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The effects of stock splits on the ownership mix of a firm.

I. Introduction

Many view a stock split as a purely cosmetic accounting change. The split neither affects a firm's real asset cash flows or those of its claimants nor the shareholder's proportional ownership. Therefore, a split should have no economic impact. Yet, firms often issue stock splits. For example, 5 to 10 percent of firms listed on national exchanges split their stock annually. The rationale for this decision is puzzling to financial theorists because a firm incurs transaction costs by issuing a split but receives no obvious economic benefit.

Empirical evidence shows real economic effects associated with stock splits. Grinblatt, Masulis and Titman (1984) document significantly positive abnormal returns of about 3.3 percent in the two days around a split announcement for a sample of 244 stocks having no other confounding announcement effects. Ohlson and Penman (1985) report that the volatility of a firm's stock increases by an average of 35% after the ex-date of the splits. Sheikh (1989) finds a corresponding increase in the standard deviation implied in the option prices of firms announcing splits. Brennan and Copeland (1988a) show that a firm's risk (beta) increases temporarily after the announcement and effective date of a split and increases permanently on the ex-date of a split. Finally, Copeland (1979), Lamoureux and Poon (1987), and Conroy, Harris and Benet (1990) show that stock splits diminish shareholder liquidity.

The financial literature contains several explanations for stock splits and the positive abnormal returns accompanying their announcement including the information asymmetry (signaling) hypothesis and an optimal trading range hypothesis. According to the information asymmetry hypothesis, managers of undervalued firms use stock splits to signal information about their future prospects to investors. Szewczyk and Tsetsekos (1992b) argue that the stock split will increase attention from brokers and initially increase institutional ownership more than individual ownership. They reasons that brokers have greater incentive to solicit business from institutions that generate higher commissions when trading in large blocks.

According to the optimal trading range hypothesis, managers use stock splits to broaden the ownership mix of the firm, i.e., to increase the number of shareholders and decrease the institutional ownership of the firm. The ownership mix becomes broader because the lower post-split share price makes it easier for individual investors to purchase shares in round lots while it increases the transaction cost of a fixed dollar transaction for institutional investors.

Our study examines the relationship between stock splits and the ownership mix of firms. The results contradict the conventional wisdom that stock splits broaden a firm's ownership base by increasing the number of shareholders and decreasing the institutional ownership. We show that the number of shareholders remains the same around the split but the number and percentage of shares owned by institutions increases. This evidence supports an attention-getting version of the information asymmetry hypothesis where managers of firms (especially smaller firms) employ stock splits to attract attention from security analysts and brokers.

II. Stock Split Hypotheses

In this section, we examine the information asymmetry and the optimal trading range hypothesis for stock splits and their implications for a firm's ownership mix.(1)

1. Information Asymmetry Hypothesis

According to the information asymmetry (signaling) hypothesis (Woolridge and Chambers (1983), Brennan and Copeland (1988) and McNichols and Dravid (1990)), managers use their inside information to determine split factors from which investors make inferences about managements' private information. Managers cannot set split factors too high because higher investor transaction costs accompanying lower share prices constrain them from doing so. These increasing transaction costs per dollar also constrain managers who do not have favorable private information from using stock splits. Managers with inside information are willing to accept the increased transaction costs in exchange for the higher pre-split share price resulting from the favorable signal to investors.

Szewczyk and Tsetsekos (1992a) find support for the signaling hypothesis and report an inverse relationship between the share price reaction to stock splits and the degree of institutional ownership. Specifically, the average share price reaction is nearly double for firms with low versus high institutional ownership. They reason that information asymmetries between managers and investors are greater for firms with low institutional ownership because of the efficient information acquisition activities of these institutions. Therefore, the lower the institutional ownership, the greater the ability for the stock split announcement to convey more favorable private information about a firm's future prospects to investors.

Empirical support is mixed on the information asymmetry hypothesis for stock splits. The findings of Brennan and Copeland (1988b) support the signaling hypothesis but those of Lakonishok and Lev (1987) and McNichols and Dravid (1990) are less strong.

A version of the information asymmetry hypothesis that has been receiving increased attention in the financial literature is the attention-getting hypothesis. Grinblatt et al. (1984) argue that managers of firms use stock splits to attract attention from institutional investors and financial analysts to trigger a revaluation of their future cash flows. Pricing efficiency increases because institutional investors more rapidly incorporate new information than individual investors.

Brennan and Hughes (1990) develop an attention-getting model where managers with favorable inside information attract the attention of security analysts by announcing stock splits. The lower post-split share prices increase trading volume and trading commissions for brokers giving them greater incentive to analyze and promote the stocks of these firms. Brennan and Hughes attribute the positive abnormal returns associated with stock splits to the release of the favorable private information from managements via the stock splits.

2. Optimal Trading Range Hypothesis

Another explanation for the positive abnormal returns associated with stock splits is the optimal trading range hypothesis. Lakonishok and Lev (1987) suggest that managers use stock splits to lower their firm's share price into a desired range. One reason for managers wanting to lower share price is to broaden their firm's ownership base. Individual investors may prefer low common stock prices because high prices deny them the economies of scale of purchasing stocks in round lots. Yet, institutions may prefer high stock prices because the fixed per-share transaction cost component reduces the costs for a given dollar value transaction. Satisfying the conflicting demands of these investors may create an optimal price range. Stock splits are an inexpensive way for firms to adjust their stock price into this trading range.

There is growing evidence that firms use stock splits to keep share prices within a preferred or optimal trading range. A survey by Baker and Gallagher (1980) reports that 98.4% of the responding managers believe that stock splits make it easier for small stockholders to purchase round lots. Also, 93.7% believe that stock splits keep a firm's stock in an optimal range. Evidence by Lakonishok and Lev (1987) supports these views of practitioners. They find that the aim of stock splits is mainly to restore stock prices to a normal range. This normal range is based on market and industry-wide price averages and possibly on some firm-specific prices. Stock splits and the resulting price increases occur after periods of unusual growth.

McNichols and Dravid (1990) find that split factors are an increasing function of presplit share prices. This finding implies that managers have some preferred trading range in mind when issuing stock splits. Baker and Powell (1993) report results with this finding. Using a survey of managers of firms that issued stock splits during the period 1987-1990, Baker and Powell report that managers of firms having [less than] 2-for-1 splits expressed a lower preferred trading range (about $18 to $29) than those with 2-for-1 splits (about $23 to $41).

McNichols and Dravid also find an inverse relationship between split factors and the market value of a firm's equity. This finding implies higher preferred trading ranges for larger firms. McNichols and Dravid suggest that a firm's desire to keep its stock price in a certain range may outweigh its desire to signal inside information to investors. That is, a firm's pre-split price and market value of equity explain more of the variance of split factors than information signalling variables.

Barker (1956) reports that the number of shareholders increased 30% for a sample of 90 firms that announced stock splits between December 31, 1951, and December 31, 1953. The number of shareholders increased only 6% for a control group of non-splitting firms over the same period. Barker gives several reasons for having a broader ownership base. First, a broad ownership base may help a firm raise new equity capital for expansion. Second, it may lessen the chance of price instability. Finally, a broad ownership base may increase the potential for customer ownership, especially for firms manufacturing consumer goods.

Lamoureux and Poon(1987) examine 41 stock splits during the period 1975 to 1985 and control for other contaminating announcements. They report that the mean number of shareholders for firms announcing stock splits increased 34.65% in the year of the split. The mean number of shareholders in their control sample of non-splitting firms increased only 2.11%. Yet, these studies have limitations because they use small samples and fail to consider the effects of the stock split on the institutional ownership of the firms. Thus, these studies do not provide convincing evidence on how stock splits affect the ownership mix.

Managers also may want to broaden their firm's ownership base in a self-serving effort to protect themselves from takeover threats. Institutional owners with short-term investment horizons may be more likely to respond to a tender offer than a broad base of individual investors. Szewczyk and Tsetsekos (1992a) discuss other costs of high institutional ownership. These costs include increased volatility of share prices, a short-term results orientation for a firm's management, and a lessened ability to raise capital through new equity issues.

McNichols and Dravid (1990) include attention-getting as part of their optimal price range hypothesis. They reason that a stock split and the resulting lower post-split price may increase the demand for a firm's stock. In turn, lower post-split stock prices will generate higher commissions for stockbrokers and will give them an incentive to market the firm's stock more aggressively. Yet, institutions prefer high share prices to lower their transactions cost for a fixed dollar trade amount. An optimal price range results from the conflicting demand preferences from institutional owners, stockbrokers, and the firm's desire for more recognition. Firms, especially small ones with low institutional ownership, may benefit from the lower share prices following stock splits.

3. Implications for Institutional Ownership

The information asymmetry, attention-getting, and optimal trading range hypotheses for stock splits are not mutually exclusive. For example, Grinblatt et al. (1984) develop the attention-getting hypothesis in an information asymmetry framework while McNichols and Dravid (1990) include both an attention-getting and an optimal trading range version of the information asymmetry hypothesis. Yet, the optimal trading range and the attention-getting hypotheses have different implications for the changes in institutional ownership that may result from a stock split. According to the optimal trading range hypothesis, stock splits should be associated with increases in the number of shareholders and decreases in the percent institutional ownership. The attention-getting hypothesis predicts an increase in the institutional ownership of firms announcing splits. Smaller firms, with low institutional ownership, probably have more incentive to use stock splits to attract attention from Wall Street. The effect of stock splits on the number of shareholders is unclear.

We examine how the institutional ownership and the number of shareholders of a firm change after the announcement of a stock split. Thus, our study provides additional insight into which hypothesis best explains managements' motives for issuing stock splits.

III. Data Description

We got our initial sample of 585 firms by screening the CRSP tape for stock splits of 1.25-for-1 or greater announced by firms on the New York (NYSE) and American (Amex) Stock Exchanges between January 1, 1982, and December 31, 1989. To distinguish between stock splits and stock dividends, the CRSP tape (which is based on Moody's Dividend Record) uses managements' own classification of the distribution. Thus, our sample

excluded stock dividends even when the distribution exceeded 25%. We also excluded multiple stock splits by a firm occurring within three years of each other.

The source of the institutional ownership data was Standard & Poor's Stock Guide. We collected the number of institutions holding shares of the firm announcing the split, the number of shares of the stock-split firm held by the institution, and the number of shares outstanding of the stock-split firm for six months before and after the stock split announcement. The latter two variables allowed us to calculate the percentage of shares held by institutions before and after the stock split announcement. We considered six months before and after the split as an effective tradeoff between lessening the confounding effects from other announcements while still allowing enough time for any changes in ownership mix to occur.

COMPUSTAT and Standard & Poor's Stock Reports were the sources for the number of shareholders and total assets of each firm. We collected the number of shareholders one year before and after the split announcement and in the year of the split announcement. Unfortunately, the number of shareholders of a firm is not reported monthly; thus, we could not get these data six months before and after the split. Instead, we collected the number of shareholders at the end of each firm's fiscal year end one year before the split and at the end of each firm's fiscal year end one year after the split. Total asset size was collected for the year before to the split announcement. COMPUSTAT reports fiscal year-end data for both variables, We dropped firms for which we could not get the above data. The final sample contained 527 stock split announcements by 481 firms.

We developed a control sample by matching each stock-split firm with one from the same four-digit Standard Industrial Classification (SIC) code whose total assets were closest to the test firm. These matching criteria are consistent with those used by Lakonishok and Lev (1987). We also followed their approach by choosing total assets over market value of equity because firms often experience large increases in equity values before stock split announcements. The announcement date (month zero) is the same for each test firm and its matched-pair.

Table 1 presents selected summary statistics for the stock split and matched samples. Panel A shows that the mean and median stock split factors were 0.92 and 1.00, respectively (a split factor of 1.0 corresponds to a 2-for-1 stock split). The mean number of institutions owning shares for the stock split and matched samples was 85.8 and 88.0, respectively. The percentage of shares held by institutions was 30.1% and 29.4%, respectively, for the two groups. These data show that the matching process resulted in samples with highly similar characteristics. Panel B shows the distribution of splits by the split factor. Of the 527 splits, 53,9% were 2-for-1 splits and more than 90% were 2-for-1 splits or less. As Panel C shows, most splits (58.1%) occurred in bull market years, namely, 1983, 1986 and 1987.

IV. Empirical Results

To examine the relationship between stock splits and ownership mix, we analyzed the behavior of three variables before and after the stock split announcement: (1) the number of institutions owning shares of the firm announcing the stock split, (2) the percentage of shares held by institutions, and (3) the number of shareholders of the firm announcing the split. Table 2 presents the results of the changes in the institutional ownership variables for the stock split and matched samples. As Panel A shows for the stock split sample, the mean number of institutions owning shares increased 20.7% and the mean percentage of shares held by institutions increased 13.3% in the one-year period around the split. The increases [TABULAR DATA OMITTED] are statistically significant at the 5% and 1% level, respectively. As Panel B shows for the matched sample, the increases in the means of these institutional ownership variables are much smaller (8.1% and 5.1%, respectively) and are not statistically significant at normal levels.

In Panel C of Table 2, we examine the differences in the institutional ownership data between the stock split sample and the matched sample of firms. We find that the difference in the mean number of institutions owning shares between the stock split sample and the matched sample six months before the split is not statistically significant. The difference six months after the stock split is also statistically insignificant. We also find that the difference in the mean percent institutional ownership between the stock split sample and the matched sample six months before the split is not statistically significant. However, six months after the split, the mean percent institutional ownership of the stock split sample is significantly greater than the mean percent institutional ownership of the matched sample.

Drawing any meaningful conclusions from the increase in institutional ownership reported in Table 2 requires further analysis. The chance exists that a stock split announcement could cause shareholders to change their ownership status by taking shares that were personally registered before the split to being held in street name at a brokerage firm after the split. If splits cause investors to change their ownership status from being personally registered to being held in street name, we would expect the second and any successive splits to be followed by reduced changes in recorded institutional ownership. Therefore, we examined the changes in institutional ownership for the 46 firms that had multiple splits during the period under study (no firms that met are screening requirements had more than two splits during the time period of our study). The results are reported in Table 3. Panel A of Table 3 reports the change in institutional ownership for the first split; Panel B reports the change in institutional ownership for the second split by these firms. Panel C reports the differences in the means between the two groups of splits. The results show that multiple splits by a firm result in increases in institutional ownership that do not differ significantly from the increases resulting from their initial splits. Thus, the increases in institutional ownership for the stock split sample reported in Table 2 do not appear to be caused by shareholders simply changing the ownership status of their shares.

Table 4 reports the changes in the mean number of shareholders for the stock split and matched samples. In these tests, the sample size declined from 527 to 480 stock splits due to missing data. For the stock split sample, the mean number of shareholders decreased slightly from 26,320 in the year before the split to 26,259 in the year of the split and increased slightly to 26,317 in the year after the split. The t-statistics for the differences in means do not differ significantly from zero. For the matched sample, the mean number of shareholders decreased from 27,850 to 26,350 to 25,454 over the same period. These decreases are also not statistically significant. In Panel C, we examine the differences in the mean number of shareholders between the stock split sample and the matched sample of firms. We find that none of the differences between the stock split sample and the matched sample is statistically significant at normal levels.

The combined results reported in Tables 2 and 4 refute the conventional wisdom that stock splits broaden a firm's ownership base. Increases in the institutional ownership of firms announcing stock splits are statistically significant but the institutional ownership of the non-splitting firms increased only slightly. This result supports the attention-getting version of the optimal trading range hypothesis. The number of stockholders remains constant for the splitting firms but declines slightly for the non-splitting firms. We find only a relative increase in the number of shareholders for the splitting firms. This result gives limited support for the broader ownership mix hypothesis.

To examine the changes in institutional ownership variables more closely, we ranked the stock split sample by total asset size and then divided the sample into quintiles. The first and fifth quintiles each had 91 firms and the middle quintiles had 90 firms each. Panel A of Table 5 shows the results for the stock split sample. The increases in the mean number of institutions owning shares are statistically significant for the four lower quintiles. The increases in the mean percentage of shares held by institutions are statistically significant for the two lowest quintiles. Panel B of Table 5 gives the results for the matched sample. Firm size, as measured by total assets, has no apparent effect on the changes in institutional ownership. None of the increases in the institutional ownership variables is statistically significant at normal levels.

Table 5 shows that the mean split factor typically increases with total asset size. We divided the stock split sample into four unequal groups based on split factors. We did this to examine whether the split factor, not firm size, produced the changes across quintiles in the institutional ownership variables shown in Table 5. As Table 6 shows, the first group included 43 firms with split factors less than 0.5. The second group included 152 firms with split factors greater than or equal to 0.5 but less than 1.0. The third group 284 firms with split factors equal to 1.0 and the fourth group included 48 firms with split factors greater than 1.0.

The differences in the increases for institutional ownership across the four groups in Table 6 are less pronounced than in Table 5. Only the increases in the mean percentage of shares held by institutions for the two middle groups of split factors are statistically significant at the 5% level. These results suggest that firm size, not the split factor, is primarily responsible for producing changes across quintiles in the institutional ownership variables shown in Table 5.

We repeated the analysis using quintiles for the stock splits. However, the distribution of stock splits renders these tests less conclusive because the mean split factors for the third and fourth quintiles equal 1.0. Although we do not report the results of these tests here, only the increase in percentage of shares held by institutions for the quintile with the smallest split factors is statistically significant at the 5% level.

Next, we ranked the stock split sample by the number of institutions owning shares six months before the stock split and again divided the sample into quintiles. Panel A of Table 7 shows the results for the stock split sample. The increase in the mean number of institutions owning shares is significant for the lowest four quintiles. The increase in the mean percent institutional ownership is significant for the three lowest quintiles. Panel B of Table 7 gives the results for the matched sample. The increase in the mean number of institutions owning shares is significant for the second and third quintiles only. None of the increases in mean percent institutional ownership is significant at the 5% level. These results differ only slightly from the results shown in Tables 5 and 6. To summarize, the results of Tables 5 through 7 show that splitting a firm's stock is associated with an increase in the institutional ownership of that firm's common stock. Also, the increase in institutional ownership is greater for small firms with low institutional ownership before to the split.

We also examined the changes in the number of shareholders before and after the split by dividing the samples into quintiles based on total asset size. Table 8 presents the results. As Panel A shows for the stock split sample, the number of shareholders increased slightly for the four lowest quintiles but decreased slightly for the highest quintile. As Panel B shows for the matched sample, the number of shareholders decreased for each quintile. None of these changes for either group is statistically significant.

[TABULAR DATA OMITTED]

[TABULAR DATA OMITTED]

[TABULAR DATA OMITTED]

[TABULAR DATA OMITTED]
TABLE 9: Cross-Sectional Regression Results: Change in Institutional
Ownership Versus Split Factor and Total Assets

Dependent Variable                Independent Variables

                     INTERCEPT   SPLTFACT   LN TASSETS    [R.sup.2]

PCHCOS                 0.725       0.0202    -0.0567        0.04
                      (9.20)      (0.05)    (-4.44(**))

PCHPIO                 0.426      -0.0376    -0.0329        0.02
                      (5.67)     (-0.80)    (-2.70(**))

*, ** Significant at the 5% and 1% level, respectively.


The results reported in Table 8 suggest that stock splits may increase the number of shareholders, but only for smaller firms. Although the increases in the number of shareholders for the four lowest quintiles of stock split firms are small, these increases accompany small decreases in the number of shareholders for the matched sample. For the lowest quintile, the relative increase was 34.0%. That is, the number of shareholders increased by 27.2% from the year before to the year after the split while the number of shareholders for the lowest quintile of the matched sample decreased 6.8% over the same period.

The increase in the number of shareholders for the lower quintiles (smaller firms) does not represent a broadening of the ownership base of these firms. Results in Table 5 show that both the mean number of institutions owning shares and the mean percentage of shares owned by institutions increased for the lower quintiles. The increased number of shareholders accompanied a more significant increase in the institutional ownership of these firms.

To extend our analysis, we also ran cross-sectional regressions using institutional ownership as the dependent variable and split factor and the natural log of total assets as the independent variables. Since 432 of the 527 stock splits were either 3-for-2 or 2-for-1 stock splits (see Panel B of Table 1 for a complete distribution by split factor), we specified split factor as a dummy variable assigning it a value of 0 for split factors of 0.5 and less and a value of 1 for split factors greater than 0.5.

The regression equations were specified as follows:

[PCHCOS.sub.i] = [a.sub.01] + [b.sub.1i](SPLTFACT) + [B.sub.2i]LN(TASSETS)

[PCHPIO.sub.i] = [a.sub.0i] + [b.sub.1i](SPLTFACT) + [B.sub.2i]LN(TASSETS)

where:

[PCHCOS.sub.i] = percentage increase in the number of institutions owning shares from six months before the split to six months after the split.

[PCHPIO.sub.i] = percentage increase in the percent institutional ownership from six months before the split to six months after the split.

SPLTFACT = dummy variable assigned a value of 0 if the split factor is less than or equal to 0.5 and assigned a value of 1 if the split factor is greater than 0.5.

TASSETS = the total assets of the firm at the end of the fiscal year before the stock split

We estimated the regression equation using a sample of 479 stock splits. We dropped 48 stock splits for two reasons. First, the percentage change in ownership could not be computed (the initial ownership was zero). Second, the change in institutional ownership was more than three standard deviations from the mean change in institutional ownership.

Based on the results reported in Tables 5 and 6, we would expect a negative relationship between both the split factor and total assets variables and the change in institutional ownership. Table 9 provides the regression results. When using the percentage change in the number of institutions owning shares as the dependent variable, the sign of the total assets variable is negative with a significant t-value of -4.44. The sign of the split factor is positive, but is insignificant at the 5% level in explaining changes in institutional ownership. When the percentage change in institutional ownership is used as the dependent variable, the sign of the total assets variable is negative with a significant t-value of -2.70. The sign of the split factor is negative, but is again insignificant at the 5% level.

V. Summary and Conclusions

In this study, we examine the relationship between stock splits and the ownership mix of firms. Our purpose is to learn whether managers use stock splits to broaden the ownership mix (decrease institutional ownership) or to attract attention from Wall Street and thereby increase institutional ownership. Our results show that stock splits accompany increases in institutional ownership for firms. Both the number of institutions owning shares and the percentage of shares owned by institutions increased for the stock split sample. For a control group of non-splitting firms, changes in these institutional ownership variables are not statistically significant. The number of shareholders for both the splitting and non-splitting firms does not change significantly around the split.

Tests on subsamples of firms show an inverse relationship between institutional ownership and total asset size. Also, we report increases in the number of shareholders for smaller firms but decreases for the quintile containing the largest firms. These results support the hypothesis that firms, especially smaller ones, may use stock splits to attract attention from Wall Street. These results also refute the widely held belief that stock splits alter the composition of a firm's stockholders by broadening its ownership mix.

The findings of this study have several implications. First, managers seeking to broaden their ownership mix should use methods other than stock splits. As this study shows, stock splits do not achieve the goals of either attracting more individual investors into the ownership mix of their firm's stock or increasing the number of shareholders. Second, the increase in institutional ownership after stock splits, especially for smaller firms, may reduce information asymmetries between managers and outside investors. As Szewczyk and Tsetsekos (1992a) note, information about a firm is likely to increase with the level of institutional ownership. In turn, pricing efficiency should increase as institutions trade on information uncovered by their own analysts and others making recommendations. Future research is needed to determine whether analyst coverage increases after stock splits.

Endnotes

1. Lamoureux and Poon (1987) offer another hypothesis by arguing that stock splits increase the value of a stock's tax timing option. However, research by Dammon, Dunn, and Spatt (1989) contradicts the tax timing hypothesis. We do not examine this hypothesis in our paper.

References

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Barker, C.A. 1956. Effective Stock Splits. Harvard Business Review 34 (January/February):101-106.

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Brennan, M.J. and P.J. Hughes. 1990. Stock Prices and the Supply of Information. Working Paper, University of California, Los Angeles.

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Ohlson, J.A., and S.H. Penman. 1985. Volatility Increases Subsequent to Stock Splits. Journal of Financial Economics 14 (June):251-266.

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Szewczyk, S.H., and G .P. Tsetsekos. 1992a. "Stock Splits, Institutional Ownership, and the Flow of Information." Working Paper, Drexel University.

Szewczyk, S.H., and G.P. Tsetsekos. 1992b. "Stock Split-Induced Changes in Ownership Structure." Working Paper, Drexel University.

Woolridge, J. R., and D.R. Chambers. 1983. Reverse Splits and Shareholder Wealth." Financial Management 12 (Autumn):5-15.

Gary E. Powell, Department of Economics and Management, Hood College, Frederick, MD 21701-9988 (301) 696-3688

H. Kent Baker, Department of Finance and Real Estate, Kogod College of Business Administration, The American University, Washington, D.C. 20016-8044 (202) 885-1949
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Date:Mar 22, 1994
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