1 The Winner’s Curse and Lottery- Allocated IPOs in China Jerry Coakley, Norvald Instefjord and...
-
Upload
jeffrey-hunter -
Category
Documents
-
view
218 -
download
4
Transcript of 1 The Winner’s Curse and Lottery- Allocated IPOs in China Jerry Coakley, Norvald Instefjord and...
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 ConferenceMay 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?
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
4
5
Background: Chinese IPOs Recent large IPOs: Chinese banks: Industrial & Commercial
Bank of China $21.6bn in 2006Also Bank of China $11bn; China Construction Bank $9bn 2005
Credit cards: Visa $17.9bn March 2008Also Mastercard
Internet eg AT&T $10.6bn 2000Also 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
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
9
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
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 pricing14
Underpricing Initial run-up (Ritter & Welch)
Initial excess return (Amihud et al)
15
%1001
0,
1,1,
j
jj
P
PR
%100
0,
1,
0,
1,1,
m
m
j
jj
P
P
P
PIR
16
Share issuance and allocation 1996-2001
Method of Share Issuance No. Initial Run-up MedianMethods of Share
Allocation
“Firm commitment” 70 1474.87% 1264.50% N/A
Certificates of deposits 8 162.38% 155.91% Normal / Pure Lottery
Prepayment in full, proportional allocation
111 148.81% 129.71% Proration
Online primary offering 592 129.72% 117.70% Pure Lottery
Online primary/secondary offering
35 158.08% 146.86% Pure Lottery/Pro ration
Online bookbuilding 6 160.24% 137.02% Pure Lottery
Online and offline bookbuilding
6 55.94% 57.19% Pure Lottery/Pro ration
Unknown 1 452.77% 452.77% -
Total 829 247.45% 128.95%
17
Share pricing 1996-2001
Method of price determination
Total of 829 562 in sample%
includedFormula
No.Initial
Run-upNo.
InitialRun-up
Earnings Forecasts 88 84.41% 47 70.46% 53.41 YES
EPS in the past 3 years 224 147.34% 146 141.51% 65.18 YES
50/50 77 148.09% 53 138.53% 68.83 YES
Weighted Average 169 122.64% 165 120.82% 97.63 YES
Negotiated 189 148.33% 151 146.93% 79.90 NO
Authorities 701474.87
%0 - - NO
Bookbuilding 12 108.09% 0 - - NO
Total 829 247.45% 562 130.67% 75.34
18
Empirical summary: Underpricing
Year No. Initial returns
Min Median Max Std. Dev.
1996 99 100.95% -18.35% 96.20% 336.88% 69.87%
1997 116 142.80% 34.58% 124.75% 463.65% 71.75%
1998 87 131.59% 1.27% 117.29% 430.65% 80.35%
1999 96 111.19% 6.01% 92.96% 820.50% 99.23%
2000 99 147.24% 0.70% 137.42% 477.98% 86.68%
2001 65 143.42% 3.41% 136.63% 413.56% 87.47%
Total 562 129.15% -18.35% 115.90% 820.50% 84.06%
19
`
0
20
40
60
80
100
0 100 200 300 400 500
5
30
46 50
92
87
78
47
42
23 19
14
8 6
3 3 3 2 1 1 1
Freq
uenc
y
Initial return (%)
1
`
0
20
40
60
80
100
0 100 200 300 400 500
5
30
46 50
92
87
78
47
42
23 19
14
8 6
3 3 3 2 1 1 1
Freq
uenc
y
Initial return (%)
1
20
0
20
40
60
80
100
120
0.0 0.5 1.0 1.5 2.0 2.5 3.0
4
46
101
74
64
41
33
21
27
12
20 15
13
6 9
3 5 5 5 5 3 2 2 1
6 5 4
2 0 1
Freq
uenc
y
Allocations (%)
27
21
Summary results: AllocationMean Min. Median Max. N
1.4008 0.0558 0.4761 90.5777 562
ALLOC (%)
Good IPOs: IRj>median
2.2408 0.1326 0.6789 90.5777 281
Bad IPOs: IRj<median
0.5604 0.0558 0.3770 5.8139 281
Good IPOs: IRj>mean
2.0427 0.1247 0.6697 90.5777 326
Bad IPOs: IRj<mean
0.5141 0.0558 0.3485 5.8139 236
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 UnderpricingNo. α1 α2 R2 (%)
1996 99 -90.94 (-3.90)*** 40.79 (5.89)*** 41.00
1997 116 -96.13 (-4.25)*** 41.74 (2.88)*** 36.55
1998 87 -168.34(-7.75)*** 70.26 (4.83)*** 64.41
1999 96 79.44 (-2.05)** 114.72 (2.87)*** 57.35
2000 99 -162.28 (-5.34)*** 44.04 (2.79)*** 40.35
2001 65 -208.23 (-5.35)*** 20.21 (2.10)** 60.17
Total 562 -56.61 (-6.06)*** 43.18 (6.20)*** 23.83
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 AllocationNo. β 1 β 2 R2 (%)
1996 99 0.79 (2.34)** -0.15 (-2.76)*** 13.33
1997 116 0.24(2.92)** 0.01 (0.24) 6.51
1998 87 0.56(5.47)*** -0.12 (-2.84)*** 35.41
1999 96 0.77 (8.17)*** -0.05 (-1.22) 61.06
2000 99 0.60 (6.93)*** -0.09 (-3.70)*** 36.06
2001 65 0.60 (5.01)*** -0.03 (-0.55) 39.53
Total 562 0.12(2.32)** -0.03 (-1.41) 1.68
ALLOCTj=β0+ β1PROCEEDSj+ β2SDIRj +vjALLOCTj = 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
Year N α1 t-value R2 (%)
1996 99 -54.94 -7.26* 24.13
1997 116 -55.34 -2.08** 5.51
1998 87 -137.92 -5.45* 26.88
1999 96 -130.50 -3.95* 15.33
2000 99 -154.72 -7.56* 29.33
2001 65 -183.49 -6.81* 41.54
Total 562 -87.84 -9.46* 17.99
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 returnAWIRj = ALLOCj * IRj - interestj
Hypothesis 3: adjusting for allocation and risk, uninformed investors earn zero abnormal returns
Lottery allocation involves risk so implies AWIR >0
30
0
10
20
30
40
50
60
70
80
0.0 0.5 1.0 1.5 2.0 2.5 3.0
23
57
65
60 60
52
46
29 29
13 13 12
8 12
10
3
8
3 4 3 1
6 4 4 3 4
2 2 2 2
Freq
uenc
y
Allocation weighted initial return (%)
9
13
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
129.15%
0.78%
27%
1%8.60%
5.14%8.70%
0%
11.99%
-1.18%
-20.00%
0.00%
20.00%
40.00%
60.00%
80.00%
100.00%
120.00%
140.00%
China Singapore UK Finland Israel
unweightedweighted
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
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!
35
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!
36