The Winner’s Curse and Lottery-Allocated IPOs in China

1. The Winner’s Curse and Lottery-Allocated IPOs in China Jerry Coakley, Norvald Instefjord and Zhe Shen* University of Essex; *Xiamen University CEF-QASS Empirical Finance Conference May 2008

2. Outline • Background • Data and Summary Stats • Hypothesis Testing • Discussion

3. 1. Background • 2 IPO puzzles --Short term underpricing --Long term underperformance • We focus on underpricing: opening day trading p exceeds offer p • Called leaving money on the table! • How do we explain it?

4. Background: Why China? • Underpricing is extreme relative to other countries • Average typically exceeds 100% but can be 4000% or more! • Emerging market – plausible to assume that some investors are uninformed • Hugely active market with unique data availability

5. Background: Chinese IPOs • Recent large IPOs: • Chinese banks: Industrial & Commercial Bank of China $21.6bn in 2006 Also Bank of China $11bn; China Construction Bank $9bn 2005 • Credit cards: Visa $17.9bn March 2008 Also Mastercard • Internet eg AT&T $10.6bn 2000 Also Google, Amazon, Netscape, Yahoo

6. Background: Winner’s curse • WC one explanation for underpricing! • Arises in auctions where bidders have only estimates of the true value • Winner is highest bidder who tends to be over optimistic • Tendency for winner to overpay increases with number of bidders • Applications: IPOs and oil fields!

7. Rock (1986) WC model • Naïve (uninformed) and informed investors • Naïve investors receive small allocations in good IPOs as everyone bids for them • They get large allocations in bad ones (dogs) as informed investors don’t compete for these • Cf Groucho Marx: “I would never join a club that would have me for a member”

8. Rock (1986) WC model • Without underpricing, naïve investors would systematically make losses • Underwriters deliberately underprice IPOs to attract them to dogs or bad issues • Prediction: Weighting abnormal returns by allocations will leave naïve investors with zero abnormal profits

9. Rock (1986) model tests • Direct tests of WC limited by LACK of detailed allocation data • Just a handful of extant studies • All claim to support WC! • Indirect studies contrast institutional and individual investor allocations

10. Contributions • First study of Rock’s model where oversubscribed IPOs are allocated by lottery as in Rock model • Lottery avoids biases against large orders by informed investors • Rock assumes latter exploit large orders • Lottery vs proration (Amihud et al JFE: an allocation is guaranteed in proration but not in a lottery

11. Contributions cont’d • Second, Rock’s model is consistent with important aspects of underpricing in our Chinese IPO sample 1996-2001 • Evidence of adverse selection: inverse relation between underpricing and allocation • Allocation weighting does indeed cause a very substantial drop in nominal abnormal returns - they a fall of more than 200-fold from 116% to just 0.51% (median).

12. Contributions cont’d • Finally our sample avoids some pitfalls of extant studies of Chinese IPOs. • We restrict our sample to IPOs that employ the same issuing method and are subject to the same regulatory regime. • Both the stock issuing and pricing methodologies vary significantly during 1990s and early 2000s with extreme underpricing (5000%) in some cases. • Largest sample to date in studies of the winner’s curse hypothesis.

13. 2. Data & Summary Stats • Sources: SinoFin CCER, DataStream, and GTA CSMAR + IPO prospectus and listing announcements. • Sample selection • A-share issue • Remain listed until the end of 2001 • Online fixed price offering to investors • Data available on the number of applicants • Data available on the rate of allocation

14. Data contd • Very recent market (1990) • Huge underpricing – in excess of 100% even excluding 1000%+ outliers • Virtually no overpricing ie no dogs! • Huge oversubscription – around 200 times • Authorities (not underwriter) mostly decide on pricing

15. Underpricing • Initial run-up (Ritter & Welch) • Initial excess return (Amihud et al)

16. Share issuance and allocation 1996-2001

17. Share pricing 1996-2001

18. Empirical summary: Underpricing

21. Summary results: Allocation

22. Determinants of underpricing (allocation) IRj=α0+ α1PROCEEDSj + α2SDIRj +uj • Larger the issue size (Proceeds), the smaller the valuation uncertainty • Greater the information asymmetry (SDIR) , the greater underpricing • IR is inversely related to size but positively related to standard deviation • In Rock’s model, these should be unrelated to allocation

23. Determinants of Underpricing IRj=α0+ α1PROCEEDSj + α2SDIRj +uj

24. Determinants of Allocation • Allocation is a proxy for excess demand • Sig related to SDIR in only 3/6 years and not in overall szample • But size (negatively related to IR) is positively related allocation! • May suggest that underpricing is greater than necessary to ensure a given level of excess demand

25. Determinants of Allocation ALLOCTj=β0+ β1PROCEEDSj+ β2SDIRj +vj ALLOCTj = log((ALLOCj+a)/(1-ALLOCj+a))

26. 3. WC Hypothesis Tests • Hypothesis 1: there is no relationship between IR and allocation (adverse selection) • Coeff is sig negative at 1% level in all cases • Bigger IR associated with stronger XD or smaller allocations • Adverse selection is also supported if we compare good vs bad IPO allocations • Median allocations are 0.38% vs 0.68% • Top vs bottom quintile means: 0.5% vs 4.34%

27. Rock’s Model: Adverse selection IRj=α0+α1ALLOCTj+εj

28. Adverse selection • Underpricing could lead to an increase in order size or in the no. of applicants • Hypothesis 2: there is no relationship between number of applicants (Orders) and the degree of underpricing • ORDERSj = a+0.18IRj+ 0.23PROCEEDSj - 0.13SDIRj +εj • (9.41) (5.37) (-7.61) • Positive relationship between underpricing and orders is consistent with prediction that underpricing attracts more investors to the IPO

29. Break even prediction • Underpricing does not imply gains for all investors in Rock’s model • Define allocation-weighted initial return • AWIRj = ALLOCj * IRj - interestj • Hypothesis 3: adjusting for allocation and risk, uninformed investors earn zero abnormal returns • Lottery allocation involves risk so implies AWIR >0

31. Break-even cont’d • The mean value of AWIR is 0.78% while the median is even lower at 0.51%. • Abnormal profits are positive but small in economic terms. • Consistent with the break-even prediction after allowing for lottery risk • Cf Yu and Tse (2006) AWIR = 0

32. Break-even cont’d • Studies in other countries: • Our sample is considerably larger, twice at a minimum than those in extant studies • Our sample more consistent. • Eg allocation bias against large orders in Singapore, Finland and UK • Results are mixed: Neg AWIR (Finland/Israel), AWIR>0 (UK/Singapore)

33. Break-even cont’d

34. 4. Discussion • Apparent evidence supporting WC: • Negative relationship between IR and ALLOC ie underpricing used to offset bias in allocation • Allocation-wgted abnormal profits are positive but economically close to zero • However, need to reexamine participation since pricing may be seen as exogenous in China (multiple of earnings) • It’s endogenous in WC model

35. Discussion • Proration vs Lottery IPOs • Lottery = proration with (lottery) risk • Sample of 74 out 111 proration IPOs with relevant data over same period • No adverse selection and mean AWIR of 5.1% > 6 times lottery AWIR! • Contrary to rational participation as proration issues are less risky!

36. Discussion • Authorities use lottery IPOs to promote mass participation or popular capitalism • Naïve investors focus more on upside potential in lottery IPOs ie focus on nominal IR rather than AWIR • This encourages herding into lottery IPOs and may explain their lower AWIR!