Korea / Special Situations, Clepsydra Capital

Sanghyun Park

Korea / Special Situations

Korea / Special Sits, Pairs, Index Rebalancing

Clepsydra Capital

Investigate special situations, pairs, and index rebalancing trades in Korea.

Event-Driven

<p>Starting this year, KRX will rebalance the KOSPI size index series (LargeCap, MidCap, and SmallCap) twice a year. Until last year, it was done once a year in March (the option expiration date). <span>However, from this year, the rebalancing is done twice a year, in March and September.</span></p><div class="content-highlight"><ul>
<li><strong>The screening method is simple and clear. It is based on the 3-month average daily market cap.</strong></li>
<li><strong>LargeCap includes 1st to 100th, and MidCap takes 101st to 300th.</strong></li>
<li><strong>The screening base date is the last trading day of February and August. So, this September rebalancing review period is June 1 to August 31.</strong></li>
</ul></div><section class="figure"><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/227/642/original/Screen+Shot+2021-09-02+at+10.06.47+PM.png?1630634901" class="editor-image img-responsive" data-smartkarma-image-id="227642"></figure></section>

Starting this year, KRX will rebalance the KOSPI size index series (LargeCap, MidCap, and SmallCap) twice a year. Until last year, it was done once a year in March (the option expiration date). However, from this year, the rebalancing is done twice a year, in March and September.
The screening method is simple and clear. It is based on the 3-month average daily market cap.
LargeCap includes 1st to 100th, and MidCap takes 101st to 300th.
The screening base date is the last trading day of February and August. So, this September rebalancing review period is June 1 to August 31.


KOSPI LargeCap & MidCap Rebalancing Preview on September 9

Korea/Asia, Events, IPOs, Douglas Research Advisory

Douglas Kim

Korea/Asia, Events, IPOs

Equity Bottom-Up

<p><strong>In this insight, we provide an NAV valuation sensitivity analysis of SK Chemicals. SK Chemicals has an 68.4% stake in <a href="https://www.smartkarma.com/entities/sk-bioscience-co-ltd" target="_blank" data-smartkarma-citation="entities:31484:1" rel="noopener">SK Bioscience (302440 KS)</a> which is worth 17.6 trillion won versus SK Chemicals' current market cap of 3.4 trillion won. </strong></p><ul>
<li>In Case A, we used the current market value of SK Bioscience. In the NAV analysis Case A, it suggests a target price of 766,134 won, which is 168% higher than current price.</li>
<li>In Case B, we used the average of the high/low value of SK Bioscience's share price in the past five months. In the NAV analysis Case B, it suggests a target price of 546,265 won, which is 91% higher than the current price.</li>
<li>In Case C, we used the low price of SK Bioscience in the past five months. In the NAV analysis Case C, it suggests a target price of 267,389 won, which is 6.5% lower than the current price.</li>
</ul><div class="content-highlight">
<p>Clearly, SK Chemicals is trading at a steep discount to its NAV. Part of this reason may be because the market may not be fully willing to reflect SK Bioscience's current market value on its controlling stake. Since its IPO in March 2021, SK Bioscience has been a huge winner and it has also vastly outperformed against SK Chemicals.</p>
<p>However, there appears to be too much valuation gap between these two companies and in the coming months, we believe that there is a higher probability of SK Chemicals outperforming versus SK Bioscience, especially as the value investors try to pick up on SK Chemicals whose market cap is only 19% of its stake in SK Bioscience. </p>
</div>

In this insight, we provide an NAV valuation sensitivity analysis of SK Chemicals. SK Chemicals has an 68.4% stake in SK Bioscience (302440 KS) which is worth 17.6 trillion won versus SK Chemicals' current market cap of 3.4 trillion won. 
In Case A, we used the current market value of SK Bioscience. In the NAV analysis Case A, it suggests a target price of 766,134 won, which is 168% higher than current price.
In Case B, we used the average of the high/low value of SK Bioscience's share price in the past five months. In the NAV analysis Case B, it suggests a target price of 546,265 won, which is 91% higher than the current price.
In Case C, we used the low price of SK Bioscience in the past five months. In the NAV analysis Case C, it suggests a target price of 267,389 won, which is 6.5% lower than the current price.

Clearly, SK Chemicals is trading at a steep discount to its NAV. Part of this reason may be because the market may not be fully willing to reflect SK Bioscience's current market value on its controlling stake. Since its IPO in March 2021, SK Bioscience has been a huge winner and it has also vastly outperformed against SK Chemicals.
However, there appears to be too much valuation gap between these two companies and in the coming months, we believe that there is a higher probability of SK Chemicals outperforming versus SK Bioscience, especially as the value investors try to pick up on SK Chemicals whose market cap is only 19% of its stake in SK Bioscience. 


SK Chemicals - Its Market Cap Is Only 19% of Its Stake in SK Bioscience

Pan-Asia Index Rebalances/ Events/ Delta One, Periscope Analytics

Brian Freitas

Pan-Asia Index Rebalances/ Events/ Delta One

Quantitative Analysis

<div><p>The Asia Short Interest weekly looks at moves in market wide short interest and highlights movements in stock specific short interest across Hong Kong, Japan, Korea and Taiwan using the last available data published by the relevant authorities.</p></div><div><p>Hong Kong saw shorts rise on <a href="https://www.smartkarma.com/entities/alibaba-group" target="_blank" data-smartkarma-citation="entities:28434:1" rel="noopener">Alibaba Group (9988 HK)</a>, <a href="https://www.smartkarma.com/entities/byd-co-ltd-h" target="_blank" data-smartkarma-citation="entities:20962:1" rel="noopener">BYD (1211 HK)</a>, <a href="https://www.smartkarma.com/entities/aia-group-ltd" target="_blank" data-smartkarma-citation="entities:14895:1" rel="noopener">AIA Group Ltd (1299 HK)</a>, <a href="https://www.smartkarma.com/entities/xiaomi-corp" target="_blank" data-smartkarma-citation="entities:24409:1" rel="noopener">Xiaomi Corp (1810 HK)</a> and <a href="https://www.smartkarma.com/entities/byd-electronic-international-co-ltd" target="_blank" data-smartkarma-citation="entities:1927:1" rel="noopener">BYD Electronics (285 HK)</a> while there was short covering on <a href="https://www.smartkarma.com/entities/ping-an-insurance-grp-co-of-china-ltd" target="_blank" data-smartkarma-citation="entities:12880:1" rel="noopener">Ping An Insurance (H) (2318 HK)</a>, <a href="https://www.smartkarma.com/entities/country-garden-services-holdings-company-limited" target="_blank" data-smartkarma-citation="entities:27343:1" rel="noopener">Country Garden Services Holdings (6098 HK)</a>, <a href="https://www.smartkarma.com/entities/meituan-dianping" target="_blank" data-smartkarma-citation="entities:26970:1" rel="noopener">Meituan (3690 HK)</a>, <a href="https://www.smartkarma.com/entities/postal-savings-bank-of-china" target="_blank" data-smartkarma-citation="entities:22848:1" rel="noopener">Postal Savings Bank of China (1658 HK)</a> and <a href="https://www.smartkarma.com/entities/citic-securities-h" target="_blank" data-smartkarma-citation="entities:463:1" rel="noopener">Citic Securities (H) (6030 HK)</a>. Shorts increased in the Consumer Discretionary, Information Technology, Health Care and Communication Services sectors, and decreased in the Financials and Industrials sectors.</p></div><div><p>In Japan, stocks that saw the most shorts were <a href="https://www.smartkarma.com/entities/toshiba-corp" target="_blank" data-smartkarma-citation="entities:637:1" rel="noopener">Toshiba Corp (6502 JP)</a>, <a href="https://www.smartkarma.com/entities/cosmos-pharmaceutical-corp" target="_blank" data-smartkarma-citation="entities:3797:1" rel="noopener">Cosmos Pharmaceutical (3349 JP)</a>, <a href="https://www.smartkarma.com/entities/rakus-co-ltd" target="_blank" data-smartkarma-citation="entities:29200:1" rel="noopener">Rakus Co Ltd (3923 JP)</a>, <a href="https://www.smartkarma.com/entities/daito-trust-construct-co-ltd" target="_blank" data-smartkarma-citation="entities:10503:1" rel="noopener">Daito Trust Construct (1878 JP)</a> and <a href="https://www.smartkarma.com/entities/aeon-financial-service-co-ltd" target="_blank" data-smartkarma-citation="entities:5887:1" rel="noopener">Aeon Financial (8570 JP)</a> while shorts decreased on <a href="https://www.smartkarma.com/entities/ryohin-keikaku-co-ltd" target="_blank" data-smartkarma-citation="entities:2765:1" rel="noopener">Ryohin Keikaku (7453 JP)</a>, <a href="https://www.smartkarma.com/entities/aeon-co-ltd" target="_blank" data-smartkarma-citation="entities:3:1" rel="noopener">Aeon Co Ltd (8267 JP)</a>, <a href="https://www.smartkarma.com/entities/lasertec-corp" target="_blank" data-smartkarma-citation="entities:4126:1" rel="noopener">Lasertec Corp (6920 JP)</a>, <a href="https://www.smartkarma.com/entities/isetan-mitsukoshi-holdings-ltd" target="_blank" data-smartkarma-citation="entities:18871:1" rel="noopener">Isetan Mitsukoshi Holdings Ltd (3099 JP)</a> and <a href="https://www.smartkarma.com/entities/mitsui-mining-smelting-co" target="_blank" data-smartkarma-citation="entities:15998:1" rel="noopener">Mitsui Mining &amp; Smelting Co (5706 JP)</a>. Shorts increased in the Industrials and Financials sectors, and decreased in the Consumer Discretionary sector.</p></div><div>
<p>Short selling finally resumed in Korea this week. Shorts increased on <a href="https://www.smartkarma.com/entities/celltrion-inc" target="_blank" data-smartkarma-citation="entities:991:1" rel="noopener">Celltrion Inc (068270 KS)</a>, <a href="https://www.smartkarma.com/entities/lg-display-co-ltd" target="_blank" data-smartkarma-citation="entities:7145:1" rel="noopener">LG Display (034220 KS)</a>, <a href="https://www.smartkarma.com/entities/sk-hynix-inc" target="_blank" data-smartkarma-citation="entities:16955:1" rel="noopener">SK Hynix (000660 KS)</a>, <a href="https://www.smartkarma.com/entities/netmarble-corporation" target="_blank" data-smartkarma-citation="entities:22839:1" rel="noopener">Netmarble Corporation (251270 KS)</a> and <a href="https://www.smartkarma.com/entities/naver-corp" target="_blank" data-smartkarma-citation="entities:16029:1" rel="noopener">Naver Corp (035420 KS)</a>. The largest percentage increase in shorts was seen on <a href="https://www.smartkarma.com/entities/hyundai-rotem-company" target="_blank" data-smartkarma-citation="entities:1554:1" rel="noopener">Hyundai Rotem Company (064350 KS)</a>, <a href="https://www.smartkarma.com/entities/sk-chemicals-co-ltd-new" target="_blank" data-smartkarma-citation="entities:26190:1" rel="noopener">Sk Chemicals Co Ltd/New (285130 KS)</a>, <a href="https://www.smartkarma.com/entities/daewoo-shipbuilding-marine-engineering" target="_blank" data-smartkarma-citation="entities:12531:1" rel="noopener">Daewoo Shipbuilding &amp; Marine Engineering (042660 KS)</a> and <a href="https://www.smartkarma.com/entities/e-mart-inc" target="_blank" data-smartkarma-citation="entities:6993:1" rel="noopener">E Mart Inc (139480 KS)</a>.</p>
<p>In Taiwan, shorts increased on <a href="https://www.smartkarma.com/entities/novatek-microelectronics-corp" target="_blank" data-smartkarma-citation="entities:10904:1" rel="noopener">Novatek Microelectronics Corp (3034 TT)</a>, <a href="https://www.smartkarma.com/entities/yang-ming-marine-transport" target="_blank" data-smartkarma-citation="entities:8502:1" rel="noopener">Yang Ming Marine Transport (2609 TT)</a>, <a href="https://www.smartkarma.com/entities/taiwan-cement" target="_blank" data-smartkarma-citation="entities:19736:1" rel="noopener">Taiwan Cement (1101 TT)</a>, <a href="https://www.smartkarma.com/entities/au-optronics-corp" target="_blank" data-smartkarma-citation="entities:6704:1" rel="noopener">AU Optronics (2409 TT)</a> and <a href="https://www.smartkarma.com/entities/mediatek-inc" target="_blank" data-smartkarma-citation="entities:772:1" rel="noopener">Mediatek Inc (2454 TT)</a>, while shorts covered on <a href="https://www.smartkarma.com/entities/wisdom-marine-lines-co-ltd" target="_blank" data-smartkarma-citation="entities:10001:1" rel="noopener">Wisdom Marine Lines (2637 TT)</a>, <a href="https://www.smartkarma.com/entities/wiwynn-corp" target="_blank" data-smartkarma-citation="entities:27838:1" rel="noopener">Wiwynn Corp (6669 TT)</a>, <a href="https://www.smartkarma.com/entities/richwave-technology-corp" target="_blank" data-smartkarma-citation="entities:18629:1" rel="noopener">Richwave Technology (4968 TT)</a>, <a href="https://www.smartkarma.com/entities/hon-hai-precision-industry-co-ltd" target="_blank" data-smartkarma-citation="entities:745:1" rel="noopener">Hon Hai Precision Industry (2317 TT)</a> and <a href="https://www.smartkarma.com/entities/hannstar-display-corp" target="_blank" data-smartkarma-citation="entities:13922:1" rel="noopener">Hannstar Display (6116 TT)</a>. </p>
</div>

The Asia Short Interest weekly looks at moves in market wide short interest and highlights movements in stock specific short interest across Hong Kong, Japan, Korea and Taiwan using the last available data published by the relevant authorities.Hong Kong saw shorts rise on Alibaba Group (9988 HK), BYD (1211 HK), AIA Group Ltd (1299 HK), Xiaomi Corp (1810 HK) and BYD Electronics (285 HK) while there was short covering on Ping An Insurance (H) (2318 HK), Country Garden Services Holdings (6098 HK), Meituan (3690 HK), Postal Savings Bank of China (1658 HK) and Citic Securities (H) (6030 HK). Shorts increased in the Consumer Discretionary, Information Technology, Health Care and Communication Services sectors, and decreased in the Financials and Industrials sectors.In Japan, stocks that saw the most shorts were Toshiba Corp (6502 JP), Cosmos Pharmaceutical (3349 JP), Rakus Co Ltd (3923 JP), Daito Trust Construct (1878 JP) and Aeon Financial (8570 JP) while shorts decreased on Ryohin Keikaku (7453 JP), Aeon Co Ltd (8267 JP), Lasertec Corp (6920 JP), Isetan Mitsukoshi Holdings Ltd (3099 JP) and Mitsui Mining &amp; Smelting Co (5706 JP). Shorts increased in the Industrials and Financials sectors, and decreased in the Consumer Discretionary sector.
Short selling finally resumed in Korea this week. Shorts increased on Celltrion Inc (068270 KS), LG Display (034220 KS), SK Hynix (000660 KS), Netmarble Corporation (251270 KS) and Naver Corp (035420 KS). The largest percentage increase in shorts was seen on Hyundai Rotem Company (064350 KS), Sk Chemicals Co Ltd/New (285130 KS), Daewoo Shipbuilding &amp; Marine Engineering (042660 KS) and E Mart Inc (139480 KS).
In Taiwan, shorts increased on Novatek Microelectronics Corp (3034 TT), Yang Ming Marine Transport (2609 TT), Taiwan Cement (1101 TT), AU Optronics (2409 TT) and Mediatek Inc (2454 TT), while shorts covered on Wisdom Marine Lines (2637 TT), Wiwynn Corp (6669 TT), Richwave Technology (4968 TT), Hon Hai Precision Industry (2317 TT) and Hannstar Display (6116 TT). 


Asia Shorts: BYD, Ping An, Toshiba, Rakus, Aeon, Celltrion, LG Display, SK Chem, Novatek, Yang Ming

<p><a href="https://www.smartkarma.com/entities/sk-bioscience-co-ltd" target="_blank" data-smartkarma-citation="entities:31484:1" rel="noopener">SK Bioscience (302440 KS)</a> is a biopharmaceutical company that focuses on the discovery and production of vaccines. The company was spun off from <a href="https://www.smartkarma.com/entities/sk-chemicals-co-ltd-new" target="_blank" data-smartkarma-citation="entities:26190:1" rel="noopener">Sk Chemicals Co Ltd/New (285130 KS)</a> in 2018 and is now 68.65% owned by SK Chemicals.</p><p>The company issued stock at KRW 65,000/share in the IPO and the stock closed limit up at KRW 169,000 on listing day. Since then, the stock has dropped 30% and is trading at the lows since listing. The stock has been stable over the last few days as volumes taper off and a lot of flippers have likely exited the stock.</p><p>With 2 days to go in the 15 day period that is used to determine Fast Entry for new listings in the <a href="https://www.smartkarma.com/entities/korea-stock-exchange-kospi-200-index" target="_blank" data-smartkarma-citation="entities:26021:1" rel="noopener">Korea Stock Exchange Kospi 200 Index (KOSPI2 INDEX)</a>, we take a look at the probability of the stock getting Fast Entry into the index, the lock up expiry schedule and the impact of passive buying on the stock.</p><p>If included in the index, passive trackers will need to buy over 4% of the free floating <a href="https://www.smartkarma.com/entities/sk-bioscience-co-ltd" target="_blank" data-smartkarma-citation="entities:31484:1" rel="noopener">SK Bioscience (302440 KS)</a> stock as of the implementation date. We see <a href="https://www.smartkarma.com/entities/sebang-global-battery-co-ltd" target="_blank" data-smartkarma-citation="entities:9618:1" rel="noopener">Sebang Global Battery (004490 KS)</a> as the most likely deletion to make way for SK Bioscience in the index.</p>

SK Bioscience (302440 KS) is a biopharmaceutical company that focuses on the discovery and production of vaccines. The company was spun off from Sk Chemicals Co Ltd/New (285130 KS) in 2018 and is now 68.65% owned by SK Chemicals.The company issued stock at KRW 65,000/share in the IPO and the stock closed limit up at KRW 169,000 on listing day. Since then, the stock has dropped 30% and is trading at the lows since listing. The stock has been stable over the last few days as volumes taper off and a lot of flippers have likely exited the stock.With 2 days to go in the 15 day period that is used to determine Fast Entry for new listings in the Korea Stock Exchange Kospi 200 Index (KOSPI2 INDEX), we take a look at the probability of the stock getting Fast Entry into the index, the lock up expiry schedule and the impact of passive buying on the stock.If included in the index, passive trackers will need to buy over 4% of the free floating SK Bioscience (302440 KS) stock as of the implementation date. We see Sebang Global Battery (004490 KS) as the most likely deletion to make way for SK Bioscience in the index.

SK Bioscience IPO: KOSPI200 Fast Entry Guaranteed; SGBC Most Likely Deletion

Equity Capital Markets

<p>Below is the final allocation.</p><table class="table table-striped">
<colgroup>
<col width="70">
<col width="70">
<col width="70">
<col width="70">
<col width="70">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Type"}'>Type</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Initial"}'>Initial</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Subscription"}'>Subscription</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Allocation"}'>Allocation</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"%"}'>%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"ESOP"}'>ESOP</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":4590000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>4,590,000</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":4490400}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>4,490,400</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":4490400}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>4,490,400</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.1957}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}'>19.57%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Institutional"}'>Institutional</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":12622500}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>12,622,500</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":12622500}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>12,622,500</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":12622500}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>12,622,500</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.55}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}'>55.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Retail"}'>Retail</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":5737500}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>5,737,500</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1957531110}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>1,957,531,110</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":5837100}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>5,837,100</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.2543}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}'>25.43%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Total"}'>Total</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":22950000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=sum(R[-3]C[0]:R[-1]C[0])">22,950,000</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1974644010}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>1,974,644,010</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":22950000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=sum(R[-3]C[0]:R[-1]C[0])">22,950,000</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(R[-3]C[0]:R[-1]C[0])">100.00%</td>
</tr>
<tr><td colspan="5" rowspan="1" data-sheets-value='{"1":2,"2":"Source: DART"}'>Source: DART</td></tr>
</tbody>
</table><p>Below is the lockup pledge as a % of subscriptions.</p><p>Nearly 60% subscribed without lockup pledge.</p><table class="table table-striped">
<colgroup>
<col width="70">
<col width="70">
<col width="70">
</colgroup>
<tbody>
<tr>
<td style="width: 214.545px;" data-sheets-value='{"1":2,"2":"Lockup"}'>Lockup</td>
<td style="text-align: right; width: 185.455px;" data-sheets-value='{"1":2,"2":"Qty."}'>Qty.</td>
<td style="text-align: right; width: 163.636px;" data-sheets-value='{"1":2,"2":"% of subsc"}'>% of subscription</td>
</tr>
<tr>
<td style="width: 214.545px;" data-sheets-value='{"1":2,"2":"6 months"}'>6 months</td>
<td style="text-align: right; width: 185.455px;" data-sheets-value='{"1":3,"3":2194034000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>2,194,034,000</td>
<td style="text-align: right; width: 163.636px;" data-sheets-value='{"1":3,"3":0.13627910091946424}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R53C2">13.63%</td>
</tr>
<tr>
<td style="width: 214.545px;" data-sheets-value='{"1":2,"2":"3 months"}'>3 months</td>
<td style="text-align: right; width: 185.455px;" data-sheets-value='{"1":3,"3":3595764000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>3,595,764,000</td>
<td style="text-align: right; width: 163.636px;" data-sheets-value='{"1":3,"3":0.22334543814661778}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R53C2">22.33%</td>
</tr>
<tr>
<td style="width: 214.545px;" data-sheets-value='{"1":2,"2":"1 month"}'>1 month</td>
<td style="text-align: right; width: 185.455px;" data-sheets-value='{"1":3,"3":3246456500}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>3,246,456,500</td>
<td style="text-align: right; width: 163.636px;" data-sheets-value='{"1":3,"3":0.20164873151197776}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R53C2">20.16%</td>
</tr>
<tr>
<td style="width: 214.545px;" data-sheets-value='{"1":2,"2":"15 days"}'>15 days</td>
<td style="text-align: right; width: 185.455px;" data-sheets-value='{"1":3,"3":610574000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>610,574,000</td>
<td style="text-align: right; width: 163.636px;" data-sheets-value='{"1":3,"3":0.03792487981717738}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R53C2">3.79%</td>
</tr>
<tr>
<td style="width: 214.545px;" data-sheets-value='{"1":2,"2":"None"}'>None</td>
<td style="text-align: right; width: 185.455px;" data-sheets-value='{"1":3,"3":9646828500}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>9,646,828,500</td>
<td style="text-align: right; width: 163.636px;" data-sheets-value='{"1":3,"3":0.5991981503952372}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R53C2">59.92%</td>
</tr>
<tr>
<td style="width: 214.545px;" data-sheets-value='{"1":2,"2":"Total"}'>Total</td>
<td style="text-align: right; width: 185.455px;" data-sheets-value='{"1":3,"3":16099563214}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>16,099,563,214</td>
<td style="text-align: right; width: 163.636px;" data-sheets-value='{"1":3,"3":1}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R53C2">100.00%</td>
</tr>
<tr><td colspan="3" rowspan="1" style="width: 605.455px;" data-sheets-value='{"1":2,"2":"Source: DART"}'>Source: DART</td></tr>
</tbody>
</table><p>A little surprisingly, 85% of the allocation went to lockup pledgers.</p><p>What can be deducted from it? It indicates that this IPO may have attracted more long-term investors than what we usually see from Korea's local IPOs.</p><table class="table table-striped">
<colgroup>
<col width="70">
<col width="70">
<col width="70">
<col width="70">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Lockup"}'>Lockup</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Qty."}'>Qty.</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"% of alloc"}'>% of allocation</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"% of SO"}'>% of SO</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"6 months"}'>6 months</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":3948100}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>3,948,100</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.3127827292533175}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R14C2">31.28%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.05160915032679739}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-2]/R28C2">5.16%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"3 months"}'>3 months</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":3331000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>3,331,000</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.2638938403644286}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R14C2">26.39%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.04354248366013072}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-2]/R28C2">4.35%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1 month"}'>1 month</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":3118610}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>3,118,610</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.24706753812636165}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R14C2">24.71%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.040766143790849675}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-2]/R28C2">4.08%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"15 days"}'>15 days</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":364380}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>364,380</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.02886749851455734}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R14C2">2.89%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.00476313725490196}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-2]/R28C2">0.48%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"None"}'>None</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1860410}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>1,860,410</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.14738839374133492}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R14C2">14.74%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.02431908496732026}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-2]/R28C2">2.43%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Total"}'>Total</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":12622500}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>12,622,500</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R14C2">100.00%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.165}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-2]/R28C2">16.50%</td>
</tr>
<tr><td colspan="4" rowspan="1" data-sheets-value='{"1":2,"2":"Source: DART"}'>Source: DART</td></tr>
</tbody>
</table><p>Following is the post-IPO shareholding.</p><table class="table table-striped">
<colgroup>
<col width="70">
<col width="70">
<col width="70">
<col width="70">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Shareholder"}'>Post-IPO shareholding</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Qty."}'>Qty.</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"%"}'>%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Lock-up"}'>Lock-up</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"SK Chemical"}'>SK Chemical</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":52350000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>52,350,000</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6843137254901961}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R28C2">68.43%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"6 months"}'>6 months</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"ESOP"}'>ESOP</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":4490400}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-17]C[2]">4,490,400</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.058698039215686275}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R28C2">5.87%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"1 year"}'>1 year</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Institutional"}'>Institutional</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":12622500}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=sum(R[1]C[0]:R[5]C[0])">12,622,500</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.165}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R28C2">16.50%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - 6 months"}'>- 6 months</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":3948100}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-12]C[0]">3,948,100</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.05160915032679739}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R28C2">5.16%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"6 months"}'>6 months</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - 3 months"}'>- 3 months</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":3331000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-12]C[0]">3,331,000</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.04354248366013072}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R28C2">4.35%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"3 months"}'>3 months</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - 1 month"}'>- 1 month</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":3118610}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-12]C[0]">3,118,610</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.040766143790849675}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R28C2">4.08%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"1 month"}'>1 month</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - 15 days"}'>- 15 days</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":364380}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-12]C[0]">364,380</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.00476313725490196}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R28C2">0.48%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"15 days"}'>15 days</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - None"}'>- None</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1860410}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-12]C[0]">1,860,410</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.02431908496732026}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R28C2">2.43%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"None"}'>None</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Retail"}'>Retail</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":5837100}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-22]C[2]">5,837,100</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.07630196078431373}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R28C2">7.63%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"None"}'>None</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Other"}'>Other</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1200000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[1]C[0]-R[-9]C[0]-R[-8]C[0]-R[-7]C[0]-R[-1]C[0]">1,200,000</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.01568627450980392}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[0]C[-1]/R28C2">1.57%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"None"}'>None</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Total"}'>Total</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":76500000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>76,500,000</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(R[-10]C[0]:R[-8]C[0])+R[-2]C[0]+R[-1]C[0]">100.00%</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}'>-</td>
</tr>
<tr><td colspan="4" rowspan="1" data-sheets-value='{"1":2,"2":"Source: DART"}'>Source: DART</td></tr>
</tbody>
</table>

Below is the final allocation.









Type
Initial
Subscription
Allocation
%


ESOP
4,590,000
4,490,400
4,490,400
19.57%


Institutional
12,622,500
12,622,500
12,622,500
55.00%


Retail
5,737,500
1,957,531,110
5,837,100
25.43%


Total
22,950,000
1,974,644,010
22,950,000
100.00%

Source: DART

Below is the lockup pledge as a % of subscriptions.Nearly 60% subscribed without lockup pledge.







Lockup
Qty.
% of subscription


6 months
2,194,034,000
13.63%


3 months
3,595,764,000
22.33%


1 month
3,246,456,500
20.16%


15 days
610,574,000
3.79%


None
9,646,828,500
59.92%


Total
16,099,563,214
100.00%

Source: DART

A little surprisingly, 85% of the allocation went to lockup pledgers.What can be deducted from it? It indicates that this IPO may have attracted more long-term investors than what we usually see from Korea's local IPOs.








Lockup
Qty.
% of allocation
% of SO


6 months
3,948,100
31.28%
5.16%


3 months
3,331,000
26.39%
4.35%


1 month
3,118,610
24.71%
4.08%


15 days
364,380
2.89%
0.48%


None
1,860,410
14.74%
2.43%


Total
12,622,500
100.00%
16.50%

Source: DART

Following is the post-IPO shareholding.








Post-IPO shareholding
Qty.
%
Lock-up


SK Chemical
52,350,000
68.43%
6 months


ESOP
4,490,400
5.87%
1 year


Institutional
12,622,500
16.50%
-


- 6 months
3,948,100
5.16%
6 months


- 3 months
3,331,000
4.35%
3 months


- 1 month
3,118,610
4.08%
1 month


- 15 days
364,380
0.48%
15 days


- None
1,860,410
2.43%
None


Retail
5,837,100
7.63%
None


Other
1,200,000
1.57%
None


Total
76,500,000
100.00%
-

Source: DART



SK Bioscience IPO: Allocation & Lockup Schedule

South Korea

SK Chemicals Co.,Ltd manufactures environmentally friendly materials. The Company produces and sells composites, high-performance materials, energy saving materials, and other products. SK Chemicals also offers total healthcare solutions services. SK Chemicals serves customers worldwide.

Price Gauge
52-week Range	0.00 - 0.00
Market Cap (USDm)	0.00
P/E	0.00
Dividend (Yield)	0.00

SK Chemicals (285130 KS)

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52-week Range

Market Cap (USDm)

P/E

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