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Qile Tan and Bill Dimovski Deakin University

The Underpricing of Infrastructure IPOs: Evidence from China. Qile Tan and Bill Dimovski Deakin University. Initial Public Offering (IPO) underpricing:. IPOs are common around the world

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Qile Tan and Bill Dimovski Deakin University

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  1. The Underpricing of Infrastructure IPOs: Evidence from China Qile Tan and Bill DimovskiDeakin University

  2. Initial Public Offering (IPO) underpricing: • IPOs are common around the world • Before 2009, the US was the leading issuer of IPOs in terms of total value. Since then, China has been the leading issuer, raising $73 billion (almost double the amount of IPO money raised on the NYSE and NASDAQ combined) in 2011 • Underpricing/first day returns to subscribers on average are also common. Facebook issue $38, close day1 $38.23 • Underpricing appears more severe in emerging markets

  3. Equally weighted average initial returns for 12 countries Australia Lee, Taylor & Walter; Woo; Pham; Ritter 1,562 1976-2011 21.8% Canada Jog & Riding; Jog & Srivastava; 696 1971-2010 6.7% Kryzanowski, Lazrak & Rakita; Ritter China Chen, Choi, & Jiang; Jia & Zhang 2,102 1990-2010 137.4% France Husson & Jacquillat; Leleux & Muzyka; 697 1983-2010 10.5% Paliard & Belletante; Derrien & Womack; Chahine; Ritter; Vismara   Germany Ljungqvist; Rocholl: Ritter; Vismara 736 1978-2011 24.2% Greece Nounis, Kazantzis & Thomas; 373 1976-2011 50.8% Thomadakis, Gounopoulos & Nounis Hong Kong McGuinness; Zhao & Wu; Ljungqvist & 1,259 1980-2010 15.4% Yu; Fung, Gul, and Radhakrishnan; Ritter India Marisetty and Subrahmanyam; Ritter 2,964 1990-2011 88.5% Jordan Al-Ali and Braik 53 1999-2008 149.0% Malaysia Isa; Isa & Yong; Yong; Ma 413 1980-2009 62.6% United Kingdom Dimson; Levis 4,877 1959-2011 16.1% United States Ibbotson, Sindelar & Ritter; Ritter 12,340 1960-2012 16.8% source: Ritter (2013)

  4. Some theoretical explanations for underpricing Rock (1986) - IPOs need to be underpriced to continually attract uninformed investors Welch(1989) – Underpricing allows for subsequent issues at a higher price Tinic (1988) suggests underpricing is like an insurance and prevents against damages to underwriters/directors Ruud (1993) – underwriters price support the issue for a short time Beatty and Ritter (1986) – greater uncertainty, greater underpricing – older entities, larger entities, those with more reputable auditors and with banking and venture capital relationships – lower underpricing

  5. Underpricing in different industries • Dimovski and Brooks (2008) – gold 13.3% (while industrials around 25%) • REITs – US – Wang, Chan and Gau(1992) negative 2.82%, Ling and Ryngaert (1997) 3.6%, Bairagi and Dimovski (2011) 4.6% • A-REITs – Dimovski (2009) 2.6% • J-REITs – Kutsuna et al (2008) 0.5% • Infrastructure – Australia 3.5% but not stat sig diff to zero • Infrastructure – India 25%

  6. Characteristics of infrastructure: • high entry barriers • monopoly characteristics • long duration • large investment scale • inelastic demand • stable, tax effective and predictable cash flows via government regulation and long-term contracts • low correlation with major asset classes • low volatility of cash-flows (Newell, Chau and Wong, 2009)

  7. What is infrastructure? • It provides the essential services for a community's economic and social needs, eg: • transport: toll roads, airport, sea ports, rail, and bridges; • energy and utilities: electricity, water, and gas; • communications: mobile phone networks, telecommunication networks, and satellite systems; and • social: healthcare, education, and correctional facilities. (RREEF, 2005; and UBS, 2006a)

  8. Previous studies of infrastructure IPOs: • Hong Kong Dewenter and Field(2001) 1996-1997, 7 infrastructure IPOs report a 4.67% underpricing (not statistically significant). • Australia Dimovski (2011) 1996-2007, 30 infrastructure IPOs report a 3.5% underpricing (not statistically significant). • India Ritchie, Dimovski and Deb (2013) 2004-10, 49 infrastructure IPOs report a 25.4% underpricing (statistically significant).

  9. Previous studies of infrastructure IPOs:

  10. Characteristics of the Chinese stock market: • Two types of shares: • A-share and B-share • Long delay between offering date and listing date • Average 260 calendar days for A-share IPOs (Su and Fleisher, 1999) • High government ownership • Highly speculate market

  11. Data: • 154 A-share infrastructure IPOs issued during1993 to 2012 • Prospectuses were downloaded from Shanghai and Shenzhen stock exchanges • CSMAR database is used for index returns and in the case of missing data in prospectus

  12. Dependent variable: Initial returns • Independent variables: • Stock exchange dummy • Market index return • Time lag between offering and listing date • Firm age • Offer price • Logarithm log of issue size • Government ownership after issuing • Pricing method dummy • Underwriter reputation

  13. Methodology: • Ordinary Least Square (OLS) • Model 1: • Utilizing all variables except Time Lag and Market return • Model 2: • Utilizing all variables

  14. Regression results: • In model 1 (LAG and MARKET are not included) offer price, stock exchange and issue sizeare highly significant with expected signs. • In model 2 (LAG and MARKET are included) stock exchange, time lag and issue sizeare highly significant with expected signs.

  15. Results: • Issue size (in log form) is significant with expected sign in all partitions in both models. • Underwriter reputation and Government retention are not significant across all partition in both models.

  16. Summary: • The average initial return for Chinese infrastructure IPOs during 1993 to 2012 is 91.1%, which is statistically significantly different to zero and relatively higher than in India and Australia. • Infrastructure IPOs in China carry less uncertainty in the valuation of the IPO comparing to the whole market.

  17. Summary: • In China, the offer price and issue size appear to be helpful in the prediction for the underpricing of infrastructure IPOs. • Government retention and underwriter reputation do not have significant predicting power in our study. • When time lag and market return being included in the regression model, the time lag and issue size can better explain the underpricing.

  18. Thank you for your time 

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