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

<ul>
<li>The upcoming rebalancing should feature a total of 12 constituents having a ±5%p free float change: eight members with +5%p or greater and four members with -5%p or harsher.</li>
<li>It seems better to outright trade individual liquidity-rich stocks: SK Bioscience, SKIET, Kakao Bank, and Krafton.</li>
<li>Considering that SKIET's recent share price correction was severe, we may want to take a relatively long trading window for SKIET while taking a tighter approach to the rest.</li>
</ul>


The upcoming rebalancing should feature a total of 12 constituents having a ±5%p free float change: eight members with +5%p or greater and four members with -5%p or harsher.
It seems better to outright trade individual liquidity-rich stocks: SK Bioscience, SKIET, Kakao Bank, and Krafton.
Considering that SKIET's recent share price correction was severe, we may want to take a relatively long trading window for SKIET while taking a tighter approach to the rest.


KOSPI 200 December Rebalancing: Constituents with a Substantial Free Float Change

I added Kolmar Korea Holdings to my synthetic subsidiary holding company list. As a result, I now track a total of 7 synthetic subsidiary holding companies, of which 3 names are currently at -1.0σ (or close) on a 20-day moving average.  <table class="table table-striped">
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<td data-sheets-value='{"1":2,"2":"Holdco"}'>Holdco</td>
<td style="text-align: left;" data-sheets-value='{"1":2,"2":"Subsidiaries in a synthetic"}'>Subsidiaries in a synthetic</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Sigma (σ) on a 20-day moving average"}'>Sigma (σ) on a 20-day moving average</td>
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<td data-sheets-value='{"1":2,"2":"LG Corp"}' data-sheets-formula="=Data!R[-1]C[1]">LG Corp</td>
<td style="text-align: left;" data-sheets-value='{"1":2,"2":"LG Chem Ltd &amp; 3 others"}' data-sheets-formula='=googlefinance(R[0]C[3], "name")&amp;" &amp; "&amp;R[0]C[4]-1&amp;" others" '>LG Chem Ltd &amp; 3 others</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.9455012913617945}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[10]C[-1]">0.95</td>
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<td data-sheets-value='{"1":2,"2":"Samsung C&amp;T Corp"}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=Data!R[-2]C[6]">Samsung C&amp;T Corp</td>
<td style="text-align: left;" data-sheets-value='{"1":2,"2":"Samsung Electronics Co Ltd &amp; 1 other"}' data-sheets-formula='=googlefinance(R[0]C[3], "name")&amp;" &amp; "&amp;R[0]C[4]-1&amp;" other" '>Samsung Electronics Co Ltd &amp; 1 other</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.34377918950498587}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[10]C[-1]">-0.34</td>
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<td data-sheets-value='{"1":2,"2":"SK Inc"}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=Data!R[-3]C[9]">SK Inc</td>
<td style="text-align: left;" data-sheets-value='{"1":2,"2":"SK Innovation Co Ltd &amp; 2 others"}' data-sheets-formula='=googlefinance(R[0]C[3], "name")&amp;" &amp; "&amp;R[0]C[4]-1&amp;" others" '>SK Innovation Co Ltd &amp; 2 others</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-1.5358952902702356}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[10]C[-1]">-1.54</td>
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<td data-sheets-value='{"1":2,"2":"Lotte Corp"}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=Data!R[-4]C[13]">Lotte Corp</td>
<td style="text-align: left;" data-sheets-value='{"1":2,"2":"Lotte Chemical Corp &amp; 1 other"}' data-sheets-formula='=googlefinance(R[0]C[3], "name")&amp;" &amp; "&amp;R[0]C[4]-1&amp;" other" '>Lotte Chemical Corp &amp; 1 other</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.48761167037793357}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[10]C[-1]">0.49</td>
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<td data-sheets-value='{"1":2,"2":"Hanwha Corp"}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=Data!R[-5]C[16]">Hanwha Corp</td>
<td style="text-align: left;" data-sheets-value='{"1":2,"2":"Hanwha Solutions Corp &amp; 2 others"}' data-sheets-formula='=googlefinance(R[0]C[3], "name")&amp;" &amp; "&amp;R[0]C[4]-1&amp;" others" '>Hanwha Solutions Corp &amp; 2 others</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.9140754552511184}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[10]C[-1]">-0.91</td>
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<td data-sheets-value='{"1":2,"2":"CJ Corp"}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=Data!R[-6]C[20]">CJ Corp</td>
<td style="text-align: left;" data-sheets-value='{"1":2,"2":"CJ Cheiljedang Corp &amp; 1 other"}' data-sheets-formula='=googlefinance(R[0]C[3], "name")&amp;" &amp; "&amp;R[0]C[4]-1&amp;" other" '>CJ Cheiljedang Corp &amp; 1 other</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.29546809089979403}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[10]C[-1]">-0.30</td>
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<td data-sheets-value='{"1":2,"2":"Kolmar Korea Holdings Co Ltd"}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}' data-sheets-formula="=Data!R[-7]C[23]">* Kolmar Korea Holdings Co Ltd</td>
<td style="text-align: left;" data-sheets-value='{"1":2,"2":"KolmarBNH Co Ltd &amp; 1 other"}' data-sheets-formula='=googlefinance(R[0]C[3], "name")&amp;" &amp; "&amp;R[0]C[4]-1&amp;" other" '>KolmarBNH Co Ltd &amp; 1 other</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-1.2339571192225773}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[10]C[-1]">-1.23</td>
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<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
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</table><div class="content-highlight">Starting with this insight, I made some changes in my calculation of NAV. I estimated each holding company's operating operation based on their latest de-consolidated operating profit. It is mostly brand royalty and office rental income. I used operating profit to exclude dividend income.</div>The revised NAV discount calculations show that they are trading mostly within a 50~60% discount to the NAV. The largest discount goes to Samsung C&amp;T, while CJ Corp enjoys the lowest discount to its NAV. Kolmar Korea Holdings features a 53.41% discount to the NAV. It is a two-subsidiary holding company as they account for 89.85% of the NAV.<table class="table table-striped">
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<td style="width: 170.909px;" data-sheets-value='{"1":2,"2":"Discount &amp; weight"}'>Discount &amp; weight</td>
<td style="text-align: right; width: 144.545px;" data-sheets-value='{"1":2,"2":"NAV discount"}'>NAV discount</td>
<td style="text-align: right; width: 171.818px;" data-sheets-value='{"1":2,"2":"Synthetic subsidiary weight in NAV"}'>Synthetic subsidiary weight in NAV</td>
<td style="text-align: right; width: 173.636px;" data-sheets-value='{"1":2,"2":"Synthetic subsidiary weight in GAV"}'>Synthetic subsidiary weight in GAV</td>
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<td style="width: 170.909px;" data-sheets-value='{"1":2,"2":"LG Corp"}' data-sheets-formula="=R[-20]C[0]">LG Corp</td>
<td style="text-align: right; width: 144.545px;" data-sheets-value='{"1":3,"3":0.5892560369567199}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=NAV!R[8]C[0]">58.93%</td>
<td style="text-align: right; width: 171.818px;" data-sheets-value='{"1":3,"3":0.7469661842230064}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[12]C[-1]:R[15]C[-1])">74.70%</td>
<td style="text-align: right; width: 173.636px;" data-sheets-value='{"1":3,"3":0.7703324033104589}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[12]C[-1]:R[15]C[-1])">77.03%</td>
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<td style="width: 170.909px;" data-sheets-value='{"1":2,"2":"Samsung C&amp;T Corp"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-20]C[0]">Samsung C&amp;T Corp</td>
<td style="text-align: right; width: 144.545px;" data-sheets-value='{"1":3,"3":0.6059911856682164}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=NAV!R[7]C[18]">60.60%</td>
<td style="text-align: right; width: 171.818px;" data-sheets-value='{"1":3,"3":0.8026397073991763}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[11]C[17]:R[12]C[17])">80.26%</td>
<td style="text-align: right; width: 173.636px;" data-sheets-value='{"1":3,"3":0.8033397666310156}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[11]C[17]:R[12]C[17])">80.33%</td>
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<td style="width: 170.909px;" data-sheets-value='{"1":2,"2":"SK Inc"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-20]C[0]">SK Inc</td>
<td style="text-align: right; width: 144.545px;" data-sheets-value='{"1":3,"3":0.5173210462000755}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=NAV!R[6]C[24]">51.73%</td>
<td style="text-align: right; width: 171.818px;" data-sheets-value='{"1":3,"3":0.689824350306107}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[10]C[23]:R[12]C[23])">68.98%</td>
<td style="text-align: right; width: 173.636px;" data-sheets-value='{"1":3,"3":0.5561346382258038}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[10]C[23]:R[12]C[23])">55.61%</td>
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<td style="width: 170.909px;" data-sheets-value='{"1":2,"2":"Lotte Corp"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-20]C[0]">Lotte Corp</td>
<td style="text-align: right; width: 144.545px;" data-sheets-value='{"1":3,"3":0.5968470100117429}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=NAV!R[5]C[30]">59.68%</td>
<td style="text-align: right; width: 171.818px;" data-sheets-value='{"1":3,"3":0.5945490346234877}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[9]C[29]:R[10]C[29])">59.45%</td>
<td style="text-align: right; width: 173.636px;" data-sheets-value='{"1":3,"3":0.4605223220736323}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[9]C[29]:R[10]C[29])">46.05%</td>
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<td style="width: 170.909px;" data-sheets-value='{"1":2,"2":"Hanwha Corp"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-20]C[0]">Hanwha Corp</td>
<td style="text-align: right; width: 144.545px;" data-sheets-value='{"1":3,"3":0.5852680864437579}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=NAV!R[4]C[36]">58.53%</td>
<td style="text-align: right; width: 171.818px;" data-sheets-value='{"1":3,"3":0.877152435515112}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[8]C[35]:R[10]C[35])">87.72%</td>
<td style="text-align: right; width: 173.636px;" data-sheets-value='{"1":3,"3":0.5736380974953866}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[8]C[35]:R[10]C[35])">57.36%</td>
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<td style="width: 170.909px;" data-sheets-value='{"1":2,"2":"CJ Corp"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-20]C[0]">CJ Corp</td>
<td style="text-align: right; width: 144.545px;" data-sheets-value='{"1":3,"3":0.47009805549763056}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=NAV!R[3]C[42]">47.01%</td>
<td style="text-align: right; width: 171.818px;" data-sheets-value='{"1":3,"3":0.8302884441278204}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[7]C[41]:R[8]C[41])">83.03%</td>
<td style="text-align: right; width: 173.636px;" data-sheets-value='{"1":3,"3":0.7147074125488337}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[7]C[41]:R[8]C[41])">71.47%</td>
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<td style="width: 170.909px;" data-sheets-value='{"1":2,"2":"Kolmar Korea Holdings Co Ltd"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-20]C[0]">* Kolmar Korea Holdings Co Ltd</td>
<td style="text-align: right; width: 144.545px;" data-sheets-value='{"1":3,"3":0.5340958452553032}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=NAV!R[2]C[48]">53.41%</td>
<td style="text-align: right; width: 171.818px;" data-sheets-value='{"1":3,"3":0.8984875914324668}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[6]C[47]:R[7]C[47])">89.85%</td>
<td style="text-align: right; width: 173.636px;" data-sheets-value='{"1":3,"3":0.8395502332299523}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=sum(NAV!R[6]C[47]:R[7]C[47])">83.96%</td>
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<tr><td colspan="4" rowspan="1" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
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</table>SK Inc and Hanwha Corp are trading 6.53% and 3.30%, respectively, below the 180-day price ratio average relative to their synthetic subsidiaries. As for Kolmar Korea, it is 6.47% above the 180-day mean.<table class="table table-striped">
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<td style="width: 180.909px;" data-sheets-value='{"1":2,"2":"Price ratio"}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}'>Price ratio</td>
<td style="text-align: right; width: 150.909px;" data-sheets-value='{"1":2,"2":"%Δ to 180-day mean"}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}'>%Δ to 180-day mean</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":2,"2":"%Δ to 180-day high"}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}'>%Δ to 180-day high</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":2,"2":"%Δ to 180-day low"}' data-sheets-numberformat='{"1":4,"2":"[$₩]#,##0"}'>%Δ to 180-day low</td>
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<td style="width: 180.909px;" data-sheets-value='{"1":2,"2":"LG Corp"}' data-sheets-formula="=R[-30]C[0]">LG Corp</td>
<td style="text-align: right; width: 150.909px;" data-sheets-value='{"1":3,"3":0.27272027473479676}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">27.27%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":-0.026235211045486387}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-2.62%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":0.5671932907320105}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">56.72%</td>
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<td style="width: 180.909px;" data-sheets-value='{"1":2,"2":"Samsung C&amp;T Corp"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-30]C[0]">Samsung C&amp;T Corp</td>
<td style="text-align: right; width: 150.909px;" data-sheets-value='{"1":3,"3":-0.006511973440811065}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-0.65%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":-0.14552204142483482}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-14.55%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":0.0747273432141876}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">7.47%</td>
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<td style="width: 180.909px;" data-sheets-value='{"1":2,"2":"SK Inc"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-30]C[0]">SK Inc</td>
<td style="text-align: right; width: 150.909px;" data-sheets-value='{"1":3,"3":-0.06531341088823561}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-6.53%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":-0.21895641555030068}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-21.90%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":0.07921083141757403}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">7.92%</td>
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<td style="width: 180.909px;" data-sheets-value='{"1":2,"2":"Lotte Corp"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-30]C[0]">Lotte Corp</td>
<td style="text-align: right; width: 150.909px;" data-sheets-value='{"1":3,"3":0.004316013360576035}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">0.43%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":-0.2435059662116036}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-24.35%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":0.2347904810497161}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">23.48%</td>
</tr>
<tr>
<td style="width: 180.909px;" data-sheets-value='{"1":2,"2":"Hanwha Corp"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-30]C[0]">Hanwha Corp</td>
<td style="text-align: right; width: 150.909px;" data-sheets-value='{"1":3,"3":-0.03301422776748001}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-3.30%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":-0.20602404741618788}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-20.60%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":0.09499308319149713}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">9.50%</td>
</tr>
<tr>
<td style="width: 180.909px;" data-sheets-value='{"1":2,"2":"CJ Corp"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-30]C[0]">CJ Corp</td>
<td style="text-align: right; width: 150.909px;" data-sheets-value='{"1":3,"3":0.06798750716362237}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">6.80%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":-0.09780200889716528}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-9.78%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":0.19502041976348705}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">19.50%</td>
</tr>
<tr>
<td style="width: 180.909px;" data-sheets-value='{"1":2,"2":"Kolmar Korea Holdings Co Ltd"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]' data-sheets-formula="=R[-30]C[0]">* Kolmar Korea Holdings Co Ltd</td>
<td style="text-align: right; width: 150.909px;" data-sheets-value='{"1":3,"3":0.06471060029942335}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">6.47%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":-0.07838372679745396}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">-7.84%</td>
<td style="text-align: right; width: 164.545px;" data-sheets-value='{"1":3,"3":0.20003594429551463}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R[0]C5-R[0]C[4])/R[0]C[4]">20.00%</td>
</tr>
<tr><td colspan="4" rowspan="1" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table>

I added Kolmar Korea Holdings to my synthetic subsidiary holding company list. As a result, I now track a total of 7 synthetic subsidiary holding companies, of which 3 names are currently at -1.0σ (or close) on a 20-day moving average.  







Holdco
Subsidiaries in a synthetic
Sigma (σ) on a 20-day moving average


LG Corp
LG Chem Ltd &amp; 3 others
0.95


Samsung C&amp;T Corp
Samsung Electronics Co Ltd &amp; 1 other
-0.34


SK Inc
SK Innovation Co Ltd &amp; 2 others
-1.54


Lotte Corp
Lotte Chemical Corp &amp; 1 other
0.49


Hanwha Corp
Hanwha Solutions Corp &amp; 2 others
-0.91


CJ Corp
CJ Cheiljedang Corp &amp; 1 other
-0.30


* Kolmar Korea Holdings Co Ltd
KolmarBNH Co Ltd &amp; 1 other
-1.23

Source: KRX

Starting with this insight, I made some changes in my calculation of NAV. I estimated each holding company's operating operation based on their latest de-consolidated operating profit. It is mostly brand royalty and office rental income. I used operating profit to exclude dividend income.The revised NAV discount calculations show that they are trading mostly within a 50~60% discount to the NAV. The largest discount goes to Samsung C&amp;T, while CJ Corp enjoys the lowest discount to its NAV. Kolmar Korea Holdings features a 53.41% discount to the NAV. It is a two-subsidiary holding company as they account for 89.85% of the NAV.








Discount &amp; weight
NAV discount
Synthetic subsidiary weight in NAV
Synthetic subsidiary weight in GAV


LG Corp
58.93%
74.70%
77.03%


Samsung C&amp;T Corp
60.60%
80.26%
80.33%


SK Inc
51.73%
68.98%
55.61%


Lotte Corp
59.68%
59.45%
46.05%


Hanwha Corp
58.53%
87.72%
57.36%


CJ Corp
47.01%
83.03%
71.47%


* Kolmar Korea Holdings Co Ltd
53.41%
89.85%
83.96%

Source: KRX

SK Inc and Hanwha Corp are trading 6.53% and 3.30%, respectively, below the 180-day price ratio average relative to their synthetic subsidiaries. As for Kolmar Korea, it is 6.47% above the 180-day mean.








Price ratio
%Δ to 180-day mean
%Δ to 180-day high
%Δ to 180-day low


LG Corp
27.27%
-2.62%
56.72%


Samsung C&amp;T Corp
-0.65%
-14.55%
7.47%


SK Inc
-6.53%
-21.90%
7.92%


Lotte Corp
0.43%
-24.35%
23.48%


Hanwha Corp
-3.30%
-20.60%
9.50%


CJ Corp
6.80%
-9.78%
19.50%


* Kolmar Korea Holdings Co Ltd
6.47%
-7.84%
20.00%

Source: KRX



Korea Synthetic Subsidiary Stub Trade: 7 in Total with 1 New One

The Korea Fair Trade Commission (KFTC) annually designates local conglomerates having an aggregate asset value of more than ₩5T as a Business Group Subject to Disclosure. These are the largest industrial conglomerates designated as a Business Group Subject to Disclosure as of the last yearend.









Rank
Conglomerate
Aggregate asset value
Number of subsidiaries
Holdco type


1
Samsung
₩424.9T
59
De-facto operating holdco


2
Hyundai Motor
₩234.7T
54
-


3
SK
₩225.5T
125
Legitimate operating holdco


4
LG
₩137.0T
70
Legitimate pure holdco


5
Lotte
₩121.5T
86
Legitimate pure holdco


6
POSCO
₩80.3T
35
-


7
Hanwha
₩71.7T
86
De-facto pure holdco


8
GS
₩66.8T
69
Legitimate pure holdco


9
Hyundai Heavy Industries
₩62.9T
30
Legitimate pure holdco


10
Shinsegae
₩44.1T
41
-


11
KT
₩36.3T
44
-


12
CJ
₩34.5T
77
Legitimate pure holdco


13
Hanjin
₩33.6T
31
Legitimate pure holdco


14
Doosan
₩29.3T
25
De facto pure holdco


15
LS
₩23.7T
54
Legitimate operating holdco


16
Booyoung
₩23.3T
23
-


17
DL
₩18.7T
32
Legitimate operating holdco

Source: Kore Fair Trade Commission

Of these 17 largest industrial conglomerates having an aggregate asset value of more than ₩20T, 6 business groups are suitable for pair trading with a synthetic subsidiary.
Samsung Group
SK Group
LG Group
Lotte Group
Hanwha Group
CJ Group
Hyundai Motor Group is a circular shareholding structure, not suitable for pair trading. POSCO, Shinsegae, KT, LS, and DL have substantial operating operations outweighing their respective listed subsidiaries. GS and Hyundai Heavy Industries have a significant presence from the unlisted companies: GS Caltex and Hyundai Oilbank. Hanjin and Doosan are more of single-subsidiary holding companies. Lastly, Booyoung is a privately-held company.Discount to NAV Samsung C&amp;T has the highest discount to the NAV at 62.77%, followed by SK Inc with 52.14%. On the other hand, CJ Corp has the lowest discount at 34.19%. Hanwha Corp also has a lower discount than the others at 38.87%.











NAV
LG Corp
Samsung C&amp;T Corp
SK Inc
Lotte Corp
Hanwha Corp
CJ Corp


Value of listed holdings
₩41,080.4B
₩52,346.7B
₩24,237.4B
₩5,377.5B
₩4,501.4B
₩5,038.1B


- % of Holdco market cap
188.20%
201.51%
128.30%
139.29%
195.29%
158.42%


Value of unlisted holdings
₩2,631.7B
₩2,528.3B
₩9,890.5B
₩1,147.7B
₩1,657.0B
₩311.7B


Stub value
-₩21,883.7B
-₩28,897.7B
-₩15,236.2B
-₩2,664.6B
-₩3,853.5B
-₩2,169.5B


Stub value per share
-₩126,820
-₩154,626
-₩216,545
-₩25,399
-₩51,408
-₩74,357


Value of operating assets
₩0.0B
₩6,100.3B
₩2,235.2B
₩0.0B
₩0.0B
₩0.0B


GAV
₩43,712.1B
₩60,975.2B
₩36,363.1B
₩6,525.2B
₩6,158.4B
₩5,349.8B


GAV per share
₩253,320
₩373,019
₩695,187
₩92,157
₩89,623
₩197,713


Discount to GAV (excl. treasury shares)
50.06%
62.74%
61.38%
60.07%
65.69%
44.87%


Holdco net cash/debt (de-consolidated)
₩1,941.8B
₩268.6B
-₩6,879.4B
-₩1,764.4B
-₩2,330.8B
-₩357.6B


Value of pref shares
₩329.8B
₩219.7B
₩140.4B
₩63.2B
₩371.0B
₩510.3B


NAV
₩45,324.1B
₩61,024.1B
₩29,343.3B
₩4,697.6B
₩3,456.7B
₩4,481.9B


NAV per share (excl. treasury shares)
₩262,662
₩373,318
₩560,983
₩66,346
₩50,304
₩165,638


Discount to NAV
51.84%
62.77%
52.14%
44.53%
38.87%
34.19%

Source: KRX &amp; DART

Synthetic subsidiary weightThe number of subsidiaries in a synthetic varies from 2 to 4, representing 67.91% to 130.22% of the NAV. LG Corp has 4, the most, having a synthetic weight of 87.87% of the NAV. SK Inc has 3 subsidiaries in its synthetic, representing 67.91% of the NAV. 









Holdco pair
Number of subsidiaries in a synthetic
Synthetic subsidiary weight in NAV
Synthetic subsidiary weight in GAV


LG Corp
4
87.87%
91.11%


Samsung C&amp;T Corp
2
76.04%
76.10%


SK Inc
3
67.91%
54.80%


Lotte Corp
2
80.47%
57.93%


Hanwha Corp
3
130.22%
73.09%


CJ Corp
2
99.77%
83.58%

Source: KRX

Sigma on a 20-day moving averageWhen I'm writing this post (2 PM in Korea local time today), SK Inc and Hanwha Corp are in a diversion below -1.0σ on a 20-day moving average relative to their respective synthetic subsidiary. In contrast, CJ Corp is in a 2.0σ diversion, just the opposite way.











Sigma (σ) on a 20-day moving average
Today
T-1
T-2
T-3
T-4


LG Corp
0.87
1.02
1.26
1.39
1.56


Samsung C&amp;T Corp
-0.47
-0.55
0.30
-2.25
-2.53


SK Inc
-1.41
-1.64
-1.67
-1.74
-1.81


Lotte Corp
0.86
1.44
1.91
1.97
2.64


Hanwha Corp
-1.16
-0.77
-0.96
0.44
1.35


CJ Corp
1.92
1.03
0.54
0.82
1.83

Source: KRX



Korea Top Conglomerates Synthetic Pair Trading

Pan-Asia Catalysts/Events, Quiddity Advisors

David Blennerhassett

Pan-Asia Catalysts/Events

Quiddity Advisors

Last Week in Event SPACE:  Swire, Hitachi Metal, Jardine, Softbank, Bingo, Japan Asia, Mainstream

Korea/Asia, Events, IPOs, Douglas Research Advisory

Douglas Kim

Korea/Asia, Events, IPOs

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).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 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

South Korea

Hanwha Corporation imports and exports petrochemicals, machinery, automotives, electronics, and steel.  The Company also produces explosives for the defense and construction industries.  In addition, Hanwha manufactures automotive airbag inflators and telecommunication equipment, such as wireless phones and provides financial services through its subsidiaries.

Price Gauge
52-week Range	0.00 - 0.00
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Hanwha Corporation (000880 KS)

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52-week Range

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