Korea / Special Sits, Pairs, Index Rebalancing, Clepsydra Capital

Sanghyun Park

Korea / Special Sits, Pairs, Index Rebalancing

Clepsydra Capital

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

Event-Driven

<p>I track a total of 141 sector pairs in Korea. Starting this insight, I grouped them into three groups: 1. Financials, 2. Retail, and 3. Industrials.</p><hr><h2>Financials</h2><p>4 pairs from the Financials group have a 180-day correlation coefficient above 0.75 (or close) and a 180-day daily price return beta above 0.70 while sitting below -1.0σ on a 20-day moving average. Of these, <strong>Hana Financial/Shinhan Financial</strong> and <strong>Hyundai Marine/DB Insurance</strong> warrant attention.</p><table class="table table-striped">
<colgroup>
<col width="200">
<col width="200">
<col width="70">
<col width="70">
<col width="70">
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<tbody>
<tr>
<td style="width: 241.818px;" data-sheets-value='{"1":2,"2":"Comp 1 (Long)"}'>Comp 1 (Long)</td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"Comp 2 (Short)"}'>Comp 2 (Short)</td>
<td style="text-align: right; width: 64.5455px;" data-sheets-value='{"1":2,"2":"Sigma on a 20-day moving average"}'>Sigma on a 20-day moving average</td>
<td style="text-align: right; width: 60.9091px;" data-sheets-value='{"1":2,"2":"180-day correlation coefficient"}'>180-day correlation coefficient</td>
<td style="text-align: right; width: 82.7273px;" data-sheets-value='{"1":2,"2":"Cointegration coefficient (180-day price Δ beta)"}'>Cointegration coefficient (180-day price Δ beta)</td>
</tr>
<tr>
<td style="width: 241.818px;" data-sheets-value='{"1":2,"2":"Mirae Asset Securities Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]">Mirae Asset Securities Co Ltd</td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"Samsung Securities Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]">Samsung Securities Co Ltd</td>
<td style="text-align: right; width: 64.5455px;" data-sheets-value='{"1":3,"3":-1.222273476903716}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]">-1.22</td>
<td style="text-align: right; width: 60.9091px;" data-sheets-value='{"1":3,"3":0.7539862250329782}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[0]C[3]">0.75</td>
<td style="text-align: right; width: 82.7273px;" data-sheets-value='{"1":3,"3":0.6991098567863366}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[2]C[-3]">0.70</td>
</tr>
<tr>
<td style="width: 241.818px;" data-sheets-value='{"1":2,"2":"Mirae Asset Securities Co Ltd"}' data-sheets-formula="=Data!R[-2]C[3]">Mirae Asset Securities Co Ltd</td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"NH Investment &amp; Securities Co Ltd"}' data-sheets-formula="=Data!R[-2]C[3]">NH Investment &amp; Securities Co Ltd</td>
<td style="text-align: right; width: 64.5455px;" data-sheets-value='{"1":3,"3":-1.1519173688233821}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]">-1.15</td>
<td style="text-align: right; width: 60.9091px;" data-sheets-value='{"1":3,"3":0.7418291376039101}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[2]C[3]">0.74</td>
<td style="text-align: right; width: 82.7273px;" data-sheets-value='{"1":3,"3":0.7031067314990199}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[1]C[3]">0.70</td>
</tr>
<tr>
<td style="width: 241.818px;" data-sheets-value='{"1":2,"2":"Hana Financial Group Inc"}' data-sheets-formula="=Data!R[-3]C[5]"><strong>Hana Financial Group Inc</strong></td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"Shinhan Financial Group Co., Ltd."}' data-sheets-formula="=Data!R[-3]C[5]"><strong>Shinhan Financial Group Co., Ltd.</strong></td>
<td style="text-align: right; width: 64.5455px;" data-sheets-value='{"1":3,"3":-1.0788984328569544}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.08</strong></td>
<td style="text-align: right; width: 60.9091px;" data-sheets-value='{"1":3,"3":0.9401716746799647}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[2]C[3]"><strong>0.94</strong></td>
<td style="text-align: right; width: 82.7273px;" data-sheets-value='{"1":3,"3":1.021970873112603}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[0]C[5]"><strong>1.02</strong></td>
</tr>
<tr>
<td style="width: 241.818px;" data-sheets-value='{"1":2,"2":"Hyundai Marine &amp; Fire Insurance Co., Ltd"}' data-sheets-formula="=Data!R[-4]C[7]"><strong>Hyundai Marine &amp; Fire Insurance Co., Ltd</strong></td>
<td style="width: 190px;" data-sheets-value='{"1":2,"2":"DB Insurance Co Ltd"}' data-sheets-formula="=Data!R[-4]C[7]"><strong>DB Insurance Co Ltd</strong></td>
<td style="text-align: right; width: 64.5455px;" data-sheets-value='{"1":3,"3":-1.0725124068124459}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.07</strong></td>
<td style="text-align: right; width: 60.9091px;" data-sheets-value='{"1":3,"3":0.9161479896868121}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[2]C[3]"><strong>0.92</strong></td>
<td style="text-align: right; width: 82.7273px;" data-sheets-value='{"1":3,"3":0.756650231829711}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[-1]C[7]"><strong>0.76</strong></td>
</tr>
<tr><td colspan="5" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><h2>Retail</h2><p>2 pairs from the Retail group have a 180-day correlation coefficient above 0.75 and a 180-day daily price return beta above 0.70 while sitting below -1.0σ on a 20-day moving average: <strong>Lotte Shopping/GS Retail</strong> and <strong>Lotte Shopping/Hyundai Department</strong>.</p><table class="table table-striped">
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<col width="200">
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<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Comp 1 (Long)"}'>Comp 1 (Long)</td>
<td data-sheets-value='{"1":2,"2":"Comp 2 (Short)"}'>Comp 2 (Short)</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Sigma on a 20-day moving average"}'>Sigma on a 20-day moving average</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"180-day correlation coefficient"}'>180-day correlation coefficient</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Cointegration coefficient (180-day price Δ beta)"}'>Cointegration coefficient (180-day price Δ beta)</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Lotte Shopping Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]"><strong>Lotte Shopping Co Ltd</strong></td>
<td data-sheets-value='{"1":2,"2":"GS Retail Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]"><strong>GS Retail Co Ltd</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-1.5275880593828013}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.53</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8726370244086025}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[0]C[3]"><strong>0.87</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8778679151859091}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[2]C[-3]"><strong>0.88</strong></td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Lotte Shopping Co Ltd"}' data-sheets-formula="=Data!R[-3]C[5]"><strong>Lotte Shopping Co Ltd</strong></td>
<td data-sheets-value='{"1":2,"2":"Hyundai Department Store Co Ltd"}' data-sheets-formula="=Data!R[-3]C[5]"><strong>Hyundai Department Store Co Ltd</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-1.126049210184334}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.13</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.9181905655104922}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[1]C[3]"><strong>0.92</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8654420144103113}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[0]C[3]"><strong>0.87</strong></td>
</tr>
<tr><td colspan="5" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><h2>Industrials</h2><p>4 pairs from the Retail group have a 180-day correlation coefficient above 0.75 and a 180-day daily price return beta above 0.70 (or close) while sitting below -1.0σ on a 20-day moving average.</p><p>Of these, the Celltrion siblings are the most correlated/cointegrated ones with a substantial diversion. I mentioned their trading dynamics in the previous insight. I will cover <strong>KAI/Hanwha Aerospace </strong>and <strong>Korea Shipbuilding/Hyundai Mipo</strong> in this post.</p><table class="table table-striped">
<colgroup>
<col width="70">
<col width="70">
<col width="70">
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<tbody>
<tr>
<td style="width: 230px;" data-sheets-value='{"1":2,"2":"Comp 1 (Long)"}'>Comp 1 (Long)</td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Comp 2 (Short)"}'>Comp 2 (Short)</td>
<td style="text-align: right; width: 80px;" data-sheets-value='{"1":2,"2":"Sigma on a 20-day moving average"}'>Sigma on a 20-day moving average</td>
<td style="text-align: right; width: 58.1818px;" data-sheets-value='{"1":2,"2":"180-day correlation coefficient"}'>180-day correlation coefficient</td>
<td style="text-align: right; width: 77.2727px;" data-sheets-value='{"1":2,"2":"Cointegration coefficient (180-day price Δ beta)"}'>Cointegration coefficient (180-day price Δ beta)</td>
</tr>
<tr>
<td style="width: 230px;" data-sheets-value='{"1":2,"2":"Korea Aerospace Industries Ltd"}' data-sheets-formula="=Data!R[-1]C[1]"><strong>Korea Aerospace Industries Ltd</strong></td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Hanwha Aerospace Co Ltd"}' data-sheets-formula="=Data!R[-1]C[1]"><strong>Hanwha Aerospace Co Ltd</strong></td>
<td style="text-align: right; width: 80px;" data-sheets-value='{"1":3,"3":-1.2612782453636326}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.26</strong></td>
<td style="text-align: right; width: 58.1818px;" data-sheets-value='{"1":3,"3":0.9151301901660448}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[2]C[3]"><strong>0.92</strong></td>
<td style="text-align: right; width: 77.2727px;" data-sheets-value='{"1":3,"3":0.6164208180229479}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[2]C[1]"><strong>0.62</strong></td>
</tr>
<tr>
<td style="width: 230px;" data-sheets-value='{"1":2,"2":"Celltrion, Inc."}' data-sheets-formula="=Data!R[-2]C[3]">Celltrion, Inc.</td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Celltrion HealthCare Co Ltd"}' data-sheets-formula="=Data!R[-2]C[3]">Celltrion HealthCare Co Ltd</td>
<td style="text-align: right; width: 80px;" data-sheets-value='{"1":3,"3":-1.178153322167809}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]">-1.18</td>
<td style="text-align: right; width: 58.1818px;" data-sheets-value='{"1":3,"3":0.8365102631201596}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[2]C[3]">0.84</td>
<td style="text-align: right; width: 77.2727px;" data-sheets-value='{"1":3,"3":0.7643376618440517}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[1]C[3]">0.76</td>
</tr>
<tr>
<td style="width: 230px;" data-sheets-value='{"1":2,"2":"Celltrion Pharm Inc"}' data-sheets-formula="=Data!R[-3]C[5]">Celltrion Pharm Inc</td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Celltrion HealthCare Co Ltd"}' data-sheets-formula="=Data!R[-3]C[5]">Celltrion HealthCare Co Ltd</td>
<td style="text-align: right; width: 80px;" data-sheets-value='{"1":3,"3":-1.066075796850893}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]">-1.07</td>
<td style="text-align: right; width: 58.1818px;" data-sheets-value='{"1":3,"3":0.8799929165201812}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[3]C[3]">0.88</td>
<td style="text-align: right; width: 77.2727px;" data-sheets-value='{"1":3,"3":0.7823707069161424}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[0]C[7]">0.78</td>
</tr>
<tr>
<td style="width: 230px;" data-sheets-value='{"1":2,"2":"Korea Shipbuilding &amp;Offshore Engn Co Ltd"}' data-sheets-formula="=Data!R[-5]C[9]"><strong>Korea Shipbuilding &amp;Offshore Engn Co Ltd</strong></td>
<td style="width: 194.545px;" data-sheets-value='{"1":2,"2":"Hyundai Mipo Dockyard Co., Ltd."}' data-sheets-formula="=Data!R[-5]C[9]"><strong>Hyundai Mipo Dockyard Co., Ltd.</strong></td>
<td style="text-align: right; width: 80px;" data-sheets-value='{"1":3,"3":-1.0295619383635715}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.03</strong></td>
<td style="text-align: right; width: 58.1818px;" data-sheets-value='{"1":3,"3":0.9657685058341984}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Sort!R[3]C[3]"><strong>0.97</strong></td>
<td style="text-align: right; width: 77.2727px;" data-sheets-value='{"1":3,"3":0.6811111503062213}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[-2]C[11]"><strong>0.68</strong></td>
</tr>
<tr><td colspan="5" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table>

I track a total of 141 sector pairs in Korea. Starting this insight, I grouped them into three groups: 1. Financials, 2. Retail, and 3. Industrials.Financials4 pairs from the Financials group have a 180-day correlation coefficient above 0.75 (or close) and a 180-day daily price return beta above 0.70 while sitting below -1.0σ on a 20-day moving average. Of these, Hana Financial/Shinhan Financial and Hyundai Marine/DB Insurance warrant attention.









Comp 1 (Long)
Comp 2 (Short)
Sigma on a 20-day moving average
180-day correlation coefficient
Cointegration coefficient (180-day price Δ beta)


Mirae Asset Securities Co Ltd
Samsung Securities Co Ltd
-1.22
0.75
0.70


Mirae Asset Securities Co Ltd
NH Investment &amp; Securities Co Ltd
-1.15
0.74
0.70


Hana Financial Group Inc
Shinhan Financial Group Co., Ltd.
-1.08
0.94
1.02


Hyundai Marine &amp; Fire Insurance Co., Ltd
DB Insurance Co Ltd
-1.07
0.92
0.76

Source: KRX

Retail2 pairs from the Retail group have a 180-day correlation coefficient above 0.75 and a 180-day daily price return beta above 0.70 while sitting below -1.0σ on a 20-day moving average: Lotte Shopping/GS Retail and Lotte Shopping/Hyundai Department.









Comp 1 (Long)
Comp 2 (Short)
Sigma on a 20-day moving average
180-day correlation coefficient
Cointegration coefficient (180-day price Δ beta)


Lotte Shopping Co Ltd
GS Retail Co Ltd
-1.53
0.87
0.88


Lotte Shopping Co Ltd
Hyundai Department Store Co Ltd
-1.13
0.92
0.87

Source: KRX

Industrials4 pairs from the Retail group have a 180-day correlation coefficient above 0.75 and a 180-day daily price return beta above 0.70 (or close) while sitting below -1.0σ on a 20-day moving average.Of these, the Celltrion siblings are the most correlated/cointegrated ones with a substantial diversion. I mentioned their trading dynamics in the previous insight. I will cover KAI/Hanwha Aerospace and Korea Shipbuilding/Hyundai Mipo in this post.









Comp 1 (Long)
Comp 2 (Short)
Sigma on a 20-day moving average
180-day correlation coefficient
Cointegration coefficient (180-day price Δ beta)


Korea Aerospace Industries Ltd
Hanwha Aerospace Co Ltd
-1.26
0.92
0.62


Celltrion, Inc.
Celltrion HealthCare Co Ltd
-1.18
0.84
0.76


Celltrion Pharm Inc
Celltrion HealthCare Co Ltd
-1.07
0.88
0.78


Korea Shipbuilding &amp;Offshore Engn Co Ltd
Hyundai Mipo Dockyard Co., Ltd.
-1.03
0.97
0.68

Source: KRX



Korea Sector Pair Trade: Financials, Retail, & Industrials

<p>Hanwha Systems' ₩1.2T offering subscription rights trade begins <strong>May 13 (this Thursday)</strong>. It will last for 5 trading sessions until May 20.</p><table class="table table-striped"><tbody>
<tr><td colspan="2" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Timetable"}'>Timetable</td></tr>
<tr>
<td style="width: 364.545px;" data-sheets-value='{"1":2,"2":"Subscription rights trade beginning"}'><strong>Subscription rights trade</strong></td>
<td style="text-align: right; width: 338.182px;" data-sheets-value='{"1":3,"3":44329}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'><strong>2021. 5. 13 ~ 5. 20</strong></td>
</tr>
<tr>
<td style="width: 364.545px;" data-sheets-value='{"1":2,"2":"Final pricing"}'><strong>Final pricing</strong></td>
<td style="text-align: right; width: 338.182px;" data-sheets-value='{"1":3,"3":44347}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'><strong>2021. 5. 31</strong></td>
</tr>
<tr>
<td style="width: 364.545px;">Subscription</td>
<td style="text-align: right; width: 338.182px;">2021. 6. 03</td>
</tr>
<tr>
<td style="width: 364.545px;">Payment</td>
<td style="text-align: right; width: 338.182px;">2021. 6. 11</td>
</tr>
<tr>
<td style="width: 364.545px;" data-sheets-value='{"1":2,"2":"Listing"}'><strong>Listing</strong></td>
<td style="text-align: right; width: 338.182px;" data-sheets-value='{"1":3,"3":44370}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'><strong>2021. 6. 23</strong></td>
</tr>
<tr><td colspan="2" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: DART"}'>Source: DART</td></tr>
</tbody></table><p><strong>The 1st round price settled at ₩15,800, giving an 11.73% discount to the last close</strong>. This price of ₩15,800 will likely serve as our ceiling price in this offering.</p><table class="table table-striped">
<colgroup>
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr><td colspan="2" rowspan="1" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"1st round pricing"}'>1st round pricing</td></tr>
<tr>
<td style="width: 370.909px;" data-sheets-value='{"1":2,"2":"Calculation period"}'>Calculation period</td>
<td style="text-align: right; width: 331.818px;" data-sheets-value='{"1":2,"2":"2021.03.20 ~ 2021.04.19"}'><div><div>2021.03.20 ~ 2021.04.19</div></div></td>
</tr>
<tr>
<td style="width: 370.909px;" data-sheets-value='{"1":2,"2":"Reference date"}'><strong>Reference date</strong></td>
<td style="text-align: right; width: 331.818px;" data-sheets-value='{"1":3,"3":44305}' data-sheets-numberformat='{"1":5,"2":"mmmm d","3":1}'><strong>April 19</strong></td>
</tr>
<tr>
<td style="width: 370.909px;" data-sheets-value='{"1":2,"2":"1-month volume weighted average price"}'>1-month volume-weighted average price (VWAP)</td>
<td style="text-align: right; width: 331.818px;" data-sheets-value='{"1":3,"3":20817}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0","3":1}'>₩20,817</td>
</tr>
<tr>
<td style="width: 370.909px;" data-sheets-value='{"1":2,"2":"1-week volume weighted average price"}'>1-week volume-weighted average price (VWAP)</td>
<td style="text-align: right; width: 331.818px;" data-sheets-value='{"1":3,"3":20222}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0","3":1}'>₩20,222</td>
</tr>
<tr>
<td style="width: 370.909px;" data-sheets-value='{"1":2,"2":"1-day close on April 19"}'>1-day close on April 19</td>
<td style="text-align: right; width: 331.818px;" data-sheets-value='{"1":3,"3":20600}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0","3":1}'>₩20,600</td>
</tr>
<tr>
<td style="width: 370.909px;" data-sheets-value='{"1":2,"2":"(A+B+C)/3"}'>(A+B+C)/3</td>
<td style="text-align: right; width: 331.818px;" data-sheets-value='{"1":3,"3":20546}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0","3":1}'>₩20,546</td>
</tr>
<tr>
<td style="width: 370.909px;" data-sheets-value='{"1":2,"2":"Reference price: Min(C,D)"}'><strong>Reference Price: Min(C,D)</strong></td>
<td style="text-align: right; width: 331.818px;" data-sheets-value='{"1":3,"3":20546}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0","3":1}' data-sheets-formula="=R[-1]C[0]"><strong>₩20,546</strong></td>
</tr>
<tr>
<td style="width: 370.909px;" data-sheets-value='{"1":2,"2":"Discount rate"}'>Discount rate</td>
<td style="text-align: right; width: 331.818px;" data-sheets-value='{"1":3,"3":0.15}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}'>15.00%</td>
</tr>
<tr>
<td style="width: 370.909px;" data-sheets-value='{"1":2,"2":"Capital increase rate"}'>Capital increase rate</td>
<td style="text-align: right; width: 331.818px;" data-sheets-value='{"1":2,"2":"71,39%"}'>71,39%</td>
</tr>
<tr>
<td style="width: 370.909px;" data-sheets-value='{"1":2,"2":"1st round price: Reference Price × (1 - 15%) / [1 + (71.39% × 15%)]"}'><strong>1st round price: Reference Price × (1 - 15%) / [1 + (71.39% × 15%)]</strong></td>
<td style="text-align: right; width: 331.818px;" data-sheets-value='{"1":3,"3":15800}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0","3":1}'><strong>₩15,800</strong></td>
</tr>
<tr><td colspan="2" rowspan="1" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: DART"}'>Source: DART</td></tr>
</tbody>
</table><hr><p><strong>Why does this subscription rights trade deserve attention?</strong></p><div><ul>
<li>Korea now has the short-selling restriction to ban short-sellers from participating in a rights offer. Those having shorted between a day after an offering announcement day and an offering price-fixing day face the restriction.</li>
<li>But this restriction applies only to the offerings announced after April 6. <strong>This Hanwha Systems offering allows us to enjoy the loophole for the last time,</strong> as the offering announcement was made on <strong>March 29</strong>.</li>
</ul></div>

Hanwha Systems' ₩1.2T offering subscription rights trade begins May 13 (this Thursday). It will last for 5 trading sessions until May 20.
Timetable

Subscription rights trade
2021. 5. 13 ~ 5. 20


Final pricing
2021. 5. 31


Subscription
2021. 6. 03


Payment
2021. 6. 11


Listing
2021. 6. 23

Source: DART
The 1st round price settled at ₩15,800, giving an 11.73% discount to the last close. This price of ₩15,800 will likely serve as our ceiling price in this offering.





1st round pricing

Calculation period
2021.03.20 ~ 2021.04.19


Reference date
April 19


1-month volume-weighted average price (VWAP)
₩20,817


1-week volume-weighted average price (VWAP)
₩20,222


1-day close on April 19
₩20,600


(A+B+C)/3
₩20,546


Reference Price: Min(C,D)
₩20,546


Discount rate
15.00%


Capital increase rate
71,39%


1st round price: Reference Price × (1 - 15%) / [1 + (71.39% × 15%)]
₩15,800

Source: DART

Why does this subscription rights trade deserve attention?
Korea now has the short-selling restriction to ban short-sellers from participating in a rights offer. Those having shorted between a day after an offering announcement day and an offering price-fixing day face the restriction.
But this restriction applies only to the offerings announced after April 6. This Hanwha Systems offering allows us to enjoy the loophole for the last time, as the offering announcement was made on March 29.


Hanwha Systems Subscription Rights Trading Begins May 13: Should Aim at the First Day

Korea/Asia, Events, IPOs, Douglas Research Advisory

Douglas Kim

Korea/Asia, Events, IPOs

<p>Our NAV analysis of <a href="https://www.smartkarma.com/entities/hanwha-corporation" target="_blank" data-smartkarma-citation="entities:10619:1" rel="noopener">Hanwha Corporation (000880 KS)</a> suggests NAV of 3,845 billion won (51,298 won per share). This represents a 62% upside from the current price of 31,600 won. The biggest component of the company's value is its investments in other Hanwha Group related companies. Hanwha Corp's 37% stake in Hanwha Solution is worth 3.3 trillion won, which represents 60% of the value of the company (pre-holdco discount).</p><p>With the resumption of the partial short selling of Korean stocks on May 3rd, more hedge funds and other active investors will likely to employ pair trade strategies involving holdcos and opcos in Korea. The pair between Hanwha Corp and Hanwha Solution is the one which have shown one of widest gaps in share price performance in the past year. In our view, there is a good chance that this price gap narrows between Hanwha Corp and Hanwha Solution in the coming months.</p>

Our NAV analysis of Hanwha Corporation (000880 KS) suggests NAV of 3,845 billion won (51,298 won per share). This represents a 62% upside from the current price of 31,600 won. The biggest component of the company's value is its investments in other Hanwha Group related companies. Hanwha Corp's 37% stake in Hanwha Solution is worth 3.3 trillion won, which represents 60% of the value of the company (pre-holdco discount).With the resumption of the partial short selling of Korean stocks on May 3rd, more hedge funds and other active investors will likely to employ pair trade strategies involving holdcos and opcos in Korea. The pair between Hanwha Corp and Hanwha Solution is the one which have shown one of widest gaps in share price performance in the past year. In our view, there is a good chance that this price gap narrows between Hanwha Corp and Hanwha Solution in the coming months.

Our NAV Analysis of Hanwha Corp and A Pair Trade with Hanwha Solution

<p>We are one trading session before the 1st-round pricing for the Hanwha Systems ₩1.2T offers.</p><p>The pricing is next Monday, April 19. </p><div><div><table class="table table-striped"><tbody>
<tr><td colspan="2" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Timetable"}'>Timetable</td></tr>
<tr>
<td style="width: 350.909px;" data-sheets-value='{"1":2,"2":"Preliminary pricing"}'><strong>Preliminary pricing</strong></td>
<td style="text-align: right; width: 351.818px;" data-sheets-value='{"1":3,"3":44305}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'><strong>2021. 4. 19</strong></td>
</tr>
<tr>
<td style="width: 350.909px;" data-sheets-value='{"1":2,"2":"Ex-rights date"}'><strong>Ex-rights date</strong></td>
<td style="text-align: right; width: 351.818px;" data-sheets-value='{"1":3,"3":44307}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'><strong>2021. 4. 21</strong></td>
</tr>
<tr>
<td style="width: 350.909px;" data-sheets-value='{"1":2,"2":"Record date"}'>Record date</td>
<td style="text-align: right; width: 351.818px;" data-sheets-value='{"1":3,"3":44308}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'>2021. 4. 22</td>
</tr>
<tr>
<td style="width: 350.909px;" data-sheets-value='{"1":2,"2":"Subscription rights trade beginning"}'>Subscription rights trade beginning</td>
<td style="text-align: right; width: 351.818px;" data-sheets-value='{"1":3,"3":44329}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'>2021. 5. 13</td>
</tr>
<tr>
<td style="width: 350.909px;" data-sheets-value='{"1":2,"2":"Subscription rights trade ending"}'>Subscription rights trade ending</td>
<td style="text-align: right; width: 351.818px;" data-sheets-value='{"1":3,"3":44329}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'>2021. 5. 20</td>
</tr>
<tr>
<td style="width: 350.909px;" data-sheets-value='{"1":2,"2":"Final pricing"}'>Final pricing</td>
<td style="text-align: right; width: 351.818px;" data-sheets-value='{"1":3,"3":44347}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'>2021. 5. 31</td>
</tr>
<tr>
<td style="width: 350.909px;" data-sheets-value='{"1":2,"2":"Listing"}'>Listing</td>
<td style="text-align: right; width: 351.818px;" data-sheets-value='{"1":3,"3":44370}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'>2021. 6. 23</td>
</tr>
<tr><td colspan="2" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: DART"}'>Source: DART</td></tr>
</tbody></table></div></div><div>
<table class="table table-striped">
<colgroup>
<col width="350">
<col width="350">
</colgroup>
<tbody>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Pricing"}'>Pricing</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1st round"}'><strong>1st round</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"RP × (1 - 15%) / [1 + (71.39% × 15%)]"}' data-sheets-formula='="RP × (1 - "&amp;(R[11]C[0]*100&amp;"%")&amp;") / [1 + ("&amp;(R[12]C[0]*100&amp;"%"&amp;" × "&amp;(R[11]C[0]*100&amp;"%"&amp;")]"))'><strong>RP × (1 - 15%) / [1 + (71.39% × 15%)]</strong></td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Reference price (RP)"}'><strong>- Reference price (RP)</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Min [Close, Avg (Close, 1W VWAP, 1M VWAP)]"}'><strong>Min [Close, Avg (Close, 1W VWAP, 1M VWAP)]</strong></td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Reference date"}'><strong>- Reference date</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44305}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}' data-sheets-formula="=Terms!R[41]C[0]"><strong>2021. 4. 19</strong></td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Ex-rights base price"}'>Ex-rights base price</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"[RP + (1st × 71.39%)] / (1 + 71.39%)"}' data-sheets-formula='="[RP + (1st × "&amp;R[9]C[0]*100&amp;"%"&amp;")] / (1 + "&amp;R[9]C[0]*100&amp;"%"&amp;")"'>[RP + (1st × 71.39%)] / (1 + 71.39%)</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Reference price (RP)"}'>- Reference price (RP)</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Previous close"}'>Previous close</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Reference date"}'>- Reference date</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44307}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}' data-sheets-formula="=Terms!R[39]C[0]">2021. 4. 21</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2nd round"}'>2nd round</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"RP × (1 - 15%)"}' data-sheets-formula='="RP × (1 - "&amp;(R[5]C[0]*100&amp;"%")&amp;")"'>RP × (1 - 15%)</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Reference price (RP)"}'>- Reference price (RP)</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Min [Close, Avg (Close, 1W VWAP)]"}'>Min [Close, Avg (Close, 1W VWAP)]</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Reference date"}'>- Reference date</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44347}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}' data-sheets-formula="=Terms!R[40]C[0]">2021. 5. 31</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Final"}'>Final</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Max [Min (1st, 2nd), 3D VWAP × 60%]"}'>Max [Min (1st, 2nd), 3D VWAP × 60%]</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Reference date"}'>- Reference date</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44347}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}' data-sheets-formula="=Terms!R[38]C[0]">2021. 5. 31</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Discount rate"}'>Discount rate</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.15}' data-sheets-numberformat='[null,3,"0.00%",1]'>15.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Capital increase rate"}'>Capital increase rate</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.7139}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=LEFT(Terms!R[11]C[0],6)*100/100">71.39%</td>
</tr>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Source: DART"}'>Source: DART</td></tr>
</tbody>
</table>
<p>As I'm writing this post, the share price is ₩20,150 with a 1W VWAP of ₩20,120 and a 1M VWAP of ₩20,829, giving a preliminary RP of ₩20,150.</p>
<p>The 1st round offering price then arrives at ₩15,500 at a discount rate of 15% and a capital increase of 71.39%.</p>
<table class="table table-striped">
<colgroup>
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"1st round pricing"}'>1st round pricing</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Date"}'>Date</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44305}' data-sheets-numberformat='{"1":5,"2":"yyyy\". \"m\". \"d","3":1}'>2021. 4. 19</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1D VWAP"}'>Previous close</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":20150}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula='=googlefinance(R[-27]C[3], "price")'>₩20,150</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1W VWAP"}'>1W VWAP</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":20119.55102347699}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=R[-7]C[2]">₩20,120</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1M VWAP"}'>1M VWAP</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":20828.708137926085}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=R[-7]C[2]">₩20,829</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Average"}'>- Average</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":20366.086387134357}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=sum(R[-3]C[0]:R[-1]C[0])/3">₩20,366</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Reference price"}'><strong>Reference price</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":20150}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=min(R[-4]C[0], R[-1]C[0])"><strong>₩20,150</strong></td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1st round price"}'><strong>1st round price</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":15500}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=ceiling.math((R[-1]C[0]*(1-R[-20]C[5]))/((1+(R[-19]C[5]*R[-20]C[5]))), 100)"><strong>₩15,500</strong></td>
</tr>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Source: DART"}'>Source: DART</td></tr>
</tbody>
</table>
<table class="table table-striped">
<colgroup>
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr><td colspan="2" data-sheets-value='{"1":2,"2":"Ex-rights base price"}'>Ex-rights base price</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Date"}'>Date</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44307}' data-sheets-numberformat='{"1":5,"2":"yyyy\". \"m\". \"d","3":1}'>2021. 4. 21</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Previous close"}'>Previous close</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":20150}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=R[-10]C[0]">₩20,150</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1st round"}'>1st round</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":15500}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=R[-6]C[0]">₩15,500</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Ex-rights base price"}'>Ex-rights base price</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":18300}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=ceiling.math(((R[-2]C[0]+(R[-1]C[0]*R[-26]C[5]))/(1+R[-26]C[5])), 100)">₩18,300</td>
</tr>
<tr>
<td> - % to close</td>
<td style="text-align: right;">-9.41%</td>
</tr>
<tr><td colspan="2" data-sheets-value='{"1":2,"2":"Source: KRX KIND"}'>Source: KRX KIND</td></tr>
</tbody>
</table>
</div>

We are one trading session before the 1st-round pricing for the Hanwha Systems ₩1.2T offers.The pricing is next Monday, April 19. 
Timetable

Preliminary pricing
2021. 4. 19


Ex-rights date
2021. 4. 21


Record date
2021. 4. 22


Subscription rights trade beginning
2021. 5. 13


Subscription rights trade ending
2021. 5. 20


Final pricing
2021. 5. 31


Listing
2021. 6. 23

Source: DART







Pricing

1st round
RP × (1 - 15%) / [1 + (71.39% × 15%)]


- Reference price (RP)
Min [Close, Avg (Close, 1W VWAP, 1M VWAP)]


- Reference date
2021. 4. 19


Ex-rights base price
[RP + (1st × 71.39%)] / (1 + 71.39%)


- Reference price (RP)
Previous close


- Reference date
2021. 4. 21


2nd round
RP × (1 - 15%)


- Reference price (RP)
Min [Close, Avg (Close, 1W VWAP)]


- Reference date
2021. 5. 31


Final
Max [Min (1st, 2nd), 3D VWAP × 60%]


- Reference date
2021. 5. 31


Discount rate
15.00%


Capital increase rate
71.39%

Source: DART


As I'm writing this post, the share price is ₩20,150 with a 1W VWAP of ₩20,120 and a 1M VWAP of ₩20,829, giving a preliminary RP of ₩20,150.
The 1st round offering price then arrives at ₩15,500 at a discount rate of 15% and a capital increase of 71.39%.






1st round pricing

Date
2021. 4. 19


Previous close
₩20,150


1W VWAP
₩20,120


1M VWAP
₩20,829


- Average
₩20,366


Reference price
₩20,150


1st round price
₩15,500

Source: DART








Ex-rights base price

Date
2021. 4. 21


Previous close
₩20,150


1st round
₩15,500


Ex-rights base price
₩18,300


 - % to close
-9.41%

Source: KRX KIND




Hanwha Systems Rights Offer: Outright Trade on Subs Rights Ahead of Ex-Rights

Cross Asset Strategy

<div class="content-highlight">
<p>On 9 April, the <a href="https://www.reuters.com/article/southkorea-nps/update-1-s-koreas-pension-fund-adjusts-rules-to-raise-domestic-equity-allocation-idUSL1N2M20EN" target="_blank" rel="noopener">NPS</a> announced that it will change rules to increase the allocation of Korean stocks, which would be the first time in a decade. This adjustment could be implemented starting next week. This change comes after a lot of pressure by the retail investors.</p>
<p>NPS increased the strategic asset allocation (SAA) limit for domestic equities from the current 2% to 3%, increasing the percentage of Korean stocks it can hold from the current band of 14.8% -18.8% (+/- 2% with 16.8% as base) to 13.8% -19.8% (+/- 3% with 16.8% as base). NPS's target of the domestic equity allocation is 16.8% (of total fund amount). <strong>As a result of this change, the sale of domestic stocks by the NPS is expected to slow down.</strong></p>
</div>


On 9 April, the NPS announced that it will change rules to increase the allocation of Korean stocks, which would be the first time in a decade. This adjustment could be implemented starting next week. This change comes after a lot of pressure by the retail investors.
NPS increased the strategic asset allocation (SAA) limit for domestic equities from the current 2% to 3%, increasing the percentage of Korean stocks it can hold from the current band of 14.8% -18.8% (+/- 2% with 16.8% as base) to 13.8% -19.8% (+/- 3% with 16.8% as base). NPS's target of the domestic equity allocation is 16.8% (of total fund amount). As a result of this change, the sale of domestic stocks by the NPS is expected to slow down.


South Korea

Hanwha Aerospace Co., Ltd. operates as an aircraft parts manufacturing company. The Company produces and sells aircraft gas turbine engine products, aircraft compressors, low pressure turbines, and other products. Hanwha Aerospace markets its products worldwide.

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

Hanwha Aerospace (012450 KS)

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Sanghyun Park

Hanwha Systems Subscription Rights Trading Begins May 13: Should Aim at the First Day

This post examines the Hanwha Systems' offering situation as we advance into the subscription rights trade window beginning May 11.

Sanghyun Park

Our NAV Analysis of Hanwha Corp and A Pair Trade with Hanwha Solution

In this insight, we provide our NAV Analysis of Hanwha Corp suggest a pair trade involving Hanwha Corp & Hanwha Solutions.

Douglas Kim

Hanwha Systems Rights Offer: Outright Trade on Subs Rights Ahead of Ex-Rights

This post looks into the feasibility of an outright trade on subscription rights ahead of the ex-rights for the Hanwha Systems rights offering next...

Sanghyun Park

NPS Raises Domestic Equity Allocations

NPS increased the strategic asset allocation (SAA) limit for domestic equities from the current 2% to 3%. As a result of this change, the sale of...

Douglas Kim

Price Gauge

52-week Range

Market Cap (USDm)

P/E

Dividend (Yield)