034 0.096 -0.078 0.140 0.001 -0.045 -0.111 -0.078 -0.103 -0.107 0.109 -0.787 0.871 -0.248** -0.090 1.000

S25 Food Processing

-0.081 -0.073 -0.087 -0.097 0.134 -0.146 0.060 -0.047 -0.040 0.102 -0.044 -0.023 -0.028 -0.044 -0.053 -0.016 0.172 -0.028 -0.061 0.045 -0.069 0.115 -0.103 -0.090 -0.033 -0.090 1.000


-0.095 -0.083 -0.049 -0.042 -0.068 -0.007 0.008 -0.026 0.072 -0.171 -0.071 -0.037 0.147 -0.071 0.022 -0.026 0.210 -0.046 0.093 0.033 -0.024 0.186 -0.168 -0.146 -0.053 -0.146 -0.053 1.000

S27 Metal and Metal Products 0.023 0.008 -0.036 -0.028 -0.046 -0.042 -0.081 -0.084 -0.035 -0.091 -0.038 -0.020 -0.024 -0.038 0.339* -0.014 -0.035 -0.024 -0.053 0.075 -0.060 0.099 -0.089 -0.078 -0.028 -0.078 -0.028 -0.046 1.000


-0.160 -0.132 -0.244*** -0.223 -0.081 0.105 -0.087 0.231*** -0.133 0.067 0.013 -0.076 -0.093 0.092 -0.108 -0.053 -0.048 0.144 0.095 -0.061 0.044 0.377 -0.340 -0.296* -0.108 -0.296* -0.108 -0.175

-0.093 1.000

S29 Textile Industry

-0.064 -0.061 -0.087 -0.081 0.208 -0.187 -0.124 -0.048 0.172 -0.106 -0.044 -0.023 0.269 -0.044 -0.053 0.494 -0.040 -0.028 0.087 -0.079 -0.069 0.115 -0.103 -0.090 -0.033 -0.090 -0.033 -0.053 -0.028

-0.108 1.000

S30 Transport Equipment 0.159 0.126 0.024 0.019 -0.073 0.070 -0.077 -0.114 -0.045 -0.119 -0.049 -0.026 -0.032 -0.049 -0.060 -0.018 0.145 -0.032 0.065 0.245*** -0.078 0.129 -0.116 -0.101 -0.037 -0.101 -0.037 -0.060

-0.032

-0.121 -0.037 1.000

*Correlation is significant at the 0.01 level (2-tailed). **Correlation is significant at the 0.05 level (2-tailed).

165

TABLE 7.7(C)

Pearson Correlations Matrix of Variables Affecting Long run Performance upto Three Years

R3 L3 S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30


1.00

L3 Initial Market Adjusted Return

0.99* 1.00

S1 Age

0.27* 0.23** 1.00

S2 Issue Size 0.22** 0.18 0.33* 1.00

S3 Listing Delay

-0.16 -0.16 -0.15 -0.44* 1.00

S4 Reciprocal of the IPO price

0.29* 0.29* -0.11 -0.25* 0.18 1.00

S5 Quality of lead Manager

0.09 0.09 0.20** 0.24** -0.17 0.05 1.00


-0.02 0.03 -0.23** -0.19 0.14 0.03 0.14 1.00

S7 IPO Year-1994

0.13 0.13 0.25* 0.04 0.03 0.07 0.02 -0.06 1.00

S8 IPO Year-1995

0.06 0.04 -0.04 0.04 0.14 0.00 -0.01 -0.03 -0.14 1.00

S9 IPO Year-1996

-0.10 -0.09 -0.06 -0.03 0.30* 0.03 -0.07 0.11 -0.06 -0.14 1.00

S10 IPO Year-1997

-0.06 -0.05 0.01 0.00 -0.01 -0.08 0.11 0.16 -0.04 -0.08 -0.04 1.00

S11 IPO Year-1998

-0.05 -0.05 -0.10 -0.15 0.18 0.03 -0.11 0.05 -0.04 -0.10 -0.04 -0.03 1.00

S12 IPO Year-1999

0.08 0.08 -0.07 0.33* -0.10 0.01 0.11 0.03 -0.06 -0.14 -0.06 -0.04 -0.04 1.00

S13 IPO Year-2000

-0.05 -0.05 0.03 -0.10 -0.03 -0.02 -0.01 0.06 -0.06 -0.13 -0.06 -0.03 -0.04 -0.06 1.00

S15 IPO Year-2002

-0.08 -0.08 0.05 -0.07 -0.11 -0.07 -0.11 0.04 -0.06 -0.13 -0.06 -0.03 -0.04 -0.06 -0.05 1.00

S16 IPO Year-2003

-0.07 -0.08 -0.03 -0.05 -0.06 0.02 -0.23** -0.06 -0.04 -0.10 -0.04 -0.03 -0.03 -0.04 -0.04 -0.04 1.00

S17 IPO Year-2004

-0.10 -0.09 -0.20** -0.03 -0.09 0.05 -0.06 -0.05 -0.09 -0.20** -0.09 -0.05 -0.06 -0.09 -0.08 -0.08 -0.06 1.00

S18 IPO Year-2005

0.08 0.10 0.13 -0.14 -0.13 -0.07 0.11 -0.04 -0.11 -0.25* -0.11 -0.06 -0.08 -0.11 -0.10 -0.10 -0.08 -0.15 1.00

S19 IPO Year-2006

0.03 0.01 0.03 0.10 -0.08 0.02 0.11 -0.04 -0.10 -0.22** -0.10 -0.06 -0.07 -0.10 -0.09 -0.09 -0.07 -0.14 -0.17 1.00

S20 Manufacturing Industries

-0.35* -0.33* -0.33* -0.31* 0.10 -0.28* -0.24* 0.07 -0.10 -0.08 0.08 -0.06 -0.01 -0.10 -0.04 0.05 0.12 0.10 0.12 -0.06 1.00

S21 Service Industries 0.38* 0.36* 0.32* 0.32* -0.10 0.29* 0.33* -0.02 0.13 0.08 -0.06 0.07 -0.11 0.13 -0.04 -0.14 -0.11 -0.07 -0.08 0.10 -0.91* 1.00


-0.05 -0.04 0.05 0.01 0.07 -0.19 -0.15 -0.08 0.00 0.00 0.22** 0.13 -0.08 -0.11 -0.10 -0.10 0.08 -0.16 0.17 -0.02 0.30* -0.28* 1.00

S23 Communication

0.03 0.02 0.03 0.02 -0.08 -0.07 0.05 -0.05 0.16 0.00 -0.05 -0.03 -0.04 -0.05 -0.05 -0.05 -0.04 -0.07 0.05 0.07 -0.30* 0.34* -0.09 1.00

S24 Financial Services 0.40* 0.38* 0.31* 0.34* -0.06 0.36* 0.36* 0.00 0.07 0.10 -0.03 0.10 -0.09 0.17 -0.01 -0.12 -0.09 -0.11 -0.10 0.08 -0.79* 0.87* -0.24* -0.11 1.00

S25 Food Processing

-0.06 -0.06 0.06 -0.19 0.24* 0.20** 0.11 -0.04 -0.04 0.09 -0.04 -0.02 -0.03 -0.04 -0.03 0.29* -0.03 -0.05 -0.06 -0.06 0.10 -0.09 -0.06 -0.03 -0.08 1.00


-0.13 -0.13 -0.01 -0.05 -0.08 -0.15 -0.02 -0.08 0.06 -0.19 -0.08 -0.05 0.14 -0.08 0.08 0.23* -0.06 0.10 0.04 -0.03 0.22** -0.20** -0.15 -0.07 -0.18 -0.05 1.00

S27 Metal and Metal Products

-0.04 -0.05 -0.02 -0.01 -0.03 -0.07 0.08 -0.05 -0.03 -0.06 -0.03 -0.01 -0.02 -0.03 -0.02 -0.02 -0.02 -0.04 0.23 -0.04 0.07 -0.06 -0.05 -0.02 -0.05 -0.01 -0.03 1.00


-0.12 -0.10 -0.29* -0.09 -0.06 -0.22** -0.17 0.27* -0.16 0.07 -0.06 -0.09 -0.11 0.12 -0.04 -0.04 0.15 0.07 -0.03 0.02 0.42* -0.38* -0.28* -0.13 -0.33* -0.09 -0.21** -0.06 1.00

S29 Textile Industry

-0.05 -0.05 -0.05 -0.24** 0.28* 0.20 -0.11 -0.02 0.20** -0.10 -0.04 -0.03 0.31* -0.04 -0.04 -0.04 -0.03 0.13 -0.08 -0.07 0.12 -0.11 -0.08 -0.04 -0.09 -0.03 -0.06 -0.02 -0.11 1.00

S30 Transport Equipment

-0.06 -0.06 -0.11 -0.05 -0.03 0.09 -0.04 -0.09 -0.04 -0.08 -0.04 -0.02 -0.03 -0.04 -0.03 -0.03 -0.03 0.18 0.13 -0.06 0.10 -0.09 -0.06 -0.03 -0.08 -0.02 -0.05 -0.01 -0.09 -0.03 1.00

*Correlation is significant at the 0.01 level (2-tailed). **Correlation is significant at the 0.05 level (2-tailed).

165

166

Table 7.8 Individual Relationships of Determinants of Medium and Long run performance with the Medium and Long run Performance

* Significantly different from zero at 1 Percent level ** Significantly different from zero at 5 Percent level

Dete

rmin

an

ts

R1 R2 R3 L1 L2 L3

Sta

nd

ar

dis

ed

β

R2

Ad

juste

d

R2

F

Cha

ng

e

Sta

nd

ar

dis

ed

β

R2

Ad

juste

d

R2

F

Cha

ng

e

Sta

nd

ar

dis

ed

β

R2

Ad

juste

d

R2

F

Cha

ng

e

Sta

nd

ar

dis

ed

β

R2

Ad

juste

d

R2

F

Cha

ng

e

Sta

nd

ar

dis

ed

β

R2

Ad

juste

d

R2

F

Cha

ng

e

Sta

nd

ar

dis

ed

β

R2

Ad

juste

d

R2

F

Cha

ng

e

S1 -.016 .000 -.006 .038 .273** .075 .067 9.984 .274*** .075 .066 7.963 -.041 .002 -.005 .261 .241*** .058 .050 7.628 .234 .055 .045 5.652

S2 .069 .005 -.002 .745 .249** .062 .054 8.198 .216 .047 .037 4.797 .050 .002 -.004 .387 .218 .047 .040 6.157 .185 .034 .024 3.457

S3 -.134 .018 .012 2.820 -.177 .031 .023 3.988 -.155 .024 .014 2.422 -.118 .014 .008 2.194 -.149 .022 .014 2.828 -.164 .027 .017 2.700

S4 .119 .014 .008 2.229 .458* .210 .203 32.890 .288** .083 .073 8.842 .117 .014 .007 2.141 .372* .138 .131 19.871 .295 .087 .077 9.314

S5 -.009 .000 -.006 .014 .085 .007 -.001 .909 .087 .008 -.003 .743 -.005 .000 -.006 .004 .072 .005 -.003 .650 .088 .008 -.002 .767

S6 .105 .011 .005 1.740 -.012 .000 -.008 .017 -.023 .001 -.010 .054 .118 .014 ..008 2.207 .020 .000 -.008 .050 .029 .001 -.009 .084

S7 .003 .000 -.006 .002 .103 .011 .003 1.319 .134 .018 .008 1.787 -.013 .000 -.006 .027 .123 .015 .007 1.909 .128 .016 .006 1.633

S8 .067 -.005 -.002 .701 .004 .000 -.008 .002 .056 .003 -.007 .311 .081 .006 .000 1.013 -.029 .001 -.007 .103 .039 .002 -.009 .151

S9 .009 .000 -.006 .014 -.074 .005 -.003 .682 -.097 .009 -.001 .937 .028 .001 -.006 .118 -.076 .006 -.002 .715 -.094 .009 -.001 .874

S10 -.066 .004 -.002 .670 -.059 .003 -.005 .433 -.057 .003 -.007 .316 -.057 .003 -.003 .507 -.045 .002 -.006 .253 -.048 .002 .008 .226

S11 -.047 .002 -.004 .336 -.053 .003 -.005 .347 -.055 .003 -.007 .297 -.057 .003 -.003 .503 -.068 .005 -.003 .575 -.051 .003 -.008 .253

S12 .152 .023 .017 3.648 .022 .000 -.008 .062 .078 .006 .004 .597 .169 .028 .022 4.532 .043 .002 -.006 .232 .083 .007 -.003 .682

S13 -.009 .000 -.006 .011 -.015 .000 -.008 .027 -.051 .003 -.008 .258 -.018 .000 -.006 .048 -.028 .001 -.007 .097 -.047 .002 -.008 .217

S14 .042 .002 -.005 .270 -.041 .002 -.006 .206 - - - - .028 .001 -.006 .119 -.032 .001 -.007 .127 - - - -

S15 -.040 .002 -.002 .246 -.037 .001 -.007 .174 -.079 .006 -.004 .608 -.030 .001 -.006 .137 -.041 .002 -.006 .212 -.083 .007 -.003 .676

S16 -.058 .003 -.003 .516 -.072 .005 -.003 .655 -.072 .005 -.005 .516 -.122 .015 .008 2.328 -.074 .005 -.003 .678 -.082 .007 -.003 .666

S17 -.055 .003 -.003 .473 -.063 .004 -.004 .501 -.097 .009 -.001 .922 -.028 .001 -.006 .123 -.050 .002 -.006 .306 -.090 .008 -.002 .796

S18 .024 .001 -.006 .087 .137 .019 .011 2.371 .075 .006 -.004 .558 .021 .000 -.006 .070 .153 .023 .016 2.981 .103 .011 .001 1.057

S19 -.087 .008 .001 1.174 -.002 .000 -.008 .000 .028 .001 -.009 .076 -.091 .008 -.002 1.290 -.002 .000 -.008 .001 .010 .000 -.010 .010

S20 -.098 .010 .003 1.489 -.266 .071 .063 9.450 -.350* .123 .114 13.705 -.074 .005 .001 .857 -.261** .068 .061 9.062 -.332* .110 .101 12.142

S21 .119 .014 .008 2.235 .283* .080 .073 10.782 .378* .143 .134 16.307 .117 .014 .007 2.163 .280** .078 .071 10.511 .361* .130 .122 14.693

S22 .025 .001 -.006 .099 -.025 .001 -.007 .079 -.048 .002 -.008 .227 .008 .000 -.006 .011 -.046 .002 -.006 .261 -.045 .002 -.008 .199

S23 -.080 .006 .000 1.007 -.001 .000 -.008 .000 .032 .001 -.009 .100 -.068 .005 -.002 .712 .002 .000 -.008 .000 .020 .000 -.010 .041

S24 .175 .030 .024 4.872 .316* .100 .092 13.711 .397* .158 .149 18.376 .167 .028 .022 4.449 .309 .095 .088 13.049 .385* .148 .140 17.051

S25 .001 .000 -.006 .000 -.081 .007 -.001 .815 -.057 .003 -.007 .324 .003 .000 -.006 .002 -.073 .005 -.003 .668 -.063 .004 -.006 .394

S26 -.058 .003 -.003 .515 -.095 .009 .001 1.122 -.126 .016 .006 1.569 -.041 .002 -.005 .256 -.083 .007 -.001 .866 -.129 .017 .007 1.670

S27 .076 .006 -.001 .903 .023 .001 -.008 .064 -.040 .002 -.009 .160 .057 .003 -.003 .508 .008 .000 -.008 .008 -.048 .002 -.008 .224

S28 -.102 .010 .004 1.620 -.160 .026 .018 3.267 -.118 .014 .014 1.394 -.063 .004 -.003 .609 -.132 .017 .010 2.208 -.100 .010 .000 .990

S29 -.060 .004 -.003 .554 -.064 .004 -.004 .514 -.050 .002 -.008 .244 -.080 .006 .000 1.006 -.061 .004 -.004 .467 -.047 .002 -.008 .214

S30 .050 .003 -.004 .391 .159 .025 .017 3.207 -.059 .003 -.007 .337 .047 .002 -.004 .347 .126 .016 .008 1.985 -.060 .004 -.007 .351

166

167

After studying the correlation matrix, now, attempt is being made

to examine the contribution of each independent variable in explaining

the long run performance of IPOs. The results are summarized in Table

7.8 for both measures of returns for all the time intervals. A perusal of

the table reveals that:-

1. Age of the company is positively related with raw returns at the

end of two years and three years in case, return is measured from

offer date and at the end of two years when measured from listing.

As such, age is found to be positively affecting the long run

performance of IPOs.

2. The coefficient of Issue size is significantly positive when regressed

against raw return at the end of two years, measured from offer

date (L2), thus indicating a positive relation between issue size and

IPO performance in long run.

3. Looking at the listing delays, the coefficient is negative, but

insignificant in all the regression (against various measures of raw

return) indicating an insignificant or no relation in the study.

4. Reciprocal of the IPO price is positively and significantly related

with the returns at the end of two and three years, when measured

from offer date. It also positively affects the returns at the end of

three years when measured from listing date. Overall, therefore, it

can be concluded that the price of the IPO is inversely related to its

long run performance.

5. While none of the time dummies are statistically significant, except

S12 and S18 have positive signs for all coefficients (when regressed

against various measures of return) whereas, others have negative

signs in most cases. It suggests that the raw returns could have

been higher in case of IPOs that were listed in 1999 and 2005

compared with other years.

6. Looking at the nature of industry, it was found that, IPOs in case

of both manufacturing and services industries have got

168

significantly higher returns at the end of second year, for return

measured from offer date and in second and third year when

return measured from listing. Manufacturing industry IPOs also

performed better at the end of second and third year when return

is measured from offer date.

7. Finally, looking at the type of business, it has been found that long

run performance measured in terms of returns from offer date, as

well as listing by firms in financial services industry, is better than

the IPOs in other industries.

The results discussed above are in line with the results of the

correlation matrix. However, it is worth noting that the results obtained

through the bivariate analysis, obtained particularly through the

regression analysis can suffer from the problem of specification bias, and

therefore, are only indicative in nature. To provide more extensive

analysis and to get in depth inference, the multivariate effects of the

possible explanations of long run performance have to be captured.

Accordingly, stepwise regression analysis has been conducted,

incorporating the continuous and categorical variables as defined in

Table 7.1.

Tables 7.9 (A) (B) (C) and Tables 7.10 (A) (B) (C) present the results

of regression analyses with R1, R2, R3, and L1, L2, L3 as dependent

variables. The significant determinants of long-run performance have

been summarized in Table 7.11. A perusal of the tables reveals that S3,

and S5 are related significantly and negatively with R1 while S1 and S24

are related significantly and positively with R1. All the determinants

taken together explain 10.7 Percent of variation in one-year after market

performance measured in terms of raw returns. S1 (age of the company)

is the major determinant of one year, medium and long-run performance

followed by S24, S3, and S5.

The significant determinants of two-year performance (R2) are S4,

S24, S18, S3 and S5. All these variables explain 40 Percent of variation in

169

the performance. The major contributor in this variation is S4 which

alone explains nearly 21 Percent variation, followed by S24, S18, S3 and S5.

Table 7.9(A) Determinants of One-Year Performance (Including Initial Return)

A Step-wise Regression Analysis Variables Entered R2 Adjusted

R2

R2

Change

F

Change

F Partial

Correlations

t

Value

S1 .034 .028 .034 5.475 5.475

S1, S24 .065 .053 .031 5.049 5.334

S1, S24, S3 .082 .064 .071 2.899 4.566

S1, S24, S3, S5 .107 .084 .025 4.300 4.574

Variables Excluded

S2 -0.01 -0.16

S4 0.09 1.16

S6 -0.05 -0.65

S7 -0.01 -0.12

S8 0.08 1.00

S9 0.03 0.41

S10 -0.11 -1.30

S11 -0.05 -0.58

S12 0.11 1.42

S13 -0.02 -0.26

S14 0.06 0.71

S15 -0.03 -0.40

S16 -0.08 -1.03

S17 -0.04 -0.44

S18 0.05 0.60

S19 -0.10 -1.22

S20 0.05 0.65

S21 -0.06 -0.75

S22 0.10 1.29

S23 -0.05 -0.66

S25 0.03 0.38

S26 -0.01 -0.08

S27 0.08 0.93

S28 -0.12 -1.48

S29 -0.06 -0.70

S30 0.09 1.07

170

Table 7.9(B) Determinants of Two-Year Performance (Including Initial Return)

A Step-wise Regression Analysis

Variables

Entered

R2 Adjusted

R2

R2

Change

F

Change

F Partial

Correlations

t

Value

S4 0.21 0.20 0.21 32.89 32.89

S4, S24 0.31 0.30 0.10 17.38 27.31

S4, S24, S18 0.35 0.33 0.04 7.09 21.47

S4, S24, S18, S3 0.39 0.37 0.04 8.08 19.06

S4, S24, S18, S3, S5 0.40 0.38 0.02 3.59 16.29

Variables Excluded

S1 0.10 1.05

S2 0.08 0.89

S6 -0.02 -0.18

S7 0.14 1.60

S8 0.00 0.03

S9 -0.13 -1.41

S10 -0.08 -0.84

S11 0.04 0.46

S12 -0.01 -0.10

S13 0.07 0.72

S14 0.01 0.12

S15 -0.05 -0.60

S16 -0.02 -0.18

S17 0.10 1.12

S19 -0.10 -1.11

S20 -0.06 -0.68

S21 -0.02 -0.21

S22 -0.03 -0.28

S23 -0.06 -0.68

S25 0.02 0.20

S26 -0.03 -0.30

S27 0.08 0.90

S28 -0.12 -1.29

S29 0.06 0.64

S30 0.13 1.47

171

Table 7.9(C) Determinants of Three-Year Performance (Including Initial Return)


Variables Entered

R2 Adjusted R2

R2

Change F Change

F Partial

Correlations t

Value

S24 0.16 0.15 0.16 18.38 18.38

S24, S1 0.18 0.17 0.02 2.97 10.86

S24, S1, S4 0.22 0.20 0.04 5.04 9.22

S24, S1, S4,

S3 0.25 0.22 0.02 2.93 7.78

Variables Excluded

S2 0.09 0.92

S5 -0.10 -0.97

S6 0.05 0.46

S7 0.06 0.63

S8 0.08 0.73

S9 -0.05 -0.45

S10 -0.07 -0.68

S11 0.01 0.08

S12 0.04 0.41

S13 -0.07 -0.63

S15 -0.07 -0.68

S16 -0.07 -0.65

S17 -0.07 -0.64

S18 0.08 0.80

S19 -0.02 -0.18

S20 -0.02 -0.21

S21 0.05 0.45

S22 0.07 0.69

S23 0.06 0.62

S25 -0.08 -0.79

S26 -0.07 -0.64

S27 -0.01 -0.12

S28 0.08 0.79

S29 -0.03 -0.30

S30 -0.05 -0.52

172

Table 7.10(A) Determinants of One -Year Performance (Excluding Initial Return)


Variables Entered

R2 Adjusted

R2

R2

Change F

Change F

Partial Correlations

t Value

S12 0.028 0.022 0.028 4.532 4.53

S12,S24 0.048 0.036 0.020 3.181 3.89

Variables Excluded

S1 -0.08 -0.93

S2 -0.01 -0.16

S3 -0.13 -1.57

S4 0.08 1.00

S5 -0.06 -0.78

S6 0.12 1.54

S7 -0.02 -0.28

S8 0.10 1.21

S9 0.03 0.38

S10 -0.07 -0.85

S11 -0.04 -0.51

S13 0.00 -0.03

S14 0.04 0.53

S15 -0.01 -0.12

S16 -0.10 -1.30

S17 0.00 -0.06

S18 0.05 0.66

S19 -0.09 -1.10

S20 0.06 0.75

S21 -0.04 -0.46

S22 0.05 0.62

S23 -0.05 -0.63

S25 0.02 0.28

S26 -0.01 -0.08

S27 0.06 0.73

S28 -0.04 -0.46

S29 -0.06 -0.77

S30 0.07 0.84

173

Table 7.10(B) Determinants of Two -Year Performance (Excluding Initial Return)


Variables

Entered

R2 Adjusted

R2

R2

Change

F

Change

F Partial

Correlations

t-

Value

S4 0.14 0.13 0.14 19.87 19.87

S4, S24 0.23 0.22 0.09 15.03 18.58

S4, S24, S18 0.28 0.26 0.04 7.15 15.39

S4, S24, S18, S3 0.30 0.28 0.03 5.09 13.20

S4, S24, S18, S3,

S5 0.32 0.29 0.02 2.96 11.32

S4, S24, S18, S3,

S5, S7 0.34 0.31 0.02 3.13 10.12

Variables Excluded

S1 0.03 0.36

S2 0.02 0.24

S6 0.04 0.44

S8 0.00 -0.05

S9 -0.10 -1.12

S10 -0.05 -0.54

S11 0.02 0.18

S12 0.03 0.37

S13 0.05 0.56

S14 0.02 0.19

S15 -0.03 -0.38

S16 -0.02 -0.21

S17 0.12 1.28

S19 -0.06 -0.63

S20 -0.05 -0.51

S21 -0.03 -0.29

S22 -0.05 -0.49

S23 -0.07 -0.78

S25 0.02 0.20

S26 -0.03 -0.35

S27 0.05 0.59

S28 -0.05 -0.51

S29 0.02 0.17

S30 0.09 0.98

174

Table 7.10 (C) Determinants of Three -Year Performance (Excluding Initial Return)


Variables Entered

R2 Adjusted R2

R2

Change F Change

F Partial

Correlations t

Value

S24 0.15 0.14 0.15 17.05 17.05

S24, S4 0.18 0.16 0.03 3.33 10.39

S24, S4, S3 0.21 0.19 0.03 4.00 8.47

S24, S4, S3,

S1, 0.23 0.20 0.02 2.85 7.19

Variables Excluded

S2 0.06 0.59

S5 -0.09 -0.86

S6 0.10 0.98

S7 0.07 0.68

S8 0.06 0.54

S9 -0.04 -0.38

S10 -0.06 -0.57

S11 0.01 0.11

S12 0.04 0.42

S13 -0.06 -0.57

S15 -0.07 -0.72

S16 -0.08 -0.79

S17 -0.07 -0.68

S18 0.12 1.16

S19 -0.04 -0.38

S20 -0.01 -0.10

S21 0.04 0.35

S22 0.08 0.76

S23 0.05 0.49

S25 -0.08 -0.79

S26 -0.07 -0.70

S27 -0.02 -0.21

S28 0.09 0.86

S29 -0.03 -0.25

S30 -0.06 -0.60

S2 0.06 0.59

175

Table 7.11 Determinants of Long-run Performance of IPOs:

Summarized Results of Step-wise Regression Analyses

Significant Determinants Long run Performance of IPOs: Dependent Variables

R1 R2 R3 L1 L2 L3

S1 0.233 --- 0.206867 --- --- 0.165443

S3 -0.164 0.253874 -0.1569 --- 0.212198 -0.1727

S4 --- 0.653217 0.255824 --- 0.545777 0.261995

S5 -0.17917 -0.14618 --- --- -0.14566 ---

S6 --- --- --- --- 0.132983 ---

S12 --- --- --- 0.144157 --- ---

S18 --- 0.254474 --- --- 0.270867 ---

S24 0.233158 0.404563 0.231903 0.142331 0.387052 0.229253

R2 0.11 0.40 0.25 0.05 0.34 0.23

Adjusted R2 0.08 0.38 0.22 0.04 0.31 0.20

* Significant at 0.01 level of significance ** Significant of 0.05 level of significance

The variables which significantly affect 3-year performance (R3) are

S24, S1, S4, and S3. First three of these positively affect the 3-year

performance while the S3 has a negative impact. Together, these

variables explain 24 Percent of the variation in the performance. Of this,

16 Percent of this variation is explained by S24 followed by S1 (4 Percent),

S4 (2 Percent) and S3 (2 Percent).

The above discussion is based on long-run performance as a

dependent variable, which has been measured in terms of raw return

that includes initial return also. The stepwise regression analysis is

performed after excluding this initial return from the long-run

performance. The results have been summarized in the Tables 7.11

mentioned above. The dependent variables have been labelled as L1, L2

and L3 representing performance (excluding initial return) at the end of

one, two and three years.

176

The Tables 7.11 reveal that one year long-run performance labelled

as L1 is significantly and positively related with S12, and S24. The

predictive power of these variables is low however and these two taken

together explain just around 5 Percent of variation in the performance.

The table 7.10 (B) reveals that S4, S24, S18, S3 ,S5, and S7 are significantly

associated with the two-year performance (L2). Further, barring S5 all

others affect the L2 positively. Taken together, these variables explain 34

Percent of variation in the two-year performance. S4 is the major

contributor with 14 Percent explanatory power followed by S29, S18, S3

and S10. The three-year long-run performance as shown by table 7.10 (C)

is significantly affected by S24, S4, S3, and S4. These variables explain 23

Percent of the variation in the performance, of which, 15 Percent is

explained by the S24 alone while the rest explain 3 Percent, 3 Percent and

2 Percent variation respectively.

The summary of all the regressions run and results obtained is

provided in the table 7.11. The table can be interpreted as follows:

1) Age of a company affects the long-run performance after one

and two years positively and also the three-year performance

after excluding the initial returns. But the quantitative impact

declines with time as is reflected by decline in the size of the

coefficients from R1 to R2 and then L3.

2) The listing delay of the IPO is a significant variable in the

determining the long run performance but the direction of its

impact is not consistent. While it impacts the one-year long-run

performance negatively, its impact on two year performance is

positive. However, long term performance after three years is

always negatively impacted by listing delay, irrespective of the

fact that whether initial return is included or not.

3) Reciprocal of the IPO price has no impact on performance after

one year but significantly and positively impacts the long run

177

performance after two and three years. Also, as a sign of

robustness, its impact does not change whether the initial

return is included or not while computing performance.

4) Reputation of lead manager is found to be significantly and

negatively related with long run performance as is reflected in

the coefficients of R1, L1 and R2. However, this variable does not

impact performance after three years.

5) Oversubscription is also found to be positively related with the

long run performance but the impact is significant only in case

of two year performance computed after excluding the initial

returns (L2).

6) Turning to the year dummies, the table shows that IPOs issued

in year 1999 get higher return after one year if the performance

is computed after excluding the initial return.

7) The year dummy for 2005 however is more significant. The IPOs

issued in 2005 recorded better performance at the end of two

years irrespective of the fact that the initial return is included or

not while computing performance.

8) Finally, looking at the activity based Classification of the

Industry, IPOs from the Financial Service Industry consistently

outperformed the IPOs from other industries across the board.

It is seen from the tables that IPOs in the financial services

domain recorded better long run performance after one, two and

three years and the result did not vary whether the initial

returns were included in computing the performance or not.

However, in both measures of performance, the coefficient is

larger for the second year, indicating a kind of inverted U

relation between performance and time in case of IPOs from the

financial services industry.

Overall, in the above analysis, it may be concluded that many

variables explain the medium and long run performance of IPOs in India.

178

These include age of the company, listing delay, IPO price, reputation of

lead manager and over subscription. Further, the dummy variables for

year and nature of the industry reveal that these factors can also impact

the long run performance of IPOs after different lags.

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