Conclusions

A ‘good market’ can provide investors with greater investment choices, and thereby succeed in attracting more investors to become involved in the financial market. In reality, many exchanges will do their utmost to induce greater numbers of firms to list on their exchanges. From the examination in this chapter of 208 IPO firms listed on the Taiwan Stock Exchange between 1995 and 2003, we find that all firms improve their investor base, and almost a half of the firms experience an increase in the total number of investors from the first to the second 252-day period after the initial listing.

On average, the increase is greater for new investors than old investors. Of the 208 IPO firms examined, 61.5 percent saw increases in new investors, while only 39.4 percent saw increases in old investors. The results also show that the rate of increase in investors has a positive correlation with holding period excess returns (HPERs), which goes some way to explaining why both firms and stock exchanges generally share a desire to see improvements in the overall numbers of investors. In addition to studying the increase in the total number of investors, the evolution of the investor base is also analyzed in this chapter.

The results provide that investors have a tendency to sell off their winning stocks and hold on to their losers; that is, the high stability group of investors (those investors who remained as net buys in periods 1 and 2) is associated with lower HPERs.

Conversely, the group with a high rate of change, from net buy to net sell investors, exhibits significantly higher HPERs. Finally, those who were previously net sell or net zero investors, and subsequently became net buy investors, have an association with significantly positive HPERs.

We can therefore conclude that investors, particularly new investors, have a preference for holding IPO stocks with higher return volatility, while a similar result is discernible for the relative book-to-market ratio. As expected, this suggests that stock exchanges should aim to encourage the listing of those firms with better performance, higher return volatility and growth.

Table 2.7 Regression results of the evolution of the investor base on firm characteristics

The table reports the results of the multiple regressions on the evolution of the investor base on firm characteristics. Period 1 (2) refers to the portfolio position for investors in the first (second) period. New (Old) refers to changes in the new (old) investor base; investors are defined as New if they had never traded during the three-year period prior to the IPO launch, and then began trading in the IPO; otherwise they are defined as Old. There are three types of investors based on the investors’ portfolio position, which is equal to buys minus sells for each investor. Net Buy (Net Sell) indicates that investors are holding positive (negative) portfolios after netting the buys by the sells. If an investor has a zero portfolio at any specific time, he has sold out his inventory and his position is Net Zero. rbm and rcap are the respective book-to-market and market capitalization to market at the 252^nd day after listing; ratiostd and rsturn represent the standard deviation in the standardized return and the turnover rate, respectively; hot252 is a dummy variable which is equal to 1 if the market price is above the 1995-2005 median value at the 252^nd day after listing; HPERs refers to the holding period excess returns between the 253^rd and 504^th day (about one year) after listing. T-statistics (not shown in the table) use heteroskedasticity-consistent standard errors. * indicates significance at the 10% level; ** indicates significance at the 5% level; and *** indicates significance at the 1% level.

Panel Period 1 Position Period 2

Position Intercept rbm Beta ratiostd rcap rsturn hot252 HPERs Adj.R²

(%)

Net Buy Net Buy 0.2415 *** -0.0357 *** 0.1150 ** 0.0643 * -1.6822 -0.0150 0.0289 -0.0373 13.7 New Net Buy Net Buy 0.0083 -0.0030 * 0.0186 *** 0.0039 0.2225 -0.0019 0.0252 *** -0.0032 26.5 A

Old Net Buy Net Buy 0.2332 *** -0.0327 *** 0.0964 ** 0.0604 * -1.9046 -0.0132 0.0036 -0.0341 13.1 Net Sell Net Buy 0.0011 -0.0010 0.0030 0.0008 0.1051 0.0009 * 0.0026 ** 0.0023 ** 16.4 New Net Sell Net Buy 0.0004 -0.0001 ** 0.0004 0.0000 0.0079 0.0000 0.0003 ** 0.0002 * 12.1 B

Old Net Sell Net Buy 0.0007 -0.0009 0.0027 0.0008 0.0973 0.0009 * 0.0023 * 0.0021 ** 16.5 Net Zero Net Buy 0.2938 *** -0.0244 * 0.0642 -0.0847 ** -2.7429 0.0405 *** 0.0174 0.0611 ** 17.5 New Net Zero Net Buy 0.0129 * -0.0037 ** 0.0059 -0.0015 0.1755 0.0035 ** 0.0193 *** 0.0065 ** 23.8 C

Old Net Zero Net Buy 0.2809 *** -0.0208 * 0.0583 -0.0833 *** -2.9184 0.0370 *** -0.0019 0.0547 ** 16.9 Net Buy Net Sell 0.0020 0.0004 -0.0036 ** 0.0023 ** 0.0791 0.0002 -0.0005 0.0016 ** 9.1 New Net Buy Net Sell 0.0006 ** 0.0000 -0.0006 ** 0.0003 0.0021 0.0000 0.0000 0.0002 * 6.1 D

Old Net Buy Net Sell 0.0014 0.0004 -0.0030 ** 0.0020 ** 0.0770 0.0002 -0.0006 0.0014 * 9.2 Net Zero Net Sell 0.0010 ** 0.0001 -0.0005 0.0002 0.0416 * 0.0001 -0.0001 0.0004 * 5.5 New Net Zero Net Sell 0.0002 ** 0.0000 0.0000 0.0000 -0.0009 0.0000 0.0000 0.0001 ** 2.6 E

Old Net Zero Net Sell 0.0008 * 0.0001 -0.0006 0.0002 0.0425 ** 0.0001 -0.0001 0.0004 * 6.0

Chapter 3 The Impact of Investors on the Cost of Capital in Initial Public Offerings

_______________________________________________________________________

1. Introduction

There are a number of studies within the extant literature in which attempts are made to explain the factors motivating initial public offerings (IPOs).¹¹ It is essentially argued in such studies that the attraction of IPOs is their ability to effectively establish the market price or value of a firm (Zingales, 1995; Mello and Parsons, 2000) while also allowing entrepreneurs to use share prices to infer the valuation of their firms by investors.¹²

Thus, IPOs can raise the overall level of publicity for a firm, thereby potentially enhancing its reputation (Maksimovic and Pichler, 2001). Furthermore, when an IPO has a higher level of disclosure (Diamond and Verrecchia, 1991; Kim and Verrecchia, 1991, 1994) or is targeted for more comprehensive coverage by analysts (Bradley, Jordan and Ritter, 2008), this can also increase the shareholder base of a firm (Mittoo, 1992; Fanto and Karmel, 1997), thereby raising the level of liquidity in a firm’s stocks, while also minimizing the costs of capital (Lins, Strickland and Zenner, 2005).¹³

Based upon a model of capital market equilibrium with incomplete information, an investor recognition hypothesis was formally developed by Merton in 1987; the model, which is essentially an extension of the Shape-Lintner ‘capital asset pricing model’

(CAPM), relaxes the assumption of equality of information for investors. The suggestion is, therefore, that such investors will invest only in those securities with regard to which they have some prior knowledge. This ultimately results in the imperfect diversification of risk, which leads to a higher risk premium being required of investors.

According to the Merton model, all other things being equal, an increase in the total number of investors who are aware of a firm – which Merton refers to as the

‘degree of investor recognition’ – will ultimately lower the expected returns of investors by reducing the ‘shadow cost’ arising from the lack of knowledge on a particular security, and will thereby increase the market value of the firm’s shares. The end result is that managers may choose to go public to reduce this shadow cost.

11 Examples include the analyses by Mittoo (1992) and Fanto and Karmel (1997) on managers and by Brau and Fawcett (2006) on chief financial officers.

12 Leland and Pyle (1977), Benveniste and Spindt (1989), Dow and Gorton (1997), Subrahmanyam and Titman (1999), Habib and Ljungqvist (2001), Maug (2001) and Benninga, Helmantelc and Sarig (2005) all suggest that given their greater diversification, outside investors are willing to pay higher prices for the risky cash flows of firms than the entrepreneurs’ own valuations of such cash flows.

13 Amihud and Mendelson (1988), Holmström and Tirole (1993) and Bolton and Von Thadden (1998) suggest that IPOs lead to the greater liquidity of a firm’s shares, which also increases the firm’s value.

Consistent with Merton (1987), several of the prior studies use the reducing cost of capital for international cross-listing as an important example, identifying an increase in the number of shareholders after cross-listing which they also associate with lower returns.¹⁴ Using visibility as a proxy for the number of investors with awareness of a particular stock, Baker, Nofsinger and Weaver (2002) note that the increase in the stock price at the time of the announcement of a firm’s cross-listing on the NYSE or LSE is negatively correlated to the shadow cost of incomplete information. From their study of the Asian markets, Amihud, Mendelson and Uno (1999) also note that for reduced minimum trading units in the Japanese equity market, lower returns are associated with an increase in the total number of shareholders.

This chapter examines the Merton (1987) ‘investor recognition hypothesis’ using the total number of traders as a proxy for the overall number of investors with awareness of a particular IPO. This measure may be an appropriate alternative proxy for investor recognition, essentially because the use of the number of shareholders in a company at the fiscal year-end cannot avoid temporal measurement bias;¹⁵ clearly, the size of the investor base is a static measure, whereas the number of traders is a flow variable which can reflect the investor base whichever investors exist within a firm.

Baker et al. (2002) use the number of analysts’ reports and number of citations of a firm in the Wall Street Journal (WSJ) or the Financial Times (FT) to represent awareness among investors of any given firm, under the assumption that information which is important to investors is obtained from such analyst reports or business newspapers.¹⁶ However, while such sources may well provide important information for investors, it is nevertheless clear that the number of times a firm is reported may not entirely equate to the number of investors with awareness of that firm. If an investor does not follow any particular firm, then any amount of analyst report coverage or news coverage on the firm is unlikely to lead to that investor taking up a position in the firm’s stocks.

The intuition behind the alternative measure proposed in this chapter is quite straightforward. The number of traders represents the number of investors who actually trade in a stock, irrespective of whether or not they are current shareholders in that particular firm; thus, when an investor does decide to trade in the stock, we would naturally expect to find that the investor already has some prior knowledge of that

14 Kadlec and McConnell (1994), Forster and Karolyi (1999) and Tse and Devos (2004).

15 The TEJ database provides a dataset of shareholders for all firms for each sample year. However, as noted in the TEJ documentation, some firms do not include the number of shareholder in the central depository; thus, it may be that changes in the investor base are not due to changes in shareholders.

16 The SRI International (1987) survey results suggest that analyst reports provide the necessary information on firms with regard to buy-side investors, while Marcus and Wallace (1991) and Walther (1997) also note that investors use such analyst reports as their primary source of information on firms.

Bailey, Chung and Kang (1999) use the number of times a firm is cited in newspapers as a proxy for the information driving the demand for its shares.

particular firm. It is suggested that investors will often have a tendency to concentrate their holdings in certain stocks to which they have some professional affinity or geographical proximity, or in stocks which they may have held for some considerable period of time (Massa and Simonov, 2006). Furthermore, according to ‘familiarity’ theory, although an investor may sell out his inventory of stocks, given that he is familiar with a particular firm, there is also a high probability of the investor holding on to that stock.

Firms going public on the stock market for the first time do so by arranging an IPO, usually with the support of an investment bank. Such firms are often younger and less well known than many existing firms, although some firms going public may well have been established for many years. In his 1987 model, Merton postulates that an increase in the relative size of the firm’s investor base will reduce its cost of capital, noting that the magnitude of the effect will be greatest for lesser-known firms and for those firms with greater firm-specific variances (Merton, 1987: 500). It should, therefore, be of some considerable interest to undertake a study of the impact of firms engaging in IPOs on the Merton (1987) investor recognition hypothesis.

In contrast to the stocks of firms which engage in cross-listing, the stocks of firms engaging in IPOs continue to be traded within the same environment and under the same trading mechanism; that is, there is no change in the overall market microstructure. The Taiwan stock market provides an appropriate trading environment for an examination of the Merton (1987) proposition, that an increase in the firms’

investor base will reduce its cost of capital. Using a unique transaction dataset, we can accurately categorize investors into the two specific groups of individual and institutional investors to facilitate our examination of the different effects of investor recognition. We know, for example, that between 1995 and 2003, individual investors in Taiwan accounted for about 77 to 90 percent of all trading volume.

Since no transaction data is available on a firm prior to its IPO launch, we divide the post-IPO period into two sub-periods, referred to in this chapter as the first and second periods (or period 1 and period 2) to measure the effects of the costs of capital on investor recognition. The first period comprises of all trading days from the first day of the IPO listing to the 252^nd trading day after the listing, while the second period comprises of all trading days from the 253^rd day after the IPO listing until the 504^th day after the listing.

The results of the examination of the Merton proposition show that the full sample of firms is associated with a rise of 3,508 in the total number of traders (an average increase of 9.98 percent), although this is not significant; this insignificant increase is also diminished by positive increases in firms in the electronics industry and by negative decreases in firms in the non-electronics industries, both of which are significant at the 5 percent level. For both the full sample and the industry sub-samples,

a significant decline is discernible in the number of institutional traders; thus, the results of this study show that not all firms provide support for an association between IPOs and increased investor base. Indeed, it is only in the electronics industry that there is any significant increase in the awareness of any particular firm among investors.

We also examine the reduction in the costs of equity capital associated with listing using the ‘market model’ to compute abnormal returns, and find that the average daily abnormal return in the first (second) period is 0.045 percent (0.015 percent).

Similar to this pattern, the average abnormal return for the first (second) period is 0.027 percent (^–0.01 percent) for firms in the non-electronics industries and 0.061 percent (0.026 percent) for firms in the electronics industry. Finally, we test the Merton (1987) investor recognition hypothesis by regressing the firms’ average abnormal returns against changes in the overall numbers of traders. The results confirm the association between investor recognition and the costs of capital.

The remainder of this chapter is organized as follows. The next section provides details of the hypotheses proposed in this chapter. Section 3 presents a discussion of the data and research methodology, followed in Section 4 by the reporting of the main empirical results, as well as tests for increased trading and the costs of capital for IPO firms. The conclusions drawn in this chapter are presented in Section 5.

2. The Merton (1987) Investor Recognition Hypothesis

The Merton (1987) investor recognition hypothesis postulates that investors are not endowed with equal information; hence they will invest only in securities with regard to which they have some prior knowledge. Under this assumption, Merton shows that expected returns are dependent upon factors other than simply market risk.

For an individual security, this introduces the shadow cost of incomplete information for a security i, which is given as:

i

where

δ is the coefficient of aggregate risk aversion; σ

_i² is the firm-specific component of the stock’s return variance; x_i is the market value of the firm relative to the market value of traded securities; and q_i is the proportion of all investors with prior knowledge of security i.

Merton demonstrates that the relationship between the actual expected excess returns for the stock, E(R_i), and the expected excess returns for the case of complete information (where q_iis equal to 1), E(R_i^*), is:

0

In reality, it is impossible for all market participants to be aware of a firm (q_i< 1);

thus, firm-specific risk is priced. Based upon the above equation, we would expect to see a general decline in returns, with the magnitude of the effect being greater for lesser-known firms (with small q_i ) and for firms with large firm-specific variances.

One of the primary motivating factors for IPO firms to go public is the desire to expand their firm’s investor base. Furthermore, such firms engaging in IPOs are generally smaller than firms which already exist within the market. We would therefore expect to see the effect of the reduction in the shadow cost for IPOs being associated with an increase in the number of traders.

Following Kadlec and McConnell (1994), Foerster and Karolyi (1999) and Baker et al. (2002), we can construct an empirical proxy for the change in the shadow cost of incomplete information, as follows:

where

σ

_ei² is the residual variance from the market model regression given by Equation (1); SIZE_i is the relative market capitalization of the firm relative to level of TAIEX at the time; and Traders^P1 and Traders^P2 are the first- and second-period proxies for the number of investors with awareness of the firm.

Several of the prior studies have used the total number of shareholders or visibility as the proxy for such awareness by investors.¹⁷ However, in this study on IPO firms, real traders should of course already have some awareness of the firms in which they are investing, regardless of whether they are net buyers, net sellers or net zero. Welch (1992) notes that potential investors focus not only on their personal information relating to a new issue, but also on whether other investors are purchasing the issue, since it is clear that traders in any particular stock should have some prior knowledge of the firm. Thus, the use of the number of traders as the proxy may well represent a more precise measure for the knowledge of the firm possessed by investors than the use of visibility.

17 Kadlec and McConnell (1994) and Foerster and Karolyi (1999) use the number of shareholders as a proxy for the number of investors with awareness of the firm, while Baker et al. (2002) employ two measures of visibility which can represent the extent of investors’ knowledge about the firms; these are: (i) the number of analysts estimating the firm’s annual earnings; and (ii) the number of citations a firm receives in an article title or leading paragraph appearing in the Wall Street Journal (WSJ) or the Financial Times (FT).

According to the Merton (1987) hypothesis, the abnormal returns experienced by firms during the first and second periods may be due to changes in the investor base, adjusted by the stock’s residual variance and relative size. Using our unique database on trading records, we can compute the total number of traders during the first period, as well as the increment in traders during the second period. Therefore, following Kadlec and McConnell (1994), Foerster and Karolyi (1999), and Baker et al. (2002), we perform the following cross-sectional regressions:

it i

i

= γ + r Δ λ + e

α

_{0 1} (5) where

α

_i refers to the first- or second-period daily abnormal returns from Equation (1). The variable ∆λ_i is the change in the shadow cost of incomplete information; assuming that it is negative for firms with an increase in traders, we would expect to see γ_i being significant and negative in the cross-sectional regressions.

Other factors such as relative market capitalization and relative book-to-market ratio are also controlled for in the regressions.

3. Data and Methodology

The initial sample of IPOs in the TSE comprises of data on 238 firms covering the period from 1995 to 2003. The sample and listing dates are obtained directly from the Taiwan Economic Journal (TEJ) and verified by annual Taiwan Stock Exchange Corporation (TSEC) statistical data. A total of 28 financial firms were excluded from the sample (comprising of banks, savings and loans companies, insurance companies,

The initial sample of IPOs in the TSE comprises of data on 238 firms covering the period from 1995 to 2003. The sample and listing dates are obtained directly from the Taiwan Economic Journal (TEJ) and verified by annual Taiwan Stock Exchange Corporation (TSEC) statistical data. A total of 28 financial firms were excluded from the sample (comprising of banks, savings and loans companies, insurance companies,

在文檔中 Complementarity and Substitutability of IPOs (頁 32-53)