An empirical assessment of initial return volatility in newly listed stocks

Paul B. McGuinness

Department of Finance, The Business Administration Faculty, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

ABSTRACT

A stockrsquo;s first month of listing or lsquo;seasoningrsquo; is often characterized by sharp volatility in initial returns. Such volatility is likely to be even more pronounced in initial public offering (IPO) markets where retail investors exert significant influence. I consider initial return volatility for IPOs pitched in Hong Kong, where the market organizer requires a sizeable fraction of shares on offer to be assigned to a retail subscription tranche. Within this context, I examine the pattern and determinants of IPO stocksrsquo; initial return volatility levels over their first 30 days of lsquo;seasoningrsquo;. I observe that IPO underpricing, market sentiment and float size figure as key explanatory factors. Results also reaffirm the importance of information asymmetry effects (Ritter, 1984; Beatty and Ritter, 1986; and Lowry et al., 2010). Larger IPO firms with tighter offer price spreads and more reputable underwriters exhibit noticeably greater price stability. I also assess Ljungqvist, Nanda and Singhrsquo;s (2006) proposition that underpricing in lsquo;hotrsquo; IPOs protects issuers and subscribers against a subsequent fall-off in issuer sentiment. Via analysis of retail tranche share allotments, I meaningfully extend findings (Jiang and Li, 2013) in this area.

KEYWORDS

IPOs; initial return volatility; price uncertainty

I. Introduction

This short article focuses on the volatility of initial public offering (IPO) returns during a newly-listed stockrsquo;s first 30 days of listing. Initial volatility can be extreme during this period. Houston, James, and Karceski (2006) observe that the first month of sea-soning is critical in establishing a stockrsquo;s fundamen-tal value. Lowry, Officer, and Schwert (2010) demonstrate that information asymmetry effects strongly underlie such return variability. In extend-ing this debate, I assess initial return volatility for IPOs pitched in Hong Kong. This setting is of inter-est given retail investorsrsquo; significant role in subscrip-tion and initial secondary market trading. This special influence derives from a dual-tranche offer form, earmarking separate retail and book-built pla-cing tranches. Subscribers to the retail tranche (RT) typically receive a large block allocation, ranging from 10 to 50% of IPO shares.¹

Various studies indicate that offer prices only partially adjust for the ex-ante uncertainty (Ritter 1984; Beatty and Ritter 1986) surrounding issuer value (Hanley 1993; and Bradley and Jordan 2002).This means that a residual or lsquo;ex-postrsquo; element of uncertainty filters into initial secondary market returns (Ritter 1984; Chen and Wilhelm 2008; Ljungqvist, Nanda, and Singh 2006; and Falconieri, Murphy, and Weaver 2009). In respect of HK, Jiang and Li (2013) identify trading effects in support of the Ljungqvist, Nanda, and Singh (2006) argument of differential pre-and post-IPO sentiment effects.

In the initial seasoning period, market values could deviate significantly from fair value due to retail investorsrsquo; greater risk of adverse selection (Rock 1986). First and consistent with Ljungqvist, Nanda, and Singh (2006), retail investors denied sizeable allocations in lsquo;hotrsquo; IPOs could flood the initial secondary market with buy orders. Second, applicants with overpriced allocations might react by quickly unloading shares. Extreme volatility may simply arise because of retail investorsrsquo; proclivity to trade exclusively on sentiment. Lock-ups also act to limit corporate and institutional investorsrsquo; ability to sell nontrivial holdings (Chen and Wilhelm 2008). Institutions may thus help in softening initial return volatility. For HK, Jiang and Li (2013) show that when pre- to post-market sentiment adjusts fromlsquo;highrsquo; to lsquo;lowrsquo;, small and large tradersrsquo; buy–sell order flows move in counter-fashion.²

In the present study, market sentiment, float size, offer price spread, underwriter quality and issuer size all figure as important determinants of initial return volatility. I also identify lsquo;hotrsquo; IPOs via RT allotments and offer support for the Ljungqvist, Nanda, and Singh (2006) model of initial returns.

1. Data, descriptive statistics and research design
2. use the standard deviation of a stockrsquo;s daily close-to-close returns over its first 30 daysrsquo; trading as my dispersion metric. This form contrasts with variability measures formulated for fixed holding-periods. For example, and in relation to HK-IPOs, McGuinness (2014a, 150) reports a standard devia-tion in initial 30-day holding returns of 21.76%. Such return variation is not within the 30-day period but across issuers (see Jog and Wang (2009) and Lowry, Officer, and Schwert (2010) for similar approaches). I thus consider return variability for a given issuing firm. This approach entails computation of the standard deviation of

successive daily rates of return from first day list-ing close (t = 1) to the close of trading day p.³ Where p = 30, the volatility measure for a given IPO firm captures the standard deviation of its first 29 close-to-close returns. Table 1 reports a mean volatility value, across all issues (n = 269), of 3.56%. In respect of an issuerrsquo;s first five days of listing (t = 0 and p = 5; t = 0 is the open of the first listing day), T

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新上市股票初始收益率波动性的实证检验

Paul B. McGuinness

金融系，工商管理学院，中国香港大学，沙田，新界，香港

摘要：股票上市的第一个月或“调味”通常以初始收益率的剧烈波动为特征。在散户投资者产生重大影响的首次公开发行（IPO）市场中，这种波动可能更为明显。我认为IPO初始收益率波动在香港尤为明显，那里的市场组织者需要相当大的一部分股份给被分配到一个散户认购份额。在此背景下，我研究了IPO股票的初始收益率波动水平在前30天的模式和决定因素。我认为IPO抑价、市场情绪和浮动规模是关键的解释因素。结果还重申信息不对称效应的重要性（Ritter，1984；Beatty和Ritter，1986；和Lowry et al.2010）,更大的IPO公司报价价差更高，承销商更具显著的价格稳定性。我还评估了Ljungqvist、南达和Singh（2006）提出的“热”IPO抑价保护发行人和认购人免受发行人情绪随后下跌的影响。通过分析零售份额份额分配，我有意义地扩展了这一领域的研究结果（江和李，2013）。

关键词：IPO回购；初始收益波动；价格不确定性

1.引言

这篇简短的文章重点讨论了新上市股票在上市前30天首次公开发行（IPO）收益的波动性。在此期间，初始波动可能是极端的。休斯敦，杰姆斯，和卡瑟斯基（2006）观察的第一个月是在建立一个股票的基本价值观的批判。Lowry，和Schwert（2010）表明，信息不对称强烈影响了这种回归变异的基础。在延长这场辩论，我对新股初始收益波动定在香港。这个设置是给散户投资者的兴趣在下标和初始的二级市场交易的重要作用。这种特殊的影响来自于双份额的报价形式，专款专用，单独的零售和图书建立军两档。零售份额（RT）的订户通常收到一个大的块分配，从10到50%的IPO股票。

各种研究表明，提供的价格只是部分调整的事前不确定性（Ritter 1984；Beatty和瑞德1986）周围的人的价值（汉利1993；布拉德利和约旦2002）。这意味着不确定性的过滤器为初级市场收益剩余的或“事后”的元素（Ritter 1984；陈和威廉2008；Ljungqvist，Nanda，辛格2006；和法尔科涅里，墨菲和Weaver 2009）。在HK方面，江和李（2013）识别在Ljungqvist，Nanda支持交易的影响，和Singh（2006）差分前、后上市的影响参数。

在初始调味期，由于散户投资者的逆向选择风险较大，市场价值可能偏离公允价值（岩石1986）。第一，与Ljungqvist一致，Nanda，和Singh（2006），散户投资者否认大规模分配热门新股可能二级市场购买订单快速增加。其次，定价过高的申请者可能会迅速卸载股票。极端波动可能仅仅是因为散户投资者倾向于情绪贸易。锁定也限制了公司和机构投资者出售非常规资产的能力（陈和威廉2008）。因此，机构可能有助于软化初始收益率波动。在HK，江和李（2013）表明，当预后市场情绪调整fromhigh 到低，小的和大的贸易商购买–卖单流反时尚运动。

在目前的研究中，市场情绪、浮动规模、报价价差、承销商质量和发行人规模都是影响初始收益率波动的重要因素。我还通过RT分配来识别“热门”IPO，并为LungQVIST、Nanda和Sunh（2006）初始收益模型提供支持。

2. 数据、描述性统计和研究设计

我用一个股票在其前30天交易中的接近收盘价的标准差作为我的分散度量。这种形式与固定持有期的变异性度量形成对比。例如，例如，相对于香港IPO，McGuinness（2014A，150）在最初的30天持有回报率中报告了21.76%的标准偏差。这种收益变化不在30天内，而是跨发行者（见Jog and Wang (2009) ， Lowry和Schwert（2010）类似的方法）。因此，我考虑给定发行公司的回归变异性。此方法需要从第一天上市的回报率接近连续每天的标准偏差计算（T = 1）的交易日，P = 30，对于一个给定的IPO公司的波动率度量了它的第一个29收盘收益率的标准差。表1报告平均波动值，跨越所有问题（n＝269），为3.56%。关于发行人的上市前五天（t＝0和p＝5；t＝0是第一上市日的开户）；表1显示平均值为5.36%（n = 269）。波动性在交易的第二十五天和第三十天之间显著下降（平均为2.82%）（即，T＝25，p＝30）。

我在2005至2009年间在港交所主板研究新的上市事宜。方程1概述决定这样股票的日常波动性。

相关的经验证据表明，优惠折扣（PROBR）与初始二级市场回报率（波动性）的变化之间存在着积极的联系。Underpr抓住了最终报价和第一次市场开放之间的市场调整助跑。这不是用户的融资成本或发行人的子描述基金的利息帐户（见Fung和CHE 2009讨论）。

对于整体市场情绪，我定义了四个时期。posmkt1捕获前全球信贷紧缩的牛市（01 / 01 / 05–31/10 / 07）和negmkt2和negmkt3亚时期的熊市条件后雷曼崩溃（01 / 11 / 07 / 09 / 08–08；和09 / 09 / 31 / 03 / 09 08–）。虚拟市场标识在2009的最后八个月复苏的情绪。对于初步情绪，我确定上市公司的上市时间为五天左右。Lowry和Schwert（2010）更活跃的几个月表现出更大的收益率。6个IPO公司的公众持股量可能也会对收益率的波动性。更大的收益波动率可能在股票更“稀缺”（Loughran和麦当劳2013, 313）。因此，我断定波动率与公众持股量的倒数成反比。

像是Ritter（1984），Beatty和Ritter（1986）、Lowry、和Schwert（2010）的报告强调的对初始定价信息不对称的重要性。假设发行人和承销商之间的信息差距在发行规模和承销商质量上有所下降，但在报价价差上有所增加。首先，大企业可能会更加明显，具有较强的跟踪记录的收入，使他们的估值不确定性。给定可能的非线性，五个假人特征（sizeq1-5）。其次，一个更广泛的传播可能意味着更大的价格定价的不确定性。第三，正如在Beatty和RITE（1986）中所争论的，不确定性应该在承销商质量（QualuWR）中降低。

在市场购买活动的全球协调员（stblzn）可能情绪波动，约三分之一的IPO面临此类干预，零售结束后的第三十个日历日允许稳定结束。由于零售关闭通常发生在上市前一周，稳定结束在上市的第二十三日历（第十七交易日）。最后，控制状态支持问题（HR）。

表1–3的描述性统计和相关性为解释变量多重共线性出现在较低的水平。对于可变建设，我利用发行文件和IPO公告张贴到港交所的网站。股票和指数的价格数据，可利用数据流得出。

表1 新上市股票初始收益波动性的描述性统计

表2 描述性统计

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