現金增資的模仿行為 - 政大學術集成

全文

(1)國立政治大學財務管理研究所碩士論文. 立. 政治大. ‧ 國. 學. Mimicking Seasoned Equity Offerings. ‧. n. er. io. sit. y. Nat. al. Ch. engchi. i Un. v. 指導教授：周冠男博士研究生：蔡宜均撰. 中華民國一百零三年六月.

(2) 謝辭致，總是細雨綿綿迷霧的木柵。本篇論文得以付梓，首先感謝指導教授周冠男老師一路上的殷殷教導，老師出國進修本可好好休息的，但卻每兩個禮拜就必須與我們一次 meeting 的鬧騰，真的感謝老師。感謝岳夢蘭老師，在我無盡徬徨不安的日子裡，總是用柔柔淡淡卻堅毅的神情給我建議，鼓勵與肯定，謝謝老師讓我深信，不用在意旁人目光，這是妳自己的路，也是一條很難走的路，但不會永遠都是無盡黑夜。. 政治大明明知道我什麼都不會，卻放手讓我自己去嘗試，嘗試失誤、嘗試跌倒，我才會立. 感謝臺北大學金融與合作經營學系的施懿宸老師，謝謝老師一直以來獨立的教育，. ‧ 國. 學. 深刻的記得，路該怎麼走。. 謝謝子淇與伊菁，讓我願意再相信，仍然有超越自利的真摯友情；謝謝同門的詩. ‧. 婷、慧慈與茹蘋，那些我們一同走過的，每次 meeting 前的崩潰，資料處理上的. sit. y. Nat. 解決，都將成為，多年後談笑風生的雲淡風輕。. n. al. er. io. 謝謝欣恩，姊姊到底存著私心把妳帶來遙遠的木柵，謝謝妳的善良與篤定，靜靜. i Un. v. 地不厭其煩地聽著我絮絮叨叨地訴說人後的沮喪與不完美。. Ch. engchi. 謝謝一路陪伴的碩班同學們，我們的苦中作樂，還有，研究室裡的歡笑或愁苦。謝謝二十四個年頭，偶爾刮著風沙跌撞的路途上，適時出現的小精靈們，雖然偶爾看見朱門、看見勝利，膚淺浮動的心仍會欽羨，但到底是得天獨厚的，縱使踉蹌，但是沿路微弱的光，總是會帶領我，一步一步，走得尚且穩妥。最後，最感謝始終支持我的父母與摯愛家人，謝謝你們，最直接的溫暖與相信。蔡宜均謹誌於臺北木柵 2014.06.24. I.

(3) Abstracts This study aims to investigate the seasoned equity offerings (SEOs) announcements result from intra-industry wave. Bradley and Yuan (2013) examine the information spillovers to rival firms and provide evidence of industry contagion effect. Using data for seasoned equity offerings from 1990 to 2010 period, our result supports seasoned equity offerings experience lower negative abnormal returns during the SEO industry wave, which is consistent with market timing hypothesis. To understand the extent. 政治大 that the SEO negative returns announcements within industries, we further study the 立. ‧ 國. 學. strategic interaction between intra-industry wave and concentration. We expect that,. ‧. industry concentration will bring the intra-industry effect. Consistent with Ali (2012),. sit. y. Nat. the results support that firms are likely to mimic their competitors conducting. n. al. er. io. seasoned equity offerings in less concentrated industry. As previous papers. Ch. i Un. v. demonstrate the negative day returns on seasoned equity offerings due to pecking. engchi. order theory and poor investment opportunities prospect. Our findings provide a new way that there exists the intra-industry wave on SEO decisions and strategic interaction within the industry enhances the mimicking behavior effect.. Key Words：Seasoned Equity Offerings (SEOs), mimicking, market timing. II.

(4) CONTNENTS I.. Introduction ............................................................................................................ 1. II.. Literature Review .................................................................................................. 4. III. Hypotheses ............................................................................................................. 8 A. B.. Market Timing Considerations for SEOs ....................................................... 8 Measures of product market concentration and strategic interaction ............ 8. IV. Data and Methodology......................................................................................... 11 Data selection ............................................................................................... 11. B. C.. Variables selections ...................................................................................... 12 Market reactions........................................................................................... 14. 政治大 Results of Multiple Regressions .................................................................. 19 立 Robustness tests ........................................................................................... 20. Empirical results .................................................................................................. 19 A. B.. 學. ‧ 國. V.. A.. VI. Conclusion ........................................................................................................... 27. ‧. n. er. io. sit. y. Nat. al. Ch. engchi. III. i Un. v.

(5) List of Tables Table 1 Number of seasoned equity offerings (SEOs) by year .................................... 16 Table 2 Univariate tests for analyzing the sample using changes in operating performance measures ......................................................................................... 17 Table 3 Market reaction to SEO announcement .......................................................... 18 Table 4 Distribution of Offering by Industry ............................................................... 22 Table 5 Results of Multiple Regressions in the same three-digit SIC code industry ... 23 Table 6 Robust tests in Fama and French industry classification ................................ 25. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. I. i Un. v.

(6) I. Introduction In this study, we argue that there still exists intra-industry mimicking wave on SEO announcements. We construct this mimicking behavior under the market timing hypothesis. Firms observe their counterparts to begin raise capital and consider there is during industry SEO wave. They may worry that if they announce equity issue too late, lack capital they will receive. Following Massa et al. (2007), we build the. 政治大 industry wave term to measure the mimicking behavior on SEO announcements, 立. ‧ 國. 學. computing the intra-industry wave is the sum of the number of SEOs announcements,. ‧. excluding those of the firm in question, that occur in the same three-digit SIC code. sit. y. Nat. industry for all the other firms in the previous six months. In sum, we aim to test the. n. al. er. io. mimicking behavior within industry and whether they influence on seasoned equity offerings.. Ch. engchi. i Un. v. As previous literature reports, industry concentration has impact on strategic interaction between counterparts. As the result, we argue that the mimicking behavior on SEO announcements is stronger under the industry concentration. We define the Conc/SEOs term to measure the interaction between industry wave and concentration, which is a proxy to measure the effect on the probability of a SEO announcement resulting from an increase in both the concentration of the industry and the intensity. 1.

(7) of the SEOs intra-industry activity. We focus on the Conc/SEOs interaction defined as the product of SEO industry wave and concentration. If the industry SEO wave in the particular industry wave is greater (small) than the median, the industry is classified as high-wave (low-wave). As our measure of concentration, we use the Herfindahl Index constructed at the three-digit SIC classification level. SEO samples in high (low) concentration are identified by sorting all the SEO samples within each fiscal year on. 政治大. this concentration dummy. Our methodologies have been recently developed and used. 立. extensively in the literature (Massa et al., 2007; Bradley et al., 2013). Ali et al. (2012). ‧ 國. 學. show that more concentrated firms prefer private placements when they raise funds,. ‧. which have minimal SEC-mandated disclosure requirements, over seasoned equity. y. Nat. er. io. sit. offerings. Therefore, we expect that firms in more concentrated industries are reluctant to conduct SEOs to send signal to their counterparts. Firms in less. al. n. iv n C U h e nlower concentrated industries will experience returns by catching the h i negative g cSEO industry wave.. Our results provide two new ways on SEO announcements. First, firms are inclined to follow their industry peers to conduct SEOs during the industry SEO wave, those during the higher SEO industry wave experience lower negative returns, which is consistent with market timing hypothesis. The other finding report that there exist the strategic interaction between industry wave and concentration. The mimicking 2.

(8) behavior is much more easily observed in less concentrated industries. The reminder of this study is as follows. In Section 2, we review the related literature. Data and methodology will be described in Section 3, we study the methodology to investigate the mimicking behavior and industry concentration affecting the SEOs announcements. In Section 4, we provide the hypotheses. Section 5 analyze the empirical evidence of the impact and Section 6, a brief conclusion and future research also be suggested.. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. 3. i Un. v.

(9) II. Literature Review SEO decisions have been intensively studied in previous literature. The most common explanation for negative returns on SEO announcements is pecking order theory. Since a firm‟s motive for capital need is often unobservable to investors, managers are considered insiders to have privilege information. Therefore, equity issue is regarded as a last resort of financing decision (Myers and Majluf, 1984).. 政治大. However, DeAngelo et al. (2010) claim that pecking order theory is problematic. 立. ‧ 國. 學. because it predicts that firms do not sell stock when they have untapped debt capacity, yet SEOs typically follow share price run-ups, which imply increased future cash. ‧. flows that could be used to support additional debt. Given the shortcomings of. sit. y. Nat. io. n. al. er. pecking order theory, market timing has become the most prominent theoretical. i Un. v. explanation for SEOs. Only overvalued firms have a motivation to do equity issue. Ch. engchi. (Asquith and Mullins, 1986; Masulis and Korwar, 1986). Clarke et al. (2004) construct the hypothesis that the negative performance of secondary equity offerings can be attributed to managers exploiting "windows of opportunity" by issuing overvalued shares. Ibbotson and Jaffe (1975) define that IPO hot issue markets are the periods in which the average first month performance (or aftermarket performance) of new issues is abnormally high. Hot issues refer the market exists the particular issue, which affects the stock price higher than average premiums in the aftermarket. Ritter 4.

(10) (1984) tests the initial price offerings (IPO) of common stock overvalued. There have had extremely high returns during particular periods. It refers to market timing on IPOs. With its intuitive and plausible view that managers attempt to sell highly priced shares when stock market conditions permit (Loughran and Ritter,1995,1997; Baker and Wurgler, 2002). Although market timing appears to provide a statistically significance on the. 政治大. decision to conduct an SEO, the literature contains no evidence on its economic. 立. significance. Bradley and Yuan (2013) find that information spillovers exist within. ‧ 國. 學. industries. Primary equity offerings send a favorable signal because firms presumably. ‧. issue new shares to invest in profitable projects. The rival response is also positively. y. Nat. er. io. sit. related due to the intra-industry spillover effect, which is the evidence of industry contagion effect. We try to follow them to examine the industry SEO wave do exists. n. al. C in different industry classification. h. engchi. i Un. v. Existing research have documented information spillovers in various areas such as bankruptcies. Lang and Stulz (1992) investigate the effect of bankruptcy announcements on the equity value of the bankrupt firm's competitors. Bankruptcy announcements bring rival firms a negative signal and decrease the competitors‟ value-weighted portfolio by 1%. Jorion and Zhang (2007) examine the information spillovers of credit events. They find strong evidence of the intra-industry information 5.

(11) transfer effects for Chapter 11 bankruptcies. Boone and Ivanov (2012) find that the non-bankrupt strategic alliance partners, on average, experience a negative stock price reaction around their partner firm's bankruptcy filing announcement. Beveniste et al. (2002) contend that there is clustering effects of IPOs through time and within industries. Burns and Liebenberg (2011) investigate the effect that U.S. acquisitions of targets in emerging and developed countries have on the targets' rivals. They provide. 政治大. evidence of information spillovers in cross-border M&A activities. Song and Walkling. 立. (2000) develop and test the Acquisition Probability Hypothesis and report that rival. ‧ 國. 學. firms earn positive abnormal returns regardless of the form and outcome of. ‧. acquisition. Funke et al. (2008) investigate the long run performance of rival. y. Nat. er. io. sit. companies related to acquisition targets. They indicate that capital market do not immediately respond the information contained in M&A announcements. Shahrur and. n. al. Venkateswaran (2009) find. iv n C that hrivals e n gthat c harei Umost similar. to the acquirer. (homogeneous rivals) experience significant negative cumulative abnormal returns (CAR) around takeover announcements. Erwin and Miller (1998) support that firms announcing open market share repurchase programs experience a significantly positive stock price reaction at announcement, whereas portfolios of rival firms in the same industry experience a significant and contemporaneous negative stock price reaction. Rajan (1994) lead to a theory of low frequency business cycles driven by 6.

(12) bank credit policies. Rational bank managers with short horizons will set credit policies that influence and are influenced by other banks and demand side conditions. These studies indicate that rival firms will be affected by their industry peers. The findings lead credence that strategic interaction does cause an effect in their rival firms. As Demsetz (1973), Dasgupta et al. (1980), Shaked (1987) and Sutton (1991) report, a firm in a more concentrated industry runs a greater risk of revealing. 政治大. company secrets through its disclosures. Therefore, we expect that firms in less. 立. concentrated industries are easily observe their counterparts to conduct SEOs and. ‧ 國. 學. decide to mimic to catching the industry SEO wave. That‟s, strategic interaction. ‧. within industry enhances the SEO industry wave.. n. er. io. sit. y. Nat. al. Ch. engchi. 7. i Un. v.

(13) III. Hypotheses A. Market Timing Considerations for SEOs In this section we lay out our studies by market timing hypothesis, which argues that managers exploit windows of opportunity to sell overvalued stock (Myers and Majluf, 1984; Clarke, Dunbar, and Kahle's 2004). To test the relative impact on the SEO decision of market timing, we examine the abnormal returns by the degree of. 政治大. industry wave. We argue that, firms will mimic their industry peers only in the market. 立. prospect well. The market timing implies the industry condition is permit (Loughran. ‧ 國. 學. and Ritter, 1995; Baker and Wurgler, 2000). Firms will observe their counterparts to. ‧. conduct SEO announcements and consider it is during SEO industry wave and make a. y. Nat. al. er. io. sit. decision to mimic in the following six months. If firms make SEO announcements by. v. n. learning within the industry competitors, they will catch the timing of industry wave. Ch. engchi. i Un. and experience lower negative SEO announcement returns. We develop it as follows,. H1：The returns of SEO announcements will be less negative during the relatively high industry SEO wave.. B. Measures of product market concentration and strategic interaction As previous paper supports, concentration has an impact on industry strategic interaction. Ali et al. (2012) reflect that firms in more concentrated industry prefer 8.

(14) private placements, which have minimal SEC-mandated disclosure requirements, over seasoned equity offerings. Gomes and Philips (2007) mention that firms with greater information asymmetry are more likely to sell new shares via a private placement rather than through seasoned equity offerings. Bamber and Cheon (1998) argue that proprietary costs of disclosure are higher in more concentrated industries. Harris (1998) argues that firms in more concentrated industries are less competitive and. 政治大. firms in such industries disclose less to protect their abnormal profits. That‟s, we. 立. presume that firms in less concentrated industry have more motivation to learn from. ‧ 國. 學. their industry peers, firms in less concentrated industries are more likely to conduct a. ‧. SEO since industry is competitive. We conjecture that a less pronounced negative. y. Nat. er. io. sit. share price reaction in less concentrated industries. Our proxy measure for the degree of industry concentration is based on the Herfindahl Index. It is measured as the sum. al. n. iv n C of the squares of market shares ofhallethe n gfirms c hini theUparticular industry for a fiscal year. We therefore propose the following hypothesis. H2：The returns of SEO announcements should be more correlated among less concentrated industry than among more concentrated industry.. According to Ali et al. (2012), firms in less concentrated industries have more incentive to conduct seasoned equity offerings. That‟s, we further presume that firms in less concentrated industry will conduct SEO during the industry wave to catch 9.

(15) market timing. Erwin and Miller (1998) show that rival firms experience significant negative stock price reactions on the day of a firm‟s repurchase announcements if the industry is concentrated. This implies： H3：The SEO industry wave is stronger when strategic interaction exists.. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. 10. i Un. v.

(16) IV. Data and Methodology. A. Data selection The time period for this study ranges from 1990 to 2010. The Securities Data Corporation (SDC) Global New Issues Database dedicates the announcement of seasoned equity offerings.. 政治大. For they must be the sample criteria：. 立. (a) The issuer's stock must be listed on the New York Stock Exchange (NYSE),. ‧ 國. 學. American Stock Exchange (Amex), or Nasdaq, and be presented on the. ‧. University of Chicago Center for Research in Security Prices (CRSP) database. y. Nat. er. io. sit. for stock price and Compustat for accounting related data.. (b) In line with Loughran and Ritter (1995), only the first filing date of the. al. n. iv n C retained h inethe n gsample. c h i InUother words,. same fiscal year is. if a firm issues. multiple SEOs within the fiscal year, we keep only the first filing date in our sample. Subsequent issues are dropped. This is consistent with the regulation of U.S. Securities and Exchange Commission as well. There are a few safe harbors that offer some level of comfort by assuring non-integration of certain exempt offerings separated by at least six months from another offering.1. 1. Securities Act Regulation D [17 C.F.R.230.502]; Securities Act Rule 147 [17 C.F.R.] 11.

(17) (c) SEO firms should be a non-financial, non-utility firm. Financials and utilities are removed since these firms‟ incentive to issue equity (for example, banks may issue equity to meet regulatory capital requirements) as well as the applicability of multiple based valuations to these firms are not comparable to other firms. American Depository Receipts (ADRs), private placements, rights offers, unit offers, closed-end funds, Real Estate Investment Trusts (REITs) are excluded as well.. 立. 政治大. The original raw data contains 13,247 samples from SDC. We exclude 148 offers. ‧ 國. 學. with lack of filing date and 1,709 samples with minor exchanges. 3,604 financial. ‧. services firms and utilities samples are excluded as well. Lastly, we drop 2,152 offers. Nat. er. io. sit. y. that occur within a year of the same firm‟s seasoned issue, which results in a final sample of 5,634 seasoned equity offers.. al. n. iv n C U The sample is observed in hen Table 1 outlines our final sample of SEOshby g c i year.. 1996 with highest frequency of 490 firms and the lowest in 1990, which has 89 observations.. B. Variables selections To start with, we construct the INDSEOWAVE term to measure the industry intensity of SEO activity. The INDSEOWAVE is computed from SDC data, and it is 12.

(18) the sum of the number of SEOs announcements, excluding those of the firm in question, that occur in the same three-digit SIC code industry for all the other firms in the previous six months. The wave term is commonly documented in M&A and equity activity ( See Massa et al., 2007; Bradley and Yuan , 2013). All of SEO samples are ranked in terms of concentration, they are classified in high (low) concentration industries are identified by sorting all the SEO samples within industries each year.. 立. 政治大. We capture the Conc/SEOs interaction term to investigate the strategic. ‧ 國. 學. interaction between industry wave and concentration. The SEOs term is brought by. ‧. the INDSEOWAVE as mentioned before. This Conc/SEOs interaction is a proxy to. y. Nat. er. io. sit. measure the effect on the probability of a SEO announcement resulting from an increase in both the concentration of the industry and the intensity of the SEOs. n. al. intra-industry activity.. Ch. engchi. i Un. v. The CRSP-Compustat Database is dedicated for all the accounting variables that have been used as controls. We choose the Herfindahl-Hirschman Index as our measure of concentration, which is the sum of the squared fraction of industry sales by all firms in the 3-digit SIC code for the year prior to the announcement. The Herfindahl index scores rank is expected to be negative. This indicates that firms in less concentrated industries outperform than those in more concentrated industries. 13.

(19) Following Clarke and Kahle (2004), RUNUP defines the issuer‟s buy-and-hold return over the year prior to the issue. ROA is earnings divided by total assets (AT) in the year before the SEO filing date. lnTA is the logarithm of total assets (AT) in the year before the SEO filing date. lnMKT is the natural logarithm of the issuer‟s market capitalization (shares outstanding multiplied by price per share) on the announcement date, which measures a firm‟s competitive position in the market place. We get it from. 政治大. a firm‟s total sales in the prior year. We expect this variable to be positively related to. 立. firm‟s cumulative abnormal returns should be larger for firms with a greater market. ‧ 國. 學. presence. Price is the SEO offer price. Tobin‟s Q is calculated as the sum of market. ‧. capitalization and total assets minus total common equity, scaled by total assets.. Nat. er. io. sit. y. lnTOBIN is the natural log of Tobin's Q, We expect the natural log of Tobin‟s Q is positively related to SEO returns.. al. n. iv n C h e n gof callhSEO Table 2 provides summary statistics i Ufirms. Panel A compares high. wave and low wave firms. Panel B compares high concentration and low concentration. firms.. C. Market reactions We examine the market reaction to the announcement of an SEO by event study method. We compute abnormal returns using the market model, 𝑅𝑖𝑡 = 𝛼𝑖 + 𝛽𝑖 𝑅𝑚𝑡 + 𝑒𝑖. (1) 14.

(20) where 𝑅𝑖𝑡 is the return of firm i at time t, 𝛼𝑖𝑡 is the average abnormal return of firm i, and 𝑅𝑚𝑡 is the value-weighted market return index. Abnormal returns 𝐴𝑅𝑖𝑡 are calculated as, 𝐴𝑅𝑖𝑡 = 𝑅𝑖𝑡 − (𝛼̂𝑖 + 𝛽̂𝑖 𝑅𝑚𝑡 ). (2). Where 𝛼̂𝑖 and 𝛽̂𝑖 are estimated from Eq. (1). The cumulative abnormal return (CAR) from firm i is calculated as follows： 𝐶𝐴𝑅𝑖 = ∑𝑇𝑖=1 𝐴𝑅𝑖𝑡. 立. 政治大. (3). The average cumulative abnormal returns for the time period (-1,+1) window. ‧ 國. 學. relative to the announcement event for which the abnormal return is being measured.. ‧. Our estimation period is -250 to -11 trading days before the SEO event.. y. Nat. io. sit. The regression is presented as follows,. er. CAR(−1, +1) = α + 𝛽1 𝑅𝑈𝑁𝑈𝑃 + 𝛽2 𝑅𝑂𝐴 + 𝛽3 𝑙𝑛TA + 𝛽4 𝑙𝑛MKT + 𝛽5 𝐻𝐻𝐼. al. n. iv n C h e n g+c𝛽h8𝐼𝑁𝐷𝑆𝐸𝑂𝑊𝐴𝑉𝐸 + 𝛽6 𝑃𝑟𝑖𝑐𝑒 + 𝛽7 𝑙𝑛TOBIN + 𝛽9 𝑇𝑂𝑇𝐴𝐿𝑆𝐸𝑂 i U + 𝛽10 𝐶𝑜𝑛𝑐/𝑆𝐸𝑂𝑠. 15.

(21) Table 1 Number of seasoned equity offerings (SEOs) by year This table provides the distribution of seasoned equity offers (SEOs) reported by SDC Database from 1990 to 2010. We report the mean (median) values of industry SEO wave (INDSEOWAVE) in each fiscal year. Number of Observations. Year. INDSEOWAVE Mean. Median. 1990. 89. 2.69. 2.00. 1991 1992 1993 1994. 292 255 373 243. 9.91 7.74 9.19 5.41. 4.00 4.00 5.00 3.00. 490 384 276 355 316. 17.33 10.85 10.57 29.03 29.58. 6.00 8.00 5.00 3.00 12.00 15.00. 230 198 255 251 207 225 209 139 284 163. 9.79 5.78 12.91 12.51 8.84 11.23 13.47 12.97 16.91 12.14. Ch. engchi. 5,634. y. sit. i Un. 12.77. 16. er. ‧ 國 n. al. ‧. io. 90-10. Nat. 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010. 學. 1995 1996 1997 1998 1999 2000. 政治大 14.21 立400. v. 5.00 3.00 7.00 5.00 4.00 5.00 6.00 4.00 7.00 8.00 5.76.

(22) Table 2 Univariate tests for analyzing the sample using changes in operating performance measures This table provides summary statistics and degree of wave (concentration). Panel A compares firms in high industry SEO wave and low industry SEO wave. Panel B compares firms in more concentrated and low concentrated industries. If the industry SEO wave in the particular industry wave is greater (small) than the median, the industry is classified as high-wave (low-wave). Panel A：Univariate tests for analyzing of SEOs firms in high and low wave. Mean. 0.0029 0.0315 5.1305. 0.0025 0.0246 5.5485. io. al. n. High Concentration Mean. C Median h. RUNUP. 0.0026. 0.0021. ROA lnTA lnMKT HHI Tobin‟Q. 0.0161 5.9680 13.1237 0.0027 7.2493. 0.0315 5.4882 13.0332 0.0017 7.4129. Variable. engchi. 17. y. 12.9240 0.0198 7.4633. sit. Nat. lnMKT 12.8972 12.7985 HHI 0.0024 0.0000 Tobin‟Q 7.9026 7.9976 Panel B：Univariate tests for analyzing of SEOs firms in high and low concentration. ‧. 0.0037 -0.1266 5.1451. Median. Median. P-value (differences in means). 0.0021 0.0315 5.0550. 0.000 0.000 0.000. 12.8679 0.0004 7.9976. 0.395 0.000 0.000. er. Mean. Low Wave. 學. RUNUP ROA lnTA. 立. High Wave. ‧ 國. Variable. 政治大. i vLow Concentration n U Mean Median. P-value (differences in means). 0.0033. 0.0026. 0.000. -0.0771 5.0109 12.6976 0.0000 7.8347. 0.0315 4.9855 12.6465 0.0000 7.9976. 0.000 0.000 0.000 0.000 0.000.

(23) Table 3 Market reaction to SEO announcement This table presents the market reaction to SEO announcements. Panel A reports average cumulative abnormal returns across three different event windows of (-1,+1), (-3,+3) and (-9,+9) days relative to the date of the SEO announcement (0) by the degree of SEO industry wave and industry concentration. The market model with returns from trading day -250 to trading day -11 are used to estimate CARs. Panel B reports the strategic interaction between industry wave and industry concentration. Difference in test is presented in last low (column). t-statistics are provided in parentheses. ***, **, and * indicate statistical significance at 1%, 5%, and 10% levels, respectively. Panel A：Univarite tests for market reaction (-1,+1) (-3,+3) (-9,+9) Mean Median Obs. Mean Median Obs. Mean Median Obs. High wave -2.60% -2.17% 2,643 -0.70% -1.06% 1,724 -0.52% -1.18% 1,746 Low wave -2.99% -2.28% 2,960 -1.57% -1.71% 1,777 -2.01% -2.29% 2,902 Test statistic -6.67*** 5.28*** -3.07*** 2.57*** 2.71*** 2.40***. 立. 政治大. ‧. ‧ 國. 學. n. Ch. y. 1,863 1,638. sit. io. al. -1.34% -1.72% 1.02. er. Nat. High concentration -2.85% -2.08% 2,317 -1.39% Low concentration -2.36% -2.03% 3,326 -1.12% Test statistic 0.62 0.60 0.64 Panel B： Interaction between Wave and Concentration to SEO announcement (1) High wave Observations CAR(-1,+1) (3) High concentration 878 -2.78%** (-2.02) (4) Low concentration 2181 -2.15% (-0.61) (3)-(4) -0.63%*** (2.59). i n U. e n g cObservations hi. 18. 1817 767. v. -0.18% -1.66% -1.89**. (2) Low wave CAR(-1,+1) -3.18%** (-1.99) -2.61% (-0.54) -0.57% (1.20). -0.71% -2.14% -2.77***. 2,298 2,350. (1)-(2) 0.40%** (-2.03) 0.46%** (-2.12).

(24) V. Empirical results. A. Results of Multiple Regressions We start by report univariate results to test whether firms observe the industry wave and conduct SEO announcements in the following six months. The estimation period is -250 to -11 trading days before the SEO event, average cumulative abnormal. 政治大. returns (CARs) across event windows from day (-1,+1), (-3,+3) and (-9,+9) around. 立. announcements of seasoned equity offerings. We use the CRSP value-weighted. ‧ 國. 學. market return as our market index. The results reports comparative average. ‧. cumulative abnormal returns (CARs) for SEO firms in High wave/ Low wave and. y. Nat. al. er. io. sit. High concentration/ Low concentration for the separate event windows following the. v. n. SEO announcements as shown in Table 3, we find that firms experience lower. Ch. engchi. i Un. negative returns during high industry wave. On average, 0.39% negative returns in one day event windows disappear during the high industry wave. Firms experience lower SEO negative day returns during higher industry wave. Firms in less concentrated industries also have lower negative announcements than those in more concentrated industries. Our results are consistent with the view that there exists mimicking wave in SEO announcements.. 19.

(25) Panel B reports the interaction effect between SEO industry wave and concentration. Since corporate policy is more observed in less concentrated industries, we argue that, the mimicking behavior is more easily observed in less concentrated industries. The Conc/SEOs interaction term is more positively significant to enhance the SEO industry wave in less concentrated industries. That‟s, firms in less concentrated firms is more likely to follow to conduct SEOs when they observe their. 政治大. industry peers negative abnormal return is lower than average. They expect to. 立. positively benefit to get lower day negative returns as well by getting the industry. ‧. ‧ 國. 學. SEO wave.. We further test whether this findings hold in multivariate setting by analyzing the. y. Nat. er. io. sit. one day abnormal returns event window on a number of control variables considers previously. Our results are consistent with the view that SEO announcements content. al. n. iv n C hen about industry prospects. This confirms the intuition g c h i ofUmarket timing hypothesis. B. Robustness tests. Although our evidence in Table 5 lends supports for the view that SEO announcements have important industry-specific mimicking behaviors. We further awaken interests by industry characteristics. Different to the aforementioned section, we try to find firms conduct SEO exists in some particular industries. We argue that 20.

(26) mimicking behavior do exist in some particular industries. SEO announcements exist frequently in particular industries as showed in Table 4. To check the robustness of our results, we try to classify our samples into industries based on four-digit SIC codes as in Fama and French (1997) instead. TOTALSEO is classified by four-digit SIC code defined as the number of firms within the given industry in the fiscal year. INDSEOWAVE is defined as the sum of the. 政治大. number of SEO announcements, excluding those of the firm in question, that occur in. 立. the same four-digit SIC code industry for all the other firms in the previous six. ‧. ‧ 國. 學. months.. Our analysis in Table 6 suggests the results remains consistent with our earlier. y. Nat. er. io. sit. studies. The findings support the market timing hypothesis and provide strong evidence the strategic interaction do exists in different industry classification. Firms. al. n. iv n C are likely issuing equity to catch hthe e SEO h i Uwave and strategic interaction n g cindustry enhances the industry SEO wave.. 21.

(27) Table 4 Distribution of Offering by Industry Firms are classified into industries based on four-digit SIC codes as in Fama and French (1997). Industry. Number of Firms. Industry. Number of Firms. Business Services Pharmaceutical products Electric Equipment Protroleum and Natural Gas. 655 358 298 231. Machinery Restaurants, Hotel, Motel Transportation Chemicals. 116 110 110 71. Retail Telecommunications Medical Equipment Computers Healthcare Wholesale. 229 180 169 162 136 119. Measuring and Control Equip Steel works, Etc. Construction Materials Entertainment Construction Other. 66 53 50 50 49 497. 學. ‧. ‧ 國. 立. 政治大. n. er. io. sit. y. Nat. al. Ch. engchi. 22. i Un. v.

(28) Table 5 Results of Multiple Regressions in the same three-digit SIC code industry This table presents the firm‟s decision to conduct SEOs using multiple regressions. The dependent variable is defined as SEO abnormal returns across event window form day -1 to day +1 around announcements on seasoned equity offerings. Model 1 and Model 2 present INDSEOWAVE and TOTALSEO respectively that industry wave do have an impact on firm‟s SEO decision. In Model 3 and Model 4,. 政治大. we take the Herfindahl index into considered to examine industry concentration measure do enhances the industry wave. Model 5 investigates cumulative abnormal returns during the SEO industry wave. In Model 6 we further examine the strategic interaction between the industry wave and concentration. t-statistics are provided in parentheses. ***, **, and * indicate statistical significance at 1%, 5%, and 10% levels.. 立. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. 23. i n U. v.

(29) CAR(-1,+1) Model (1) INDSEOWAVE. Model (2). Model (3). 0.01008*** (7.37). TOTALSEO. Model (4). 0.03769*** (11.70) 0.00476*** (5.96). 0.02265*** (11.84). Model (5) 0.01444*** (4.33) 0.00362* (1.86). 0.01532*** (4.54) 0.00320 (1.63) 0.01937 (1.63). 0.01371 (0.94) 0.15635*** (3.87) 0.02841 (1.60). 0.01519 (1.04) 0.15632*** (3.87) 0.02946* (1.66). 0.07577*** (4.89) -0.05698 (-0.28) 0.00285*** (3.13) 0.00821. 0.07640*** (4.93) -0.09713 (-0.48) 0.00286*** (3.14) 0.01027. (0.35) 0.46176** (2.37) 5372 0.0249. (0.44) 0.45715** (2.35) 5372 0.0256. Conc/ SEOs RUNUP. 立. ROA. io. al. n. Price lnTOBIN. Number of obs. R-squared. 0.31712*** (21.02) 5372 0.0122. 0.32154*** (20.17) 5372 0.008. Ch. engchi 1.03472*** (17.86) 5372 0.0440 24. y. -0.22720*** (-3.40). -0.20449*** (-3.03). sit. Nat. HHI. er. lnMKT. ‧. ‧ 國. 學. lnTA. Intercept. 政治大. i n U. v. 0.97164*** (15.87) 5372 0.0440. Model (6).

(30) Table 6 Robust tests in Fama and French industry classification This table presents the firm‟s decision to conduct SEOs using multiple regressions. The dependent variable is defined as SEO abnormal returns across event window form day -1 to day +1 around announcements on seasoned equity offerings. Model 1 and Model 2 present INDSEOWAVE and TOTALSEO respectively that industry wave do has an impact on firm‟s SEO decision. In Model 3 and Model 4, we take the Herfindahl index into considered to examine industry concentration measure do enhances the industry wave. Model 5. 政治大. investigates cumulative abnormal returns during the SEO industry wave. In Model 6 we further examine the strategic interaction between the industry wave and concentration. t-statistics are provided in parentheses. ***, **, and * indicate statistical significance at 1%, 5%, and 10% levels.. 立. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. 25. i n U. v.

(31) CAR(-1,+1) Model (1) INDSEOWAVE. Model (2). Model (3). 0.14817*** (5.47). TOTALSEO. Model (4). 0.13547*** (4.69) 0.00314*** (5.11). 0.00287*** (4.54). Model (5) 0.00846*** (4.82) 0.00088 (1.13). 0.01529*** (4.60) 0.00160* (1.92) 0.00502 (2.42). 0.01826 (1.28) 0.03468*** (3.36) 0.03411* (1.95). 0.02033 (1.42) 0.03514 (3.41) 0.03258* (1.86). 0.07918*** (5.19) -0.07467 (-0.37) 0.00325*** (3.59) 0.00786. 0.07746*** (5.07) -0.05292 (-0.26) 0.00328*** (3.63) 0.01253. (1.04) 0.48367** (2.51) 4396 0.0233. (0.55) 0.49778 (2.58) 4396 0.0246. Conc/ SEOs RUNUP. 立. ROA. io. al. n. Price lnTOBIN. Number of obs. R-squared. 0.33273*** (21.98) 4396 0.0068. 0.30879 (16.51) 4396 0.0059. Ch. engchi 0.34664*** (18.49) 4396 0.0298 26. y. -0.03851 (-1.26). -0.03018* (-1.80). sit. Nat. HHI. er. lnMKT. ‧. ‧ 國. 學. lnTA. Intercept. 政治大. i n U. v. 0.32854*** (15.16) 4396 0.0166. Model (6).

(32) VI. Conclusion In this study, we examine how the degree of product market competition affects the firm‟s decision to SEO announcements. According to previous literature, SEO announcements send a negative signal about poor investment opportunities prospect. We argue that, in the case of strategic interaction between firms, SEO announcement acquires a mimicking dimension.. 政治大 Our results provide two important findings. We find that SEOs negative day 立. ‧ 國. 學. returns will lower during the industry wave exists. On average, 0.39% negative. ‧. returns in one day event windows disappear during the high industry wave.. sit. y. Nat. Consistent with market timing hypothesis, firms follow the industry wave will. n. al. er. io. perform better on their SEO abnormal returns. The other results also support. Ch. i Un. v. industry concentration brings strategic interaction, which enhances the firm‟s. engchi. mimicking behavior. These results are also robust in different industry classification. We confirm this intuition by showing that SEO firms in less concentrated industries outperform the market. Our results blends corporate finance decision and industrial organization. The study gives a few crumbs of information about mimicking SEO behavior.. 27.

(33) We hope provide some new ways regarding why firms tend to cluster their SEOs and why they observe SEOs happening in waves.. 立. 政治大. ‧. ‧ 國. 學. n. er. io. sit. y. Nat. al. Ch. engchi. 28. i Un. v.

(34) References Ali, Ashiq, Klasa, Sandy, Yenug, Eric, 2012, Industry concentration and corporate disclosure policy, SSRN elibrary. Asquith, and David W. Mullins, 1986, Equity issues and offering dilution, Journal of Financial Economics 15, 61-89. Bamber, L., Cheon, Y., 1998, Discretionary management earnings forecast disclosures: antecedants and outcomes associated with forecast venue and forecast specificity, Journal of Accounting Research 36, 167-190. Baker, M., Wurgler, J., 2002, The equity share in new issues and aggregate stock returns, Journal of Finance 55, 2219-2258. Benveniste, Lawrence M., Walid Y Busaba, and William Wilhelm, 2002, Information externalities and the role of underwriters in primary equity markets, Journal of Financial Intermediation 11, 61-86. Boone, A.L.,Ivanov,V., 2012, Bankruptcy spillover effects on strategic alliance. 立. 政治大. ‧. ‧ 國. 學. partners, 2012, Journal of Financial Economics 103, 551-569. Bradley, D., Yuan, X., Information spillovers around seasoned equity offerings, 2013, Journal of Corporate Finance 21, 106-118. Brewer III, Elijah, William E. Jackson III, Julapa A. Jagtiani, and Thong Nguyen, 2000, The price of bank mergers in the 1990s, Economic Perspectives 24, 2-23. Burns, Natasha, and Ivonne Liebenberg, 2011, U.S. Takeovers in foreign markets: Do. y. Nat. sit. n. al. er. io. they impact emerging and developed markets differently?, Journal of Corporate Finance 17, 1028-1046. Clarke, Jonathan, Craig Dunbar, and Kathleen Kahle, 2004, The long-run performance of secondary equity issues: A test of the windows of opportunity hypothesis, Journal of Business 77, 575-603. Dasgupta, P. and Stiglitz, J., 1980, Uncertainty, Industrial Structure and the Speed of R&D, Bell Journal of Economics 11, 1-28. DeAngelo, Harry, Linda DeAngelo, and René Stulz, 2010, Seasoned equity offerings, market timing, and the corporate life cycle, Journal of Financial Economics 95, 275-295.. Ch. engchi. i Un. v. Demsetz, Harold, 1973, Industry structure, market rivalry and public policy, Journal of Law and Economics 16, 1-9. Erwin, Gayle R., and James M. Miller, 1998, The intra-industry effects of open-market share repurchases: contagion or competitive? The Journal of Financial Research 21, 389-406. Funke, Christian, Timo Gebken, Lutz Johanning, and Gaston Michel, 2008, Information signaling and competitive effects of M&A: long-term performance of rival companies, SSRN eLibrary. 29.

(35) Gomes, A., Philips, G.M., 2007, Private and public security issuance by public firms: The role of asymmetric information. Working Paper, University of Maryland. Harris, M. H., 1998, The association between competition and managers‟ business segment reporting decisions. Journal of Accounting research 36, 111-128. Hertzel, M. G., Li, Z., Officer, M. S., Rodgers, K.J., 2006, Inter-firm linkages and the wealth effects of financial distress along the supply chain. Journal of Financial Economics 87, 374-387. Ibbotson, Roger G., 1975,“Hot Issue” Markets, Journal of Finance 30, 1027-1042. Jorion, Philippe, and Gaiyan Zhang, 2007, Good and bad credit contagion: Evidence from credit default swaps, Journal of Financial Economics 84, 860–883. Lang, Larry H.P. and Rene M. Stulz, 1992, Contagion and Competitive Intra-industry Effects of Bankruptcy Announcements：An Empirical Analysis. Journal of Financial Economics 32, 45-60. Loughran, Tim, and Jay Ritter, 1995, The new issues puzzle, The Journal of Finance. 立. 政治大. ‧. ‧ 國. 學. 50, 23-52. Loughran, Tim, and Jay Ritter, 1997, The operating performance of firms conducting seasoned equity offerings, Journal of Finance 52, 1823-1850. Massa, Massimo, Zahid Rehman, and Theo Vermaelon, 2007, Mimicking repurchases, Journal of Financial Economics 84, 624-666. Masulis, and Ashok N. Korwar, 1986, Seasoned equity offerings: An empirical investigation, Journal of Financial Economics 15, 91-118.. y. Nat. sit. n. al. er. io. Myers, Stuart, and Nicholas Majluf, 1984, Corporate financing and investment decisions when firms have information that investors do not have, Journal of Financial Economics 13, 187-221. Ritter, J., 1984, The „hot issue‟ market of 1980, Journal of Business 57, 215-240. Rajan, Raghuram G, 1994, Why Bank Credit Policies Fluctuate: A Theory and Some Evidence. The Quarterly Journal of Economics 109, 399-441. Roll, Richard and Stephen A. Ross, 1980, An empirical investigation of the arbitrage pricing theory, Journal of Finance 35, 1073-1103. Shahrur, Husayn, and Anand Venkateswaran, 2009, Industry Prospects And Acquirer Returns In Diversifying Takeovers, Journal of Financial Research 32, 23-51.. Ch. engchi. i Un. v. Shaked, A.,Sutton,J.,1987.Product differentiation and industrial structure, Journal of Industrial Economics 26,131-146. Song, Moon H., and Ralph A. Walkling, 2000, Abnormal returns to rivals of acquisition targets: A test of the “acquisition probability hypothesis”, Journal of Financial Economics 55, 143-171. Sutton, John., 1991, Sunk costs and market structure: Price competition, advertising and the evolution of concentration. Cambridge, MA: MIT Press. 30.

(36) Appendix A. Variables description. Variable. Description. Panel A. SEO characteristics and description INDSEOWAVE. TOTALSEO Conc/SEOs. The sum of the number of SEOs announcements, excluding those of the firm in question, that occur in the same three-digit SIC code industry for all the other firms in the previous six months. Classify by three-digit SIC codes, defined as the number of firms within the given industry in the fiscal year. A proxy to measure the effect on the probability of a SEO announcement resulting from an increase in both the concentration of the industry and the intensity of the SEOs intra-industry activity.. 立. 政治大. Panel B. variables related to firm characteristics. ‧ 國. y. Nat. sit. io. The natural logarithm of the issuer‟s market capitalization (shares outstanding multiplied by price per share) on the announcement date. The Herfindahl-Hirschman Index, which is the sum of the squared fraction of industry sales by all firms in the 3-digit SIC industry for the year prior to the announcement. The issue of SEO offer price. The natural log of Tobin's Q.. n. al. er. lnMKT. ‧. lnTA. The firm‟s buy-and-hold returns over the year prior the issue. Earnings divided by total assets (AT) in the year before the SEO filing date. The logarithm of total assets (AT) in the year before the SEO filing date.. 學. RUNUP ROA. HHI. Price lnTOBIN. Ch. engchi. 31. i Un. v.

(37)