HK IPO Cross-Market Pattern Analysis
Based on AB-tier data from 264 stocks
Last 6 months (2025-11 ~ 2026-05) key metrics vs historical averages. Green = above historical, Red = below, Gray = similar.
Normal Market: Recent IPO performance is in line with historical averages. Standard participation strategy applies.
Stocks where A-tail (last A-tier) expected lots barely exceed or fall below B-head (first B-tier). Lower gap ratio = more anomalous tier structure.
Each dot represents one IPO. Higher oversubscription does not guarantee better first-day returns.
Based on registrar allotment file ID prefix analysis. Industry classification from prospectus details.
Industries with lower average hit rates tend to attract more speculative subscription behavior.
| # | Industry | Stocks | Avg. Hit Rate |
|---|---|---|---|
| 1 | 金融服务 | 1 | 80.8% |
| 2 | 智能驾驶 | 1 | 71.88% |
| 3 | 工业供应链技术与服务 | 1 | 54.23% |
| 4 | 半导体 | 4 | 52.88% |
| 5 | 家用电器 | 1 | 50.76% |
| 6 | 激光雷达 | 1 | 50.58% |
| 7 | 新能源材料 | 1 | 34.27% |
| 8 | 金融服务 | 1 | 33.63% |
| 9 | 汽车及出行 | 1 | 33.05% |
| 10 | 企业服务/软件 | 1 | 32.79% |
| 11 | 矿业资源 | 2 | 31.75% |
| 12 | 消费/餐饮 | 1 | 30.16% |
| 13 | 工业制造 | 3 | 28.97% |
| 14 | 新能源汽车 | 1 | 28.63% |
| 15 | 通信设备 | 1 | 26.75% |
| 16 | 人工智能 | 1 | 25.12% |
| 17 | 工业机器人 | 1 | 25.01% |
| 18 | 人工智能 | 4 | 24.66% |
| 19 | 数字孪生 | 1 | 23.62% |
| 20 | 消费/餐饮 | 1 | 22.12% |
| 21 | 半导体 | 4 | 21.66% |
| 22 | 人工智能 | 1 | 21.33% |
| 23 | 消费零售 | 7 | 20.57% |
| 24 | 工业制造 | 5 | 20.35% |
| 25 | CCUS | 1 | 20.04% |
| 26 | 汽车零部件 | 1 | 18.35% |
| 27 | 机器人科技 | 3 | 17.81% |
| 28 | 半导体 | 7 | 17.7% |
| 29 | 3D打印/消费电子/智能制造 | 1 | 17.64% |
| 30 | 自动驾驶 | 1 | 17.03% |
| 31 | 消费/餐饮 | 1 | 15.71% |
| 32 | 机器人科技 | 1 | 15.28% |
| 33 | 有色金属 | 1 | 14.02% |
| 34 | 生物医药 | 1 | 12.76% |
| 35 | 企业服务/软件 | 1 | 12.75% |
| 36 | 软件 | 1 | 11.84% |
| 37 | 企业服务/软件 | 2 | 11.18% |
| 38 | 智慧家庭 | 1 | 9.63% |
| 39 | 生物医药 | 11 | 8.59% |
| 40 | 医疗健康 | 3 | 7.92% |
| 41 | 人工智能 | 3 | 7.2% |
| 42 | 消费零售 | 3 | 6.42% |
| 43 | 生物医药 | 1 | 6.0% |
| 44 | 医疗器械 | 1 | 5.6% |
| 45 | 储能电池 | 1 | 5.37% |
| 46 | 医疗健康 | 2 | 5.09% |
| 47 | 教育 | 1 | 4.93% |
| 48 | 冷链物流 | 1 | 4.51% |
| 49 | 工业制造 | 4 | 4.1% |
| 50 | 消费零售 | 1 | 3.21% |
| 51 | 文旅演出 | 1 | 3.15% |
| 52 | 生物医药 | 2 | 2.72% |
| 53 | 物流包装 | 1 | 2.5% |
| 54 | 机电工程 | 1 | 1.19% |
| 55 | 化工新材料 | 1 | 0.0% |
| 56 | 医疗健康 | 1 | 0.0% |
| 57 | 商业物联网 | 1 | 0.0% |
| 58 | 土木工程 | 1 | 0.0% |
| 59 | 新能源 | 2 | 0.0% |
| 60 | 新能源 | 1 | 0.0% |
| 61 | 无线通信模组 | 1 | 0.0% |
| 62 | 汽车及出行 | 2 | 0.0% |
| 63 | 消费电子 | 2 | 0.0% |
| 64 | 生物医药 | 1 | 0.0% |
| 65 | 矿业资源 | 1 | 0.0% |
| 66 | 矿业资源 | 1 | 0.0% |
| 67 | 通信设备 | 1 | 0.0% |
Monthly IPO activity and average first-day returns. Helps identify hot vs cold IPO windows.
Box plot showing median, quartile, and range of subscription multiples by industry.
Each bubble is an IPO. X = oversubscription ratio (log), Y = market cap (log), bubble size = first-day return magnitude. Green = positive, red = negative. Scroll to zoom.
Industries where hot IPOs (>100x oversubscription) tend to perform differently from cold IPOs (<1x).
| # | Industry | Hot (>100x) | Hot Avg Return | Cold (<1x) | Cold Avg Return |
|---|---|---|---|---|---|
| 1 | 生物医药 | 14 | 90.67% | 0 | — |
| 2 | 半导体 | 9 | 82.98% | 0 | — |
| 3 | 工业制造 | 9 | 22.81% | 0 | — |
| 4 | 消费零售 | 9 | 48.35% | 0 | — |
| 5 | 人工智能 | 6 | 171.46% | 0 | — |
| 6 | 医疗健康 | 5 | 90.43% | 0 | — |
| 7 | 矿业资源 | 4 | 84.8% | 0 | — |
| 8 | 企业服务/软件 | 3 | 9.28% | 0 | — |
| 9 | 新能源 | 3 | 137.82% | 0 | — |
| 10 | 机器人科技 | 2 | 16.71% | 0 | — |
| 11 | 汽车及出行 | 2 | 28.69% | 0 | — |
| 12 | 消费/餐饮 | 2 | 6.1% | 0 | — |
How often does the public offer clawback trigger for each mechanism type, and does it correlate with first-day performance? Data based on HKEX allotment announcements.
| Mechanism | Total IPOs | Triggered | Trigger Rate | Avg Oversub | Avg Return (Triggered) | Avg Return (Non-Triggered) |
|---|---|---|---|---|---|---|
| 机制B | 122 | 1 (discretionary) | N/A (no clawback) | 2031.5x | 44.2% | 37.3% |
| 机制A(旧) | 41 | 41 | 100.0% | 573.4x | 7.3% | — |
| 18C特专科技 | 12 | 12 | 100.0% | 4606.8x | 98.3% | — |
| 机制A | 9 | 9 | 100.0% | 2746.1x | 58.8% | — |
Overall: 63/184 IPOs trigger clawback (34.2% trigger rate).
Do cornerstone-backed IPOs perform better? Comparing average first-day returns, win rates, and subscription levels between IPOs with and without cornerstone investors. Bubble size = return magnitude, green = positive, red = negative.
| Industry | With CS | With CS Ret | Without CS | Without CS Ret |
|---|---|---|---|---|
| Other | 94 | 9.86% | 27 | 3.92% |
| 人工智能 | 3 | 83.27% | 5 | 151.94% |
| 企业服务/软件 | 3 | 1.67% | 1 | 23.86% |
| 储能电池 | 1 | 31.29% | 0 | — |
| 冷链物流 | 1 | 0.33% | 0 | — |
| 化工新材料 | 0 | — | 1 | 4.03% |
| 医疗健康 | 3 | -1.73% | 3 | 135.96% |
| 医疗器械 | 0 | — | 1 | -8.57% |
| 半导体 | 6 | 84.13% | 7 | 35.86% |
| 商业物联网 | 1 | 241.11% | 0 | — |
| 土木工程 | 1 | 11.67% | 0 | — |
| 工业供应链技术与服务 | 1 | 0.0% | 0 | — |
Distribution of first-day returns across all IPOs with available data. Helps understand the typical range of IPO outcomes and tail risks. Red = loss buckets, green = profit buckets.
Grey market trading happens T-1 afternoon before official listing. Compare grey market performance with first-day official performance to assess predictive power. Higher correlation = stronger predictive signal.
Strong correlation — grey market strongly predicts first-day direction.
Grey up / First down: 119 | Grey down / First up: 82
Top 15 IPOs with the largest gap between grey market and first-day returns. Large gaps may indicate low grey market liquidity, information asymmetry, or sudden sentiment shifts.
| # | Stock | Grey Mkt % | First-Day % | Gap |
|---|---|---|---|---|
| 1 | BBSB International Limited (08610) | +415.0% | +11.67% | 403.3% |
| 2 | 森松國際控股有限公司 (02155) | +61.69% | +258.87% | 197.2% |
| 3 | 歐化國際有限公司 (01711) | +0.14% | +185.71% | 185.6% |
| 4 | 360 魯大師控股有限公司 (03601) | +38.89% | +218.52% | 179.6% |
| 5 | WAC Holdings Ltd. (08619) | +67.5% | +245.0% | 177.5% |
| 6 | 賓仕國際控股有限公司 (01705) | +127.0% | +298.0% | 171.0% |
| 7 | 日照港裕廊股份有限公司 - Ｈ股 (06117) | +3.33% | +166.67% | 163.3% |
| 8 | 金叶国际集团 (08549) | +476.0% | +330.0% | 146.0% |
| 9 | 毛記葵涌有限公司 (01716) | +575.0% | +431.67% | 143.3% |
| 10 | 天任集團控股有限公司 (01429) | +45.71% | +185.71% | 140.0% |
| 11 | 中國石墨集團有限公司 (02237) | +15.38% | +143.08% | 127.7% |
| 12 | 科利實業控股集團有限公司 (01455) | +102.5% | +230.0% | 127.5% |
| 13 | 邁科管業控股有限公司 (01553) | +117.11% | -5.7% | 122.8% |
| 14 | 中國優質能源集團有限公司 (01573) | +11.11% | +130.0% | 118.9% |
| 15 | 利特米 (01936) | +62.0% | +176.0% | 114.0% |
Annual IPO count, average first-day return, and win rate since 2010. Shows the bull/bear cycles of the HK IPO market. FINI platform launched Nov 2023, shortening settlement from T+5 to T+2.
| Year | IPO Count | Avg Return | Win Rate | Non-Negative % | Avg Oversub |
|---|---|---|---|---|---|
| 2010 | 74 | +7.56% | 62.2% | 66.2% | — |
| 2011 | 63 | +1.38% | 49.2% | 58.7% | — |
| 2012 | 45 | +4.58% | 55.6% | 73.3% | — |
| 2013 | 79 | +18.91% | 57.0% | 62.0% | — |
| 2014 | 102 | +51.75% | 64.7% | 68.6% | — |
| 2015 | 118 | +193.92% | 66.1% | 71.2% | — |
| 2016 | 115 | +214.92% | 73.9% | 83.5% | — |
| 2017 | 158 | +74.72% | 70.3% | 75.9% | — |
| 2018 | 205 | +15.83% | 58.0% | 67.3% | — |
| 2019 | 161 | +8.65% | 54.7% | 63.4% | — |
| 2020 | 144 | +18.19% | 60.4% | 66.7% | — |
| 2021 | 90 | +12.08% | 44.4% | 54.4% | — |
| 2022 | 75 | +7.1% | 40.0% | 64.0% | 0.4x |
| 2023 | 62 | +1.31% | 50.0% | 62.9% | 4.3x |
| 2024 | 64 | +5.72% | 57.8% | 62.5% | 314.6x |
| 2025 | 110 | +36.8% | 66.4% | 71.8% | 1639.9x |
| 2026 | 51 | +51.79% | 84.3% | 88.2% | 2003.5x |
IPO count, average first-day return, and win rate by calendar month. Reveals seasonal patterns in HK IPO market. December is typically the year-end IPO rush with highest volume; August is the summer lull with fewest IPOs but often higher returns.
| Month | IPO Count | Avg Return | Win Rate | Avg Oversub |
|---|---|---|---|---|
| Jan | 174 | +67.72% | 69.0% | 951.9x |
| Feb | 75 | +52.16% | 69.3% | 1322.3x |
| Mar | 142 | +22.64% | 56.3% | 992.2x |
| Apr | 82 | +74.26% | 64.6% | 886.6x |
| May | 103 | +42.18% | 68.9% | 1153.7x |
| Jun | 133 | +28.76% | 52.6% | 410.3x |
| Jul | 253 | +20.65% | 57.7% | 227.0x |
| Aug | 45 | +127.55% | 48.9% | 2262.2x |
| Sep | 105 | +65.75% | 64.8% | 675.8x |
| Oct | 166 | +92.37% | 65.1% | 1768.5x |
| Nov | 165 | +52.66% | 59.4% | 1103.2x |
| Dec | 273 | +29.23% | 53.8% | 757.1x |
Quarterly Summary:
| Quarter | IPO Count | Avg Return | Win Rate |
|---|---|---|---|
| Q1 | 391 | +48.36% | 64.5% |
| Q2 | 318 | +44.84% | 61.0% |
| Q3 | 403 | +44.34% | 58.6% |
| Q4 | 604 | +52.99% | 58.4% |
Analyzing characteristics of IPOs that fell below offer price on day one. Data shows moderate oversubscription (15-50x) has the HIGHEST loss rate (45.5%), while very high (>500x) has the lowest (16.1%). This contradicts the intuition that hotter IPOs are safer.
Risk alert: 15-50x oversubscription has highest loss rate (45.5%). IPOs in this range deserve more careful evaluation.
The most critical risk indicator. The 15-50x range has the highest loss rate — moderately hot IPOs often price too aggressively, leaving less upside for first-day trading.
| Subscription Range | IPO Count | Loss Count | Loss Rate |
|---|---|---|---|
| <1x (Under-subscribed) | 3 | 1 | 33.3% |
| 1x-15x (Moderate) | 44 | 13 | 29.5% |
| 15x-50x (Hot) | 33 | 15 | 45.5% |
| 50x-100x (Very Hot) | 16 | 7 | 43.8% |
| 100x-500x (Extremely Hot) | 47 | 12 | 25.5% |
| >500x (Mega Hot) | 87 | 14 | 16.1% |
| Mechanism | IPO Count | Loss Count | Loss Rate |
|---|---|---|---|
| 未分类 | 1397 | 449 | 32.1% |
| 未知 | 155 | 52 | 33.5% |
| 机制B | 109 | 23 | 21.1% |
| 机制A(旧) | 38 | 15 | 39.5% |
| 18C特专科技 | 10 | 1 | 10.0% |
| 机制A | 9 | 2 | 22.2% |
The 15 IPOs with the worst first-day returns. Use as extreme risk case reference.
| # | Stock | First-Day % | Avg Oversub | Mechanism |
|---|---|---|---|---|
| 1 | 大人国际 (01957) | -56.88% | — | 未分类 |
| 2 | 七牛智能 (02567) | -56.73% | 19.9x | 机制A(旧) |
| 3 | 多点数智 (02586) | -54.32% | 1.9x | 机制A(旧) |
| 4 | 马可数字科技 (01942) | -50.0% | — | 未分类 |
| 5 | 明基医院 (02581) | -49.46% | 6.3x | 机制B |
| 6 | 銅師傅 (00664) | -49.17% | 59.5x | 机制A |
| 7 | 中赣通信 (02545) | -46.4% | 196.0x | 机制A(旧) |
| 8 | Hygieia Group Limited (01650) | -46.4% | — | 未分类 |
| 9 | 翰思艾泰－Ｂ (03378) | -46.25% | 3074.1x | 机制B |
| 10 | 創陛控股有限公司 (02680) | -45.56% | — | 未分类 |
| 11 | 方舟健客 (06086) | -44.62% | 16.6x | 未知 |
| 12 | 淮北绿金股份 (02450) | -44.5% | — | 未知 |
| 13 | 潤利海事集團控股有限公司 (02682) | -44.0% | — | 未分类 |
| 14 | 優樂賽共享 (02649) | -43.64% | 5297.2x | 机制B |
| 15 | 蜆殼電業有限公司 (02381) | -43.6% | — | 未分类 |
6-month rolling average of core IPO market indicators. Tracks hot and cold market cycles to help time IPO participation. Data since 2010.
Current Temperature: 2026-01 ~ 2026-05 | Hot — 6-month rolling average of core IPO mark
| Month | Avg Return | Win Rate | IPOs | Temperature |
|---|---|---|---|---|
| 2026-05 | +45.38% | 73.7% | 76 | Hot |
| 2026-04 | +41.15% | 70.4% | 81 | Hot |
| 2026-03 | +40.65% | 70.2% | 84 | Hot |
| 2026-02 | +46.41% | 72.1% | 79 | Hot |
| 2026-01 | +52.03% | 72.6% | 73 | Hot |
| 2025-12 | +49.3% | 68.6% | 70 | Hot |
| 2025-11 | +48.35% | 75.0% | 60 | Hot |
| 2025-10 | +46.92% | 80.0% | 60 | Hot |
| 2025-09 | +36.08% | 78.4% | 51 | Hot |
| 2025-08 | +26.26% | 70.9% | 48 | Warm |
| 2025-07 | +15.32% | 65.9% | 44 | Warm |
| 2025-06 | +14.93% | 62.5% | 40 | Warm |
| 2025-05 | +12.65% | 68.6% | 35 | Warm |
| 2025-04 | +9.84% | 62.5% | 32 | Warm |
| 2025-03 | +3.51% | 56.8% | 37 | Cold |
| 2025-02 | +2.19% | 61.3% | 31 | Cold |
| 2025-01 | +1.99% | 63.7% | 33 | Cold |
| 2024-12 | -0.9% | 56.8% | 37 | Cold |
| 2024-11 | -1.45% | 44.4% | 36 | Cold |
| 2024-10 | +2.99% | 55.5% | 36 | Cold |
| 2024-09 | +4.66% | 54.8% | 31 | Cold |
| 2024-08 | +4.95% | 55.9% | 34 | Cold |
| 2024-07 | +8.52% | 52.8% | 36 | Warm |
| 2024-06 | +8.58% | 58.5% | 41 | Warm |
Annual standard deviation of first-day returns. High volatility means strong IPO performance divergence, low volatility indicates market consensus.
| Year | First-Day Std Dev | Grey Market Std Dev | IPOs | Regime |
|---|---|---|---|---|
| 2026 | ±79.31% | ±89.03% | 51 | High |
| 2025 | ±72.94% | ±75.01% | 110 | Normal |
| 2024 | ±36.01% | ±23.93% | 64 | Normal |
| 2023 | ±26.2% | ±25.59% | 62 | Normal |
| 2022 | ±36.87% | ±23.77% | 75 | Normal |
| 2021 | ±48.04% | ±33.74% | 90 | Normal |
| 2020 | ±52.58% | ±35.63% | 144 | Normal |
| 2019 | ±32.47% | ±24.91% | 161 | Normal |
| 2018 | ±51.68% | ±46.93% | 205 | Normal |
| 2017 | ±311.75% | ±24.36% | 158 | High |
| 2016 | ±434.04% | ±19.51% | 115 | High |
| 2015 | ±478.35% | ±13.51% | 118 | High |
| 2014 | ±134.78% | ±15.14% | 102 | High |
| 2013 | ±82.75% | ±14.63% | 79 | High |
| 2012 | ±13.63% | — | 45 | Low |
| 2011 | ±16.35% | — | 63 | Low |
| 2010 | ±18.31% | — | 74 | Low |
Combined share of top 10 allottees. High concentration = institutional control. Data shows medium concentration (50-75%) yields the best first-day returns.
Key finding: Concentration and first-day returns show an inverted U-shape. Medium concentration (50-75%) performs best — moderate institutional backing provides confidence without excessive control by a few players.
| Concentration | IPOs | Avg Return | Win Rate | Avg Oversub |
|---|---|---|---|---|
| Low (<50%) | 33 | +19.41% | 63.6% | 1540.4x |
| Moderate-Low (50-65%) | 46 | +60.91% | 78.3% | 1440.9x |
| Moderate-High (65-75%) | 33 | +28.83% | 72.7% | 1544.8x |
| High (>75%) | 79 | +20.83% | 65.8% | 968.6x |
Which cornerstone investors consistently pick winning IPOs? Ranking investors with ≥5 deals by average first-day return of the stocks they backed. Bubble size = total investment amount.
| # | Investor | Deals | Avg Return | Win Rate | Best Deal | Worst Deal | Total Invest (HKD eq.) |
|---|---|---|---|---|---|---|---|
| 1 | 富國資產管理(香港)有限公司 | 7 | +77.74% | 100.0% | 09606 (+116.7%) | 02788 (+32.76%) | 4.4B |
| 2 | TruMed | 5 | +74.3% | 100.0% | 09606 (+116.7%) | 06990 (+3.14%) | 4.4B |
| 3 | Invesco Advisers, Inc. | 6 | +67.4% | 66.7% | 06606 (+215.08%) | 02268 (-2.3%) | 40.8B |
| 4 | 匯添富基金管理股份有限公司 | 8 | +67.24% | 75.0% | 02155 (+258.87%) | 06669 (-26.05%) | 10.7B |
| 5 | Fidelity International | 15 | +61.1% | 100.0% | 01024 (+160.87%) | 06996 (+1.11%) | 75.4B |
| 6 | Cormorant Asset Management, LP | 10 | +60.73% | 100.0% | 06606 (+215.08%) | 06996 (+1.11%) | 10.0B |
| 7 | Rock Springs Capital Master Fund LP | 8 | +60.67% | 75.0% | 06606 (+215.08%) | 02126 (-7.56%) | 6.0B |
| 8 | Prime Capital Funds | 5 | +60.35% | 100.0% | 06969 (+150.0%) | 01801 (+18.6%) | 12.7B |
| 9 | Worldwide Healthcare Trust PLC | 6 | +58.79% | 100.0% | 06606 (+215.08%) | 01521 (+4.69%) | 11.3B |
| 10 | 富國基金管理有限公司 | 9 | +58.62% | 100.0% | 09606 (+116.7%) | 02768 (+4.03%) | 6.5B |
| 11 | LAV Amber Limited | 5 | +56.2% | 60.0% | 06606 (+215.08%) | 06628 (-17.25%) | 6.4B |
| 12 | 易方達基金管理有限公司 | 8 | +50.74% | 87.5% | 09606 (+116.7%) | 06669 (-26.05%) | 11.2B |
| 13 | 廣發國際資產管理有限公司 | 7 | +50.66% | 71.4% | 03858 (+177.84%) | 00638 (-11.72%) | 5.0B |
| 14 | BlackRock Funds | 16 | +50.58% | 81.2% | 01024 (+160.87%) | 02142 (-10.99%) | 85.9B |
| 15 | Mega Prime Development Limited | 10 | +48.0% | 80.0% | 02706 (+242.2%) | 01609 (-8.57%) | 5.3B |
| 16 | Perseverance Asset Management International (Singapore) Pte. Ltd. | 5 | +47.56% | 80.0% | 06656 (+103.42%) | 06669 (-26.05%) | 12.7B |
| 17 | Boyu Capital Opportunities Master Fund | 15 | +45.58% | 73.3% | 06606 (+215.08%) | 06609 (-24.56%) | 17.6B |
| 18 | China Orient Multi-Strategy Master Fund | 5 | +45.18% | 80.0% | 02158 (+147.91%) | 09666 (+0.0%) | 2.8B |
| 19 | 南方基金管理股份有限公司 | 8 | +43.93% | 62.5% | 06606 (+215.08%) | 02150 (-13.54%) | 6.8B |
| 20 | 盤京港景投資基金 | 5 | +43.04% | 60.0% | 09606 (+116.7%) | 06669 (-26.05%) | 2.5B |
| 21 | Lake Bleu Prime Healthcare Master Fund Limited | 23 | +42.64% | 69.6% | 06606 (+215.08%) | 06609 (-24.56%) | 37.1B |
| 22 | Octagon Investments Master Fund LP | 13 | +42.15% | 76.9% | 06606 (+215.08%) | 06609 (-24.56%) | 6.8B |
| 23 | 中國太保投資管理(香港)有限公司 | 5 | +41.73% | 60.0% | 06656 (+103.42%) | 00638 (-11.72%) | 4.0B |
| 24 | MY Asian Opportunities Master Fund, L.P. | 5 | +41.59% | 80.0% | 09606 (+116.7%) | 00470 (+0.0%) | 8.0B |
| 25 | Aranda Investments Pte. Ltd. | 7 | +40.08% | 57.1% | 01024 (+160.87%) | 06628 (-17.25%) | 33.1B |
| 26 | 泰康人壽 | 5 | +39.72% | 100.0% | 00100 (+109.09%) | 02525 (+9.96%) | 6.6B |
| 27 | 3W Funds | 14 | +39.67% | 64.3% | 06969 (+150.0%) | 06609 (-24.56%) | 13.7B |
| 28 | 泰康人壽保險有限責任公司 | 16 | +39.39% | 87.5% | 00068 (+144.09%) | 02050 (-0.13%) | 27.2B |
| 29 | 工銀理財有限責任公司 | 8 | +38.97% | 87.5% | 06656 (+103.42%) | 02050 (-0.13%) | 3.8B |
| 30 | Huang River Investment Limited | 6 | +38.12% | 66.7% | 09887 (+91.71%) | 01364 (-6.44%) | 15.5B |
Analysis limited to cornerstone investors with ≥5 tracked deals. Investment amounts in HKD equivalent (USD converted at ~7.8). Past performance of cornerstone investors does not guarantee future IPO results.
Which IPO sponsors (保荐人) consistently bring the best-performing IPOs to market? Ranking sponsors with ≥5 deals by average first-day return. Bubble size = number of deals. Green = positive avg return, Red = negative.
| # | Sponsor | Deals | Sole | Joint | Avg Return | Win Rate | Best Deal | Worst Deal |
|---|---|---|---|---|---|---|---|---|
| 1 | 上銀國際有限公司 | 5 | 4 | 1 | +814.41% | 80.0% | 08091 (+2937.04%) | 01612 (-6.0%) |
| 2 | 新源資本有限公司 | 5 | 4 | 1 | +494.63% | 80.0% | 08149 (+1170.59%) | 08547 (+0.0%) |
| 3 | 大有融資有限公司 | 24 | 24 | 0 | +434.56% | 87.5% | 08369 (+1900.0%) | 02682 (-44.0%) |
| 4 | 東皓資本有限公司 | 5 | 5 | 0 | +417.99% | 100.0% | 08411 (+2005.0%) | 08392 (+11.36%) |
| 5 | 天財資本國際有限公司 | 11 | 11 | 0 | +375.54% | 90.9% | 08182 (+1525.0%) | 08417 (-2.94%) |
| 6 | 浩德融資有限公司 | 16 | 15 | 1 | +242.73% | 75.0% | 08097 (+1556.0%) | 01346 (-27.06%) |
| 7 | 絡繹資本有限公司 | 7 | 6 | 1 | +217.23% | 85.7% | 08432 (+1296.55%) | 08523 (-20.0%) |
| 8 | 豐盛融資有限公司 | 41 | 40 | 1 | +205.8% | 82.9% | 08221 (+2033.33%) | 01660 (-22.5%) |
| 9 | 華富建業企業融資有限公司 | 16 | 15 | 1 | +191.4% | 93.8% | 08245 (+1145.61%) | 01522 (-27.0%) |
| 10 | 建泉融資有限公司 | 11 | 11 | 0 | +190.58% | 63.6% | 08290 (+2100.0%) | 06822 (-24.64%) |
| 11 | 富比資本有限公司 | 16 | 16 | 0 | +106.13% | 68.8% | 08240 (+1500.0%) | 08096 (-32.14%) |
| 12 | 派杰亞洲有限公司 | 18 | 15 | 3 | +95.08% | 61.1% | 08300 (+1166.67%) | 08511 (-23.85%) |
| 13 | 匯富融資有限公司 | 29 | 28 | 1 | +75.27% | 69.0% | 08133 (+965.0%) | 02187 (-29.33%) |
| 14 | 中國光大融資有限公司 | 37 | 29 | 8 | +71.95% | 64.9% | 08052 (+1900.0%) | 02450 (-44.5%) |
| 15 | 凱基金融亞洲有限公司 | 7 | 7 | 0 | +71.13% | 85.7% | 08349 (+388.57%) | 08353 (-18.92%) |
| 16 | 創升融資有限公司 | 32 | 29 | 3 | +65.01% | 71.9% | 08057 (+726.67%) | 02680 (-45.56%) |
| 17 | 力高企業融資有限公司 | 23 | 22 | 1 | +61.86% | 60.9% | 08035 (+851.22%) | 03938 (-36.31%) |
| 18 | 興業金融融資有限公司 | 11 | 11 | 0 | +61.23% | 54.5% | 08346 (+428.3%) | 01235 (-25.4%) |
| 19 | 鎧盛資本有限公司 | 12 | 9 | 3 | +56.98% | 66.7% | 08093 (+496.36%) | 00331 (-25.09%) |
| 20 | 創僑國際有限公司 | 13 | 12 | 1 | +51.84% | 69.2% | 08121 (+300.0%) | 02448 (-17.5%) |
| 21 | 域高融資有限公司 | 11 | 11 | 0 | +42.82% | 72.7% | 08027 (+170.0%) | 02263 (-20.0%) |
| 22 | 德健融資有限公司 | 24 | 24 | 0 | +41.36% | 79.2% | 08321 (+700.0%) | 01937 (-36.79%) |
| 23 | 八方金融有限公司 | 7 | 6 | 1 | +39.82% | 85.7% | 01711 (+185.71%) | 01536 (-8.7%) |
| 24 | 國泰君安融資有限公司 | 79 | 56 | 23 | +38.93% | 67.1% | 08127 (+966.67%) | 02230 (-31.11%) |
| 25 | 同人融資有限公司 | 21 | 21 | 0 | +34.35% | 76.2% | 08549 (+330.0%) | 01692 (-33.85%) |
| 26 | 浦銀國際融資有限公司 | 8 | 4 | 4 | +33.47% | 50.0% | 01384 (+150.56%) | 02512 (-17.39%) |
| 27 | 中毅資本有限公司 | 5 | 5 | 0 | +32.36% | 80.0% | 08659 (+90.0%) | 02147 (-17.65%) |
| 28 | 西證(香港)融資有限公司 | 12 | 12 | 0 | +29.68% | 66.7% | 02427 (+230.19%) | 01545 (-10.0%) |
| 29 | 東興證券(香港)有限公司 | 12 | 12 | 0 | +26.03% | 58.3% | 01695 (+158.33%) | 01156 (-28.57%) |
| 30 | 天泰金融服務有限公司 | 6 | 6 | 0 | +21.48% | 83.3% | 01872 (+46.51%) | 08208 (+0.0%) |
Analysis limited to sponsors with ≥5 tracked deals. Sole sponsor = sole IPO sponsor; Joint = joint IPO sponsor. IPO sponsors are responsible for due diligence and bringing the company to market. Past sponsor performance does not guarantee future IPO results.
Does having more banks in an IPO deal lead to better or worse first-day returns? Analysis of total syndicate size, lead manager count, and bookrunner count vs average return. Counterintuitive finding: smaller syndicates consistently outperform larger ones.
| Syndicate Size | IPOs | Avg Return | Median Return | Win Rate |
|---|---|---|---|---|
| 1-2 | 329 | +110.03% | +5.87% | 70.5% |
| 3-5 | 592 | +57.11% | +3.51% | 61.0% |
| 6-10 | 436 | +16.27% | +0.65% | 53.4% |
| 11-20 | 315 | +15.76% | +1.49% | 58.1% |
| 21+ | 34 | +26.36% | +0.81% | 61.8% |
| Syndicate Size | IPOs | Avg Return | Median Return | Win Rate |
|---|---|---|---|---|
| 1-2 | 514 | +99.98% | +5.79% | 69.6% |
| 3-5 | 467 | +41.85% | +2.51% | 58.2% |
| 6-10 | 423 | +12.52% | +0.74% | 55.3% |
| 11-20 | 231 | +12.49% | +0.45% | 52.4% |
| 21+ | 8 | +22.4% | +1.07% | 75.0% |
| Syndicate Size | IPOs | Avg Return | Median Return | Win Rate |
|---|---|---|---|---|
| 1-2 | 680 | +86.08% | +5.74% | 68.8% |
| 3-5 | 438 | +16.93% | +0.48% | 52.3% |
| 6-10 | 368 | +13.5% | +0.76% | 55.2% |
| 11-20 | 166 | +10.42% | +0.34% | 52.4% |
| 21+ | 5 | -10.13% | +0.21% | 60.0% |
Syndicate = all banks/firms participating in an IPO deal. Lead managers (牵头经办人) are mid-tier syndicate members responsible for distribution. Bookrunners (账簿管理人) handle order book and pricing. The inverse relationship likely reflects that larger syndicates are typical for mega-IPOs which are already 'fully priced' with limited upside, while smaller syndicates serve small-cap IPOs with more room for first-day pops. Past patterns do not predict future outcomes.
HKEX launched the FINI platform in November 2023, reducing IPO settlement from T+5 to T+2 and lowering funding costs for investors. How did this regulatory change impact IPO first-day returns, win rates, and market activity?
| Metric | Pre-FINI | Post-FINI | Change |
|---|---|---|---|
| IPO Count | 1470 | 246 | -1224 |
| Avg Return | 51.62% | 29.08% | -22.5% |
| Median Return | 2.29% | 5.26% | +3.0% |
| Win Rate | 59.2% | 67.1% | +7.9% |
| Volatility (Std Dev) | 225.23% | 65.93% | -159.3% |
| Avg Oversubscription | 12.0x | 1328.8x | +1316.8x |
| Monthly Avg IPOs | 9.2/mo | 8.2/mo | -1.0/mo |
FINI (Fast Interface for New Issuance) launched 2023-11-22. Key changes: T+5 to T+2 settlement cycle, fully electronic IPO process, reduced funding cost for margin subscribers. Pre-FINI covers all IPOs before Nov 2023; Post-FINI covers Nov 2023 onwards. Past performance does not predict future outcomes.
Multi-factor correlation analysis: which factors are most predictive of first-day IPO returns? Pearson correlation coefficient (r) measures linear relationship strength. r > 0 = positive predictor, r < 0 = negative predictor. |r| > 0.3 = strong, |r| > 0.1 = moderate.
| # | Factor | Correlation (r) | Strength | Direction | Samples |
|---|---|---|---|---|---|
| 1 | Grey Market Premium | 0.7907 | Strong | Positive | 1346 |
| 2 | Oversubscription Ratio | 0.4511 | Strong | Positive | 229 |
| 3 | Application Count | 0.3862 | Strong | Positive | 232 |
| 4 | Cornerstone Presence | -0.1529 | Moderate | Negative | 1716 |
| 5 | Syndicate Size | -0.1259 | Moderate | Negative | 1704 |
| 6 | Public Allocation Ratio | -0.0337 | Weak | Negative | 136 |
| 7 | Greenshoe Presence | -0.0022 | Weak | Negative | 1716 |
Correlation does not equal causation. Grey market premium is the strongest signal because it reflects near-real-time market pricing. Oversubscription and application count are sentiment proxies. Cornerstone presence is negatively correlated — cornerstone-backed IPOs have lower average returns (likely because they are more mature, larger, with limited upside). Greenshoe presence shows near-zero correlation with returns (r≈0) — confirming the D22 finding that the apparent greenshoe premium is entirely a size effect. Past patterns do not guarantee future outcomes.
Does a shorter offer period signal stronger demand? Analyzing the relationship between offer period length, first-day returns, and oversubscription ratios.
| Offer Period | IPO Count | Avg Return | Median Return | Win Rate | Std Dev | Avg Oversub |
|---|---|---|---|---|---|---|
| Short (1-3 days) | 43 | 52.1% | 6.4% | 67.4% | 97.11% | 2051.2x |
| Standard (4 days) | 4 | 43.03% | 22.7% | 75.0% | 58.55% | 2197.9x |
| Extended (5-6 days) | 83 | 44.22% | 24.66% | 74.7% | 72.64% | 1860.5x |
| Ultra-long (7+ days) | 8 | 10.93% | 6.22% | 75.0% | 40.97% | 2745.8x |
Offer period is measured in calendar days from offer_period_start to offer_period_end per the prospectus. Standard HK IPO offer windows are 3-6 days; some extend due to holidays or market arrangements. Shorter windows typically indicate strong bookbuilding demand and underwriter confidence. Past patterns do not guarantee future outcomes.
Do smaller IPOs deliver bigger first-day pops? Analyzing the relationship between market capitalization at IPO, first-day returns, and oversubscription. Testing the small-cap effect in HK IPOs.
| Market Cap Range | Count | Avg Return | Median | Win Rate | Std Dev | Avg Oversub |
|---|---|---|---|---|---|---|
| Small (<2B) | 9 | 70.73% | 7.61% | 77.8% | 134.35% | 5088.0x |
| Mid (2-10B) | 41 | 73.89% | 86.7% | 78.0% | 89.06% | 3227.3x |
| Large (10-50B) | 44 | 38.05% | 7.42% | 68.2% | 79.92% | 1275.8x |
| Mega (>50B) | 15 | 35.37% | 13.26% | 86.7% | 39.4% | 598.1x |
Market cap = offer price x total post-IPO shares per prospectus. A clear small-cap effect exists in HK IPO first-day returns: smaller floats offer greater upside potential due to limited float, high retail participation, and wider pricing uncertainty. Mega-cap IPOs have higher win rates but limited upside due to fuller pricing and institutional dominance. Past patterns do not guarantee future outcomes.
The greenshoe (over-allotment option) allows underwriters to sell up to 15% additional shares for price stabilization. Do greenshoe IPOs perform better? Raw numbers say yes — but size-adjusted analysis reveals the opposite.
| Metric | With Greenshoe | Without Greenshoe | Spread |
|---|---|---|---|
| IPO Count | 86 | 95 | -9 |
| Avg Return | 46.22% | 28.51% | +17.7% |
| Median Return | 13.41% | 5.07% | +8.3% |
| Win Rate | 72.1% | 67.4% | +4.7% |
| Std Dev | 82.93% | 61.43% | +21.5% |
| Avg Oversub | 2082.4x | 1293.9x | +788.5x |
| Market Cap Range | With Greenshoe (#) | With Greenshoe (%) | Without Greenshoe (#) | Without Greenshoe (%) | Spread |
|---|---|---|---|---|---|
| Small (<2B) | 6 | 46.0% | 3 | 120.2% | -74.2pp |
| Mid (2-10B) | 27 | 73.3% | 14 | 74.9% | -1.6pp |
| Large (10-50B) | 35 | 31.5% | 9 | 63.3% | -31.8pp |
| Mega (>50B) | 15 | 35.4% | 0 | — | — |
The greenshoe option allows underwriters to purchase up to 15% additional shares at the offer price within 30 days of listing. Dual purpose: (1) price stabilization — underwriters can buy back shares to support the price; (2) meet excess demand. Greenshoe IPOs are predominantly larger deals, so raw comparisons are heavily confounded by the size effect. Past patterns do not guarantee future outcomes.
