The market impact of change in corporate diversification (focus): some new evidence.

ABSTRACT

Market reaction to seasoned equity issue is mostly negative but the effect of the level of a firm's diversification on the market response is not clearly understood. This paper examines the impact of corporate diversification on seasoned equity offerings. It has been found that for high focused (i.e. less diversified) firms market reaction is less negative. But when the relationship between the change in focus and market impact is examined, it is observed that market reacts more negatively to firms which have increased their focus in the recent past. This finding supports the arguments of both information asymmetry and free cash flow theories.

1. INTRODUCTION

Corporate diversification through acquisition or other means is the source of external growth and an indicator of the company's organizational and structural changes. But the impact of corporate diversification and more importantly change in the level of diversification (focus) on the market reaction to the seasoned equity offerings, has not received much attention. Two of the most pertinent research questions are: 1) Does diversification affect shareholders' wealth, and 2) what is the effect of diversification on information asymmetry between managers and shareholders, and consequently on the value of seasoned equity offerings.

Empirical evidence regarding the effect of diversification on the value of the firm is not conclusive. Weston (1970) and Williamson (1975) argue that diversified firms are more profitable because of their ability to pool internally generated funds and allocate them properly. For diversified firms economies of scale [Teece (1980)] and efficient allocation of resources [Stein (1997)] are expected to have a positive impact on valuation.

Lewellen (1971) showed the benefit of coinsurance through diversification and found that diversified firms have greater debt capacity. If, in a world of taxes, debt funds are cheaper than equity funds, borrowing will increase the value of equity. Chandler (1977) found that multidivisional firms would be able to create specialized divisions and thus will benefit from inherent efficiency. Stulz (1990) argues that diversified firms are capable of reducing the under-investment problem [Myers (1977)] through the creation of a larger internal market. Shleifer and Vishny (1992) contend that conglomerates would have a higher debt capacity because they can sell assets in those industries that suffer the least from liquidity problem. Thus diversified companies will be able to make more positive net present value investments than their segments would make as separate firms.

Opponents of the 'positive impact' theory focused on the cost of diversification. Amihud and Lev (1981) mention that managers prefer diversification in order to protect the value of their human capital. In the context of both Jensen's (1986) free 'cash flow theory' and 'agency theory' managers benefit from managing larger, diversified firms. These firms have relatively larger debt capacity. So, the management might tend to indulge them in value decreasing investment projects (Berger and Ofek, 1995). Based on a similar argument Meyer, Milgram, and Robert (1992) argued that a failing firm when standing alone can not have a value less than zero but under the conglomerate structure the failing firm might have a negative value. The profitable division(s) carrying the failing division(s) will ultimately reduce the value of the conglomerate.

With the exception of Matsusaka (1993) there is very little empirical evidence that supports the benefit of diversification. Morck, Shleifer, and Vishny (1990) documented those announcements of unrelated acquisitions result in a negative market return. Lang and Stulz (1994), and Berger and Ofek (1995) have found that diversified firms trade in the market at a discount of between 13 to 15 percent compared to a portfolio of single segment firms in the same industry. A similar finding was also observed for Japanese and UK firms (Lins and Servaes, 1997). While examining the sensitivity of cash flows of one segment to another, Shin and Stulz (1997) have found that the cross subsidization among the segments is inefficient in general.

Some researchers have argued that diversification increases the information asymmetry between managers and shareholders [Myerson (1982) and Harris, Kriebel, and Raviv (1982)]. They contend that increased diversification makes it more difficult to get information about the firm. So, information asymmetry costs are higher in conglomerates than in more focused firms.

Examination of the relationship between information asymmetry and market reaction to the announcement of seasoned equity offerings reveals that as the level of information asymmetry increase, the greater is the value loss to the firm (Dierkens (1991)]. In a more recent work, Karim, Ahmed, and Rutledge (2000) documented that market reaction to seasoned equity offering is consistently negatively related to the level of information asymmetry.

In this paper attempt has been made to understand the relationship between information asymmetry and market impact through the examination of market's differential reaction between diversified and focused firm at the announcement of seasoned equity offerings. It is already established in the market place that market reaction to seasoned equity offering is generally negative. If the level of diversification is a relevant factor then it is expected that market reaction to such announcements should be different for firms with different levels of diversification. Therefore, it would be of great interest to look at how market reaction to such announcements (announcement of seasoned equity) varies depending on the diversification level of the issuing firm. A more significant aspect of this paper is that it also examines the 'signaling effect' of the change in diversification or focus, i.e. how does the stock market react to the knowledge that the firm has recently changed its level of focus.

2. HYPOTHESIS

Lewellen (1971) showed that debt capacity of diversified firms is higher than un-diversified or 'focused' firms. So, it is possible for diversified firms to have a lower cost of capital. When a diversified firm issues equity instead of debt to finance investment project, market might interpret such an action as an over investment problem and/or inefficiency of the managers. Since empirical evidence has already established that equity issuance is a costly action as well as a value-decreasing event, when there is debt capacity available the issuance of equity is certainly bad news. On the other hand, if the firm has already exhausted its debt capacity then the possibility of over investment becomes a concern to the outside investors. Also, a positive correlation has been demonstrated between diversification and information asymmetry. Considering these factors, one should expect that the market reaction should be negative. Thus:

   H1: A diversified firm issuing seasoned equity should experience
   more negative reaction at the announcement of such issuance when
   compared with of that of an un-diversified firm.

In this context it is also important to see how market reacts to the knowledge that the issuing firms have changed their diversification level in the recent past. The most relevant structural change in this context is: firms' reduction of lines of business through the sale of existing, unrelated segments/divisions in order to increase the focus of the overall corporate objective. And the other one is the acquisition of a new segment /division to widen the corporate diversity and hence reducing focus (i.e., becoming more diversified).

Recent empirical work in this area have documented that increased focus is associated with increase in the value of the firm (Berger and Ofek (1995), Comment and Jarrell (1995)). These papers argue that such a positive effect is due to the market's understanding that these firms are now (after selling the segments) capable of managing the corporation more efficiently than before.

In addition to the arguments suggested in the above literature, there are other factors that might have also contributed toward the positive reaction to the sale of unrelated businesses (focus increasing activity). Firms after increasing their focus will have the proceeds from the sale of unrelated business available to them which should lessen the need to raise capital in the market. They are expected to be more capable of maximizing their value by not forgoing positive net present value (NPV) projects. Therefore, it is very likely that these firms should gain value in the market, as long as market value of a firm is based on the discounted present value of the future net present value attainable to the firm.

In this paper it is argued that if these firms then decide to raise capital by issuing equity in the subsequent years of focus increasing activities, the market becomes suspicious about the efficiency of cash allocation by the management and also become skeptical about the positive net-present-value of the future project to be undertaken, if they have used their fund collected from the sale of assets to pay off debts then they should have debt capacity outstanding, and if they have not used up their funds then they should be using that fund to finance the project and thus avoid any value loss. Under these circumstances:

   H2: If the seasoned equity issuing firm has increased its focus
   in the recent past then the amount negative effect of such
   issuance will be the greatest.

3. DATA AND METHODOLOGY

3.1 Data

Two data sources, the half-yearly publication of Investment Dealer's Digest (1989-1994) and data 'Compustat PCPLUS 1996' was used. From the first data source seasoned issue offering date (hereinafter, event date) information and from the second data source corporate diversification level data, 4-digit SIC codes of the companies and the reported sales by the SIC code were obtained. The financial year-end date for the sample was collected from the Wall Street Journal Index (WSJI).

The following criteria were then set for each event to be a part of the sample for the reasons described below:

a: For the financial data, Compustat Annual data tape of 1996 (hereinafter, Compustat) is used. If the sample firm is not in the data tape then events related to that company are deleted from the sample.

b: For market data, the daily return data tape of Center for Research in Security Price (CRSP) for period ending December 31, 1996 is used. Abnormal return calculation methodology requires that each sample event must have return data for -187 days from event date up to +15 days from event date. Sample event failing to meet these criteria is also dropped from the sample.

C: For cross sectional analysis on yearly data from Compustat, in order to avoid the confounding effect, sample events were deleted which have seasoned or combined issue within the past 12 months or within the subsequent 12 months. In case of firms making multiple issues within the event period (1989 through 1994) the earliest event was first considered provided there was no seasoned or combined offering in the past 12 months of such offering. A second event to be considered in the sample from the same company, the second offering must be at least 12 months apart from the first offering provided no similar offering took place within the subsequent 12-month period.

d: To avoid possible information contamination around the sample event date from offerings other than seasoned or combined offerings (such as offering of debt, convertibles etc.) sample events were also eliminated where such events were present within 30 days surrounding the sample event date.

e: We also deleted those events, which are not listed in the American Stock Exchange (AMEX) or in the New York Stock Exchange (NYSE) or in the NASDAQ Market System.

This screening process resulted in a total of 739 events by 459 firms (Table 1). From this total, 189 events were dropped due to non-availability of data leaving us with 550 events by 459 firms. Table 2 contains the distribution of the sample events by the level of diversification or focus of the issuer. Exchange listing and industry classifications of the firms are also given.

3.2 Methodology

Compustat data were used to calculate the measures of focus level of sample firms. The first measure is a net sale based Herfindahl index. Net sales represent gross sales (the amount of actual billings to customers for regular sales completed during the period) reduced by cash and trade discounts, and returned sales and allowances for which credit is given to customers. Net sales are reported in Compustat for each segment only if the segment sale is at least 10% of the total sales. A net sales based Herfindahl index reflects the degree to which revenues are concentrated in just a few of a company's business segment, and calculated across n business segments as the sum of squares of each segment i's sales, [S.sub.i], as a proportion of total sales:

[H.sub.t] = [[summation of].sup.n.sub.i=1] ([[S.sub.it]/[[summation of].sup.n.sub.i=1] [S.sub.it]).sup.2]

Where, [H.sub.t] takes values between zero and one. The closer [H.sub.t] is to one, the more concentrated are the firm's sales within a few segments, and hence the more focused its operations. High focused firms are those which have [H.sub.t] in the event year greater than the industry adjusted median Herfindahl index, and rest is called low focused or diversified firms.

Samples were sub-grouped according to their change in focus level. If the firms have increased focus in two years prior to the event year, they were identified as focus-increased firms. On the other hand, if firms decreased their focus over the two years prior to the event year, then those were identified as focus decreased firms.

There were 67 sample events from the Banks, 390 events from the Industrial samples and 93 samples from the Utilities. Of the total sample 470 sample events belonged to the low-focus group, and 80 events were in the high-focus group. High focused events are those where issuers' level of diversification as measured by Herfindahl Index (HI) was greater than the median Herfindahl Index of the overall sample.

Market reaction to seasoned equity offerings were measured using daily excess returns of the events. The event day is designated as day 0 in the event time. The estimation period is t = -162 to -36 relative to the event date (day 0), and was used to calculate the normal return of the event window that is a 31 day period (-15 through +15 relative to event day).

The market model was used to estimate normal or expected returns of the common stocks of the sample events. In this ordinary least squares model, returns on a given security were regressed against the concurrent returns of the market. The Center for Research on Security Prices (CRSP) equally- weighted index was used as a proxy for the market Portfolio.

[R.sub.jt] = [[alpha].sub.j] + [[beta].sub.j][R.sub.mt] + [[epsilon].sub.jt]

Where,

T = day measured relative to the event,

[R.sub.jt] = return on security j on day t,

[R.sub.mt] = daily equally-weighted index for all common stocks on NYSE & AMEX and NASDAC firms on the CRSP tape on the event date t (a proxy for the market portfolio of the risky assets)

[[alpha].sub.j] = estimated period intercept of firm j

[[beta].sub.j] = Ordinary Least Square (OLS) estimates of firm j's market model parameters.

[E.sub.jt] = the error term of security j on the sample event day

The abnormal returns (AR) for each sample event j on day t are obtained as follows:

A[R.sub.jt] = [R.sub.jt] - ([[alpha].sub.j] - [[beta].sub.j][R.sub.mt])

Daily abnormal or excess returns ([Ar.sub.jt]) were calculated for each sample event in the study over the event window (The expected value of A[R.sub.jt] is zero by definition). The abnormal returns (AR) for each sample event j on the sample event date t were calculated as:

Then the Cumulative abnormal returns was calculated for three days around event day and five days around the event date by summing the abnormal returns of sample events around the date, and the notations used in this respect are--CA[R.sub.0,0], CA[R.sub.-1,+1], CA[R.sub.-2,+2].

Cross sectional analysis was employed in the study to identify the relationship between the identified independent variables with the dependent variable. The dependent variables are CA[R.sub.0,0], and CA[R.sub.-1,+1] and the main independent variables are: Herfindahl Index(HI), Tobin's Q as a measure of growth opportunities, leverage ratio, market value of assets, cash flow to total assets, issue size and dummies for the sub-group of sample. In the sample additional independent variable for the focus level(high-focus = 1, low focus = 0) were used. Chung and Pruitt's model was used to estimate the approximate Tobin's Q:

Approximate Tobin's Q = (MVA + PS + DEBT)/TA

Where MVA = Product of firm's share price and number of common shares Outstanding

PS = Liquidating value of firm's outstanding preferred stock DEBT = Short-term liabilities net of short-term assets plus book value of the firm's long-term debt

TA = Book value of the total assets of the firm

Firm's leverage ratio was defined as the book value of current liabilities plus long-term debt divided by the sum of the book value of current and long-term debt, market value of common stock, the liquidating value of common stock (Pilotte, 1992).

Calculated Tobin's Q of sample firms were adjusted by using the industry median. The same step was also taken for book-to-market ratio and as well as for leverage ratio. The industry-adjusted value for a variable was calculated by subtracting the median value for the industry from the actual value for the firm. Event year was defined as the financial year within which firm made the equity issue announcement. For the purpose of the study the 'last year' (i.e., the year before the event year) was the relevant year. Because, this was the year where the issue event's impacts on accounting numbers were not incorporated. In other words, the grouping of the samples is made based on last year's value of relevant variable.

4. EMPIRICAL RESULTS

Table 3 shows the event-day abnormal return, 3-day cumulative abnormal returns, and 5-day cumulative abnormal returns of the sample events used in this study. The t-statistics, reported in the table 3 indicates that all the abnormal returns were negative and highly statistically significant except for the focus-decreased firms. These findings are consistent with the existing empirical findings on seasoned equity offerings that such an event is a value-decreasing event.

A more interesting observation here is the market's reaction to focused increased firms. As reported in table 3, both high and low-focus firms reacted negatively at the announcement of equity issuance, though reaction to high-focus firms was less negative. The reason being that equity issues by high-focus firms are viewed more favorably by the market, as these firms have lower level of information asymmetry due to less diversity in their corporate structure. These results are different from that of Nassirpour, Karim, Siegel, and Ahmed (1998). But when the 'change in focus' is considered, focus increased firms reacted more negatively than focus decreased firms. These results were reproduced in tables 4 and 5 where differences in cumulative abnormal return (CAR) over three event periods were estimated. CAR for high-focus firms were less negative for all three event periods, but the difference was significant only for the (-1 to +1) period. For firms, which experienced change in focus, as reported in table 5, in all cases CAR for focus increased firms were found to be significantly more negative than focus.

This supports the second hypothesis, which contends that market might get surprise if focus increased firms raise capital in the equity market. Since these firms increased their focus over the past years, they should have funds available from the sale of assets. This relatively more negative reaction supports the postulations of 'Information Asymmetry Theory' and 'Free cash Flow Theory'.

Results of the cross sectional regressions are produced in table 6. The dummy variable (HF/LF-D), takes value 1 (one) if the firm is a focused-firm (non-diversified and/or less diversified) or takes the value 0 (zero) otherwise. Industry adjusted Herfindahl Index (HI) was used to stratify the sample. If the HI of the sample firm was more than the industry median, then the sample was placed in the high focus group. Otherwise it was classified as a low focused firm. It was found that the coefficient for the dummy is statistically significant and has positive sign for all the models (model 1 through model 5). This implies that market's reaction to seasoned equity offerings has a positive association with issuing firms' diversification / focus level. That is, if the firm is more focused less negative is the market reaction to such issue announcements. This finding supports the arguments of Myerson (1982), Harris, Kreiebel, and Raviv (1982) that firms by decreasing information asymmetry through increasing focus level (anti-diversification) increases the value of the firm.

We also ran a cross sectional regression only for the firms which experienced change in focus in the recent past (Table 7). The dummy variable INCR/DCR-F (increased focus=1, otherwise=0), is consistently negative and significant for all the models, in other words, the market negatively views focus-increased samples' equity issuance. Interestingly enough, the coefficient of the variable HF/LF-D (dummy variable for level of focus) though still positive, loses its significance in the presence of INCR/DCR-F. Market seems to assign more importance to the news of 'change' in focus than its actual level. This paper argues that this may be due to fact that market interprets this as misuse of free cash flow. Because these firms should have proceeds from the sale of assets when they increased their focus. This argument is supported when it is observed (Table 6) that the coefficient for cash flow to total assets consistently shows a negative sign.

5. CONCLUSION

The analysis of the impact of corporate focus/diversification on market's reaction to seasoned equity offerings reveals that market reaction is less negative for the high-focused firm when compared with low-focused diversified firms. The argument is that high-focused firms are high value firms as well as have less information asymmetry due to their lower level of diversity. Therefore, issue announcements by them should have less negative impact when compared with diversified (low-focused) firms.

A more important contribution of this paper is the examination of the differential market reaction to equity announcements by focus-increased firms and focus decreased firms. It is found that market reaction is significantly more negative for firms who have increased their focus level in the recent past. Interpretation is that financing needs of the focus-increased firms should have been met by the funds already acquired through the focus increasing activity in the recent past (i.e. sale of 'unrelated' assets). When these firms try to raise capital in the equity market subsequent to focus increasing activities, it may reflect on their efficiency or lack of it in using the available cash. So, market should react negatively at the announcement of equity issuance by these firms. More importantly, in the regression the dummy for focus changing activity, INC/DCR-F (Table 7) is consistently negative and significant.

Findings of this paper indicate that corporate structural change through the change in the diversification/focus level, is an important factor in understanding the market reaction to equity issue and raise questions about the conclusions of the previous empirical works.

TABLE 1
THE DISTRIBUTION OF SAMPLE EVENTS (1) AND SAMPLE FIRMS (2) BY EXCHANGE
LISTING (3)--NEW YORK STOCK EXCHANGE(NYSE), AMERICAN STOCK EXCHANGE
(AMEX), AND NASDAQ MARKET SYSTEM(NSDQ); BY INDUSTRY CLASSIFICATION
(4)--INDUSTRIAL (IND), BANKS AND FINANCIAL INSTITUTIONS(BNK) AND
UTILITIES(UTL) AND BY THE EVENT YEAR.

        SAMPLE EVENTS BY             SAMPLE FIRMS BY
YEAR    EXCHANGE                     EXCHANGE

        NYSE   AMEX   NSDQ   TOTAL   NYSE   AMEX   NSDQ   TOTAL

1989    43     14     29     86      30     10     25     65

1990    35     03     23     61      22     03     14     39

1991    94     10     61     165     55     04     42     101

1992    89     15     43     147     52     07     29     88

1993    12     15     52     187     61     09     32     102
        0

1994    58     06     29     93      41     05     18     64

TOTAL   43     63     237    739     261    38     160    459
        9

        SAMPLE EVENTS BY          SAMPLE FIRMS BY
YEAR    INDUSTRY                  INDUSTRY

        IND   BNK   UTL   TOTAL   IND   BNK   UTL   TOTAL

1989    50    16    20    86      43    08    14    65

1990    41    08    12    61      29    05    05    39

1991    107   36    22    165     74    22    05    10
                                                    1

1992    98    27    22    147     64    13    11    88

1993    117   35    35    187     69    20    13    10
                                                    2

1994    67    18    08    93      46    16    02    64

TOTAL   480   140   11    739     325   84    50    45
                    9                               9

(1) Sample Events are the Seasoned Equity issue events
between 1983 and 1994.

(2) Sample Firms are the Seasoned Equity issuing firms.

(3) Exchange listings is identified through the exchange
listing code available in Compustat Annual data tape.

(4) Industry classification is done using the two-digit
SIC code, available in the Compustat data Tape.

TABLE 2
DISTRIBUTION OF SEGMENT SAMPLE EVENTS BY THE INDUSTRY
CLASSIFICATION (1) AND EXCHANGE LISTING (2) OF THE
SAMPLE EVENTS. PANEL--A SHOWS THE DISTRIBUTION FOR
THE SAMPLE EVENTS BY THE FOCUS LEVEL--HIGH-FOCUS AND
LOW-FOCUS; PANEL B SHOWS THE DISTRIBUTION BY THE FOCUS
ACTIVITY OVER THE LAST THREE YEARS--INCREASED FOCUS AND
DECREASED FOCUS.

              INDUSTRIES

              BANK   INDUSTRY   UTILITIES

PANEL--A
HIGH-         05     35         40
  FOCUSED
LOW-          62     355        53
  FOCUSED
TOTAL         67     390        93
PANEL--B
FOCUS-        10     70         28
  INCREASED
FOCUS-        0      22         12
  DECREASED
TOTAL         10     92         40

              EXCHANGES              TOTAL

              AMEX   NASDAQ   NYSE   INDUSTRY   EXCHANGE

PANEL--A
HIGH-         03     02       75     80         80
  FOCUSED
LOW-          39     162      269    470        470
  FOCUSED
TOTAL         42     164      344    550        550
PANEL--B
FOCUS-        07     11       90     108        108
  INCREASED
FOCUS-        02     02       30     34         34
  DECREASED
TOTAL         09     13       120    142        142

(1) Exchange listing is identified through the exchange
listing code available in the Compustat Annual data tape.

(2) Industry classification is done using the first
two-digit of Standard Industry Classification (SIC)
code, available in the Compustat data tape.

TABLE 3
EVENT-DAY ABNORMAL RETURN, 3-DAYS CUMULATIVE ABNORMAL RETURN, AND
5-DAYS CUMULATIVE ABNORMAL RETURN AROUND THE EVENT DATE. EVENT DATE
IS THE SEASONED EQUITY OFFERING DATE. SAMPLE ARE BROKEN DOWN BY
INDUSTRY, LEVEL OF FOCUS USING MEASURE OF HERFINDAHL INDEX, AND BY
THE CHARACTERISTICS WHETHER THE FIRM HAS INCREASED OR DECREASED FOCUS
IN THE PAST TWO YEARS. EXCHANGE LISTING, NUMBERS IN THE ITALIC ARE
THE T-STATISTICS FOR THE ABNORMAL RETURNS. FOR INDUSTRY
IDENTIFICATION OF THE SAMPLE EVENTS COMPUSTAT ASSIGNED CODE IS USED.

                        % OF          CUMULATIVE
                        POSITIVE ON   ABNORMAL
                        EVENT-DAY     RETURN
                                      ([CAR.sub.0,0])

Total Sample (550)      33.818%       -0.0077593
                                      (-6.2234969) ***
Banks (67)              38.806%       -0.0061204
                                      (-3.3220608) ***
Industrial (390)        34.103%       -0.0081631
                                      (-4.8714528) ***
Utilities (93)          29.032%       -0.0072465
                                      (-3.9996239) ***
Low-Focused firms       34.043%       -0.0081452
(470)
                                      (-5.8453073)
High-focused firms      32.500%       -0.0054922
(80)
                                      (-2.1597445) **
Focus-Decreased firms   41.176%       +0.00032344
(34)
                                      (+0.1046223)
Focus-Increased firms   33.333%       -0.0076122
(108)
                                      (-3.0157780) ***

                        CUMULATIVE         CUMULATIVE
                        ABNORMAL           ABNORMAL
                        RETURN ([CAR       RETURN ([CAR
                        .sub.1,1])         .sub.2,2])

Total Sample (550)      -0.0222482         -0.0253050
                        (-0.3524879) ***   (-8.8348033) ***
Banks (67)              -0.0223947         -0.0281230
                        (-5.2758592) ***   (-4.1881187) ***
Industrial (390)        -0.0243086         -0.0259596
                        (-8.5253349) ***   (-6.9256363) ***
Utilities (93)          -0.0135021         -0.0204041
                        (-4.6325057) ***   (-5.0737493) ***
Low-Focused firms       -0.0241938         -0.0270284
(470)
                        (-10.2757292)      (-8.6946852)
High-focused firms      -0.0108177         -0.0151799
(80)
                        (-2.1474938) **    (-2.0774432) **
Focus-Decreased firms   -0.0095545         -0.0040735
(34)
                        (-1.0687636)       (-0.3441721)
Focus-Increased firms   -0.0247227         -0.0289556
(108)
                        (-5.1248885) ***   (-4.8314578) ***

* ** *** denotes significant at 0.10(0.05)(0.01) level

TABLE 4
EVENT-DAY ABNORMAL RETURN, 3-DAYS CUMULATIVE ABNORMAL RETURN,
AND 5-DAYS CUMULATIVE ABNORMAL RETURN AROUND THE EVENT DATE OF
SEASONED EQUITY OFFERING BY THE SEGMENT SAMPLE. DIFFERENCES IN
ABNORMAL RETURNS WERE ALSO PRESENTED, LEVEL OF FOCUS USING
MEASURE OF HERFINDAHL INDEX. NUMBERS IN THE ITALIC ARE THE
T-STATISTICS FOR THE ABNORMAL RETURNS. COMBINED OFFERINGS
ARE WHERE ON THE SAME EVENT DATE BOTH PRIMARY AND SECONDARY
SEASONED EQUITY IS OFFERED.

                    LOW-           HIGH-
                    FOCUSED        FOCUSED        DIFFERENCES

TOTAL SAMPLE--550   N=470          N=80
EVENT-DAY           -0.00814518    -0.00549223    -0.002653
                    (-5.8453073)   (-2.1597445)
3-DAYS CUMULATIVE   -0.02419376    -0.01081770    -0.013376 **
                    (-0.2757292)   (-2.1474938)
5-DAYS CUMULATIVE   -0.02702838    -0.01517993    -0.011848
                    (-8.6946852)   (-2.0774432)

* ** *** denotes significant at the 0.10 (0.05) (0.01) level.

Table 5
DIFFERENCE IN CUMULATIVE ABNORMAL RETURN BETWEEN FOCUS INCREASED
(N=108) AND FOCUS DECREASED N=34 FIRMS. VALUES IN THE PARENTHESIS
ARE THE T-STATISTICS

             Cumulative Abnormal Return          Difference

Event Date   Focus Increased   Focus Decreased

(0, 0)       -0.0076122        +0.00032344       -0.0079356
             (-3.0157780) **   (0.1046223)       (-1.644) *
(-1, 1)      -0.0247227        -0.0095545        -0.0151682
             (-5.1248885) **   (-1.0687636)      (-3.44) **
(-2, 2)      -0.0289556        -0.0040735        -0.0248821
             (-4.8314578) **   (-0.3441721)      (-2.42) **

* Significant at 0.05 level

** Significant at 0.01 level

TABLE 6
CROSS-SECTIONAL REGRESSION RESULTS OF THE SAMPLES USED IN THIS SECTION
OF STUDY. DEPENDENT VARIABLE IS 3-DAY COMULATIVE ABNORMAL RETURN.
INDEPENDENT VARIABLES ARE: HERFINDAHL INDEX(HI), LEVERAGE RATIO(LEV),
TOBIN'S Q RATIO, MARKET TO BOOK RATIO(M/B), CASH FLOW TO TOTAL
ASSETS(CFTA), LOG OF MARKET VALUE OF ASSETS (L(MVA)), SIZE OF THE
SEASONED EQUITY ISSUE ADJUSTED BY THE MARKET VALUE OF ASSETS
(ISUSIZE). DUMMY HF TAKES VALUE 1(ONE) IF THE ISSUING FIRMS IS A
HIGH-FOCUSED FIRM AND 0 (ZERO) OTHERWISE.

Overall Sample
550              MODEL -1       MODEL -2       MODEL -3

INTCPT           -0.017649 *    -0.009902      -0.009704
HF/LF-D          +0.014386 **   +0.015503 **   +0.013882 **
HI               -0.007877      -0.008421      -0.005423
LEV                             -0.013642      -0.018798
TOBIN'S Q                       -0.002859      -0.000880
ISUSIZE                                        -0.000000
CFTA
L (MVA)
ADJR-SQ          0.0064         0.0069         0.0167
PROB>F           0.0682         0.01061        0.0163

Overall Sample
550              MODEL -4       MODEL -5

INTCPT           -0.012607      -0.039082 **
HF/LF-D          +0.014010 **   +0.010874 *
HI               -0.006831      +0.001398
LEV              -0.014975      -0.025446 **
TOBIN'S Q        -0.000353      -0.000333
ISUSIZE          -0.000000 **   -0.000000
CFTA             +0.034801 *    +0.035469 *
L (MVA)                         +0.003843 **
ADJR-SQ          0.0205         0.0279
PROB>F           0.0096         0.0027

** *** denotes significant at the 0.10 (0.05) (0.01) level

TABLE 7
Cross sectional regression results for the sample events which
have either increased focus or decreased focus in the past three
years. Dependent variable is the EVENT-DAY'S ABNORMAL RETURN.
Independent variables are: Leverage ratio (LEV), Tobin's Q ratio,
Cashflow to total Assets (CFTA), Relative issue size (size of the
issue adjusted by the market value of assets). Variable HF/LF-D
refers to Dummy which takes value 1 (one) if the firms is a
high-focused firm at the issue announcement year and 0 (zero)
otherwise. Dummy INC/DCR-F takes value 1 (one) if the firm belongs
to focus increase group and 0 (zero) otherwise.

Overall Sample
(142)            MODEL -1      MODEL -2      MODEL -3

INTCPT           -0.002926     -0.001786     +0.008759
HI               +0.005920     +0.003519     +0.002610
INC/DCR-F        -0.008573 *   -0.008613 *   -0.009110 *
HF/LF-D                        +0.003028     +0.004997
LEV                                          -0.025515 **
TOBIN'S Q                                    -0.000375
ISUSIZE
CFTA
ADJR-SQ          0.0071        0.0013        0.0290
PROB>F           0.2253        0.3674        0.1087

Overall Sample
(142)            MODEL -4        MODEL -5

INTCPT           +0.011178       +0.016828
HI               +0.008006       +0.005431
INC/DCR-F        -0.008807 *     -0.008546 *
HF/LF-D          +0.001990       +0.003022
LEV              -0.037151 ***   -0.040510 ***
TOBIN'S Q        =0.003536       +0.001446
ISUSIZE          -0.00000 **     -0.000000
CFTA                             -0.038430
ADJR-SQ          0.0650          0.0687
PROB>F           0.0190          0.0198

* ** *** denotes significant at the 0.10 (0.05) (0.01) level

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Dr. Mojib Ahmed earned his Ph.D. in Finance at Old Dominion University, Norfolk, Virginia in 1998. Currently he is an Associate Professor of Finance at SUNY-Empire State College, New York.

Dr. Niazur Rahim earned his Ph.D. in Finance at Virginia Commonwealth University, Richmond, Virginia in 1994. Currently he is an Associate Professor of Finance at Christopher Newport University, Newport News, Virginia.

Prof. Moshfique Uddin earned his Masters in Commerce (M.COM.) from Dhaka University, Bangladesh. Currently he is an Assistant Professor of Banking and Finance at Dhaka University.