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">
</colgroup>
<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">
<colgroup>
<col width="200">
<col width="200">
<col width="70">
<col width="70">
<col width="70">
</colgroup>
<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">
<col width="70">
<col width="70">
</colgroup>
<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

Equity Capital Markets

Hanwha Systems Co Ltd / Equity Capital Markets

<p>Hanwha Systems announced a ₩1.2T rights offer at a 71.39% capital increase rate.</p><p>Per-share allocation for stockholders is 0.58124 as 20% goes to the ESOP.</p><p>The pricing discount is 15%, a little more aggressive than the usual 20%.</p><p>The ex-rights fall on April 21, with the preliminary pricing on April 19. The final pricing will be out on May 31. You can trade subscription rights between May 13~20.</p><table class="table table-striped">
<colgroup>
<col width="300">
<col width="300">
</colgroup>
<tbody>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Overview"}'>Overview</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Issuer"}'>Issuer</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Hanwha Systems Co Ltd"}' data-sheets-formula='=googlefinance(R[1]C[0], "name")'>Hanwha Systems Co Ltd</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Ticker"}'>Ticker</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"272210"}' data-sheets-formula='="272210"'>272210</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Target"}'>Target</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"A public offering of forfeited shares after offering to stockholders"}'>A public offering of forfeited shares after offering to stockholders</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Transferability"}'>Transferability</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Renounceable"}'>Renounceable</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Volume"}'>Volume</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":78689000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>78,689,000</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Bonus issue volume"}'>Bonus issue volume</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>0</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Preliminary price"}'>Preliminary price</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":15250}' data-sheets-numberformat='{"1":2,"2":"[$₩-412]#,##0","3":1}'>₩15,250</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Preliminary value"}'>Preliminary value</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1200007250000}' data-sheets-numberformat='{"1":2,"2":"[$₩-412]#,##0","3":1}' data-sheets-formula="=R[-3]C[0]*R[-1]C[0]">₩1,200,007,250,000</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Oversubscription privilege"}'>Oversubscription privilege</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.2}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}'>20.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Banker"}'>Banker</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Daishin &amp; KIS"}'>Daishin &amp; KIS</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Underwriting type"}'>- Underwriting type</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Standby"}'>Standby</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="300">
<col width="300">
</colgroup>
<tbody>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Allocation"}'>Allocation</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Common"}'>Common</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":110230389}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula='=googlefinance(R[-13]C[0], "shares")'>110,230,389</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Pref (incl. RCPS &amp; CPS)"}'>Pref (incl. RCPS &amp; CPS)</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>0</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Total shares"}'>Total shares</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":110230389}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-2]C[0]+R[-1]C[0]">110,230,389</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Treasury shares"}'>Treasury shares</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1926128}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>1,926,128</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Total shares ex treasury shares"}'>Total shares ex treasury shares</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":108304261}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-2]C[0]-R[-1]C[0]">108,304,261</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Offer volume"}'><strong>Offer volume</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":78689000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[1]C[0]+R[2]C[0]"><strong>78,689,000</strong></td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Common"}'><strong>- Common</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":78689000}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-16]C[0]"><strong>78,689,000</strong></td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Pref"}'><strong>- Pref</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'><strong>0</strong></td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Per-share allocation"}'><strong>Per-share allocation</strong></td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.58124398263518}' data-sheets-numberformat='{"1":2,"2":"#,##0.0000000","3":1}' data-sheets-formula="=R[15]C[0]/R[-4]C[0]"><strong>0.5812440</strong></td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Capital increase"}'>Capital increase</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.7138594058667433}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[-4]C[0]/R[-7]C[0]">71.39%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Dilution"}'>Dilution</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.41652156730191414}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[-5]C[0]/(R[-8]C[0]+R[-5]C[0])">41.65%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Total shares after rights offer"}'>Total shares after rights offer</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":188919389}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[1]C[0]+R[2]C[0]">188,919,389</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Common"}'>- Common</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":188919389}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-12]C[0]+R[-7]C[0]">188,919,389</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Pref"}'>- Pref</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-12]C[0]">0</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Bonus issue"}'>Bonus issue</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[1]C[0]+R[2]C[0]">0</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Common"}'>- Common</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>0</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Pref"}'>- Pref</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}'>0</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Per-share allocation"}'>Per-share allocation</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":2,"2":"#,##0.0000000","3":1}' data-sheets-formula="=R[-3]C[0]/(R[-6]C[0]-R[-14]C[0])">0.0000000</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Total shares after bonus issue"}'>Total shares after bonus issue</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":188919389}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[1]C[0]+R[2]C[0]">188,919,389</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Common"}'>- Common</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":188919389}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-7]C[0]+R[-4]C[0]">188,919,389</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Pref"}'>- Pref</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-7]C[0]+R[-4]C[0]">0</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"ESOP allocation"}'>ESOP allocation</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":15737800}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-16]C[0]*R[1]C[0]">15,737,800</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - %"}'>- %</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.2}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}'>20.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Stockholder allocation"}'>Stockholder allocation</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":62951200}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-18]C[0]-R[-2]C[0]">62,951,200</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - %"}'>- %</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.8}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=R[-1]C[0]/R[-19]C[0]">80.00%</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="300">
<col width="300">
</colgroup>
<tbody>
<tr><td colspan="2" rowspan="1" data-sheets-value='{"1":2,"2":"Timetable"}'>Timetable</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"BOD meeting"}'>BOD meeting</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44284}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'>2021. 3. 29</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Preliminary pricing"}'>Preliminary pricing</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":"Ex-rights date"}'>Ex-rights 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":"Record date"}'>Record date</td>
<td style="text-align: right;" 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 data-sheets-value='{"1":2,"2":"Subscription rights trade beginning"}'>Subscription rights trade beginning</td>
<td style="text-align: right;" 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 data-sheets-value='{"1":2,"2":"Subscription rights trade ending"}'>Subscription rights trade ending</td>
<td style="text-align: right;" 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 data-sheets-value='{"1":2,"2":"Final pricing"}'>Final pricing</td>
<td style="text-align: right;" 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 data-sheets-value='{"1":2,"2":"Stockholder subscription"}'>Stockholder subscription</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44350}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'>2021. 6. 3</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Public subscription"}'>Public subscription</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44355}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'>2021. 6. 8</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Payment"}'>Payment</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":44358}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}'>2021. 6. 11</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Listing"}'>Listing</td>
<td style="text-align: right;" 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" rowspan="1" data-sheets-value='{"1":2,"2":"Source: DART"}'>Source: DART</td></tr>
</tbody>
</table><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"}'>1st round</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;")]"))'>RP × (1 - 15%) / [1 + (71.39% × 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, 1M VWAP)]"}'>Min [Close, Avg (Close, 1W VWAP, 1M 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":44305}' data-sheets-numberformat='{"1":5,"2":"yyyy. m. d","3":1}' data-sheets-formula="=Terms!R[41]C[0]">2021. 4. 19</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>

Hanwha Systems announced a ₩1.2T rights offer at a 71.39% capital increase rate.Per-share allocation for stockholders is 0.58124 as 20% goes to the ESOP.The pricing discount is 15%, a little more aggressive than the usual 20%.The ex-rights fall on April 21, with the preliminary pricing on April 19. The final pricing will be out on May 31. You can trade subscription rights between May 13~20.





Overview

Issuer
Hanwha Systems Co Ltd


Ticker
272210


Target
A public offering of forfeited shares after offering to stockholders


Transferability
Renounceable


Volume
78,689,000


Bonus issue volume
0


Preliminary price
₩15,250


Preliminary value
₩1,200,007,250,000


Oversubscription privilege
20.00%


Banker
Daishin &amp; KIS


- Underwriting type
Standby

Source: DART







Allocation

Common
110,230,389


Pref (incl. RCPS &amp; CPS)
0


Total shares
110,230,389


Treasury shares
1,926,128


Total shares ex treasury shares
108,304,261


Offer volume
78,689,000


- Common
78,689,000


- Pref
0


Per-share allocation
0.5812440


Capital increase
71.39%


Dilution
41.65%


Total shares after rights offer
188,919,389


- Common
188,919,389


- Pref
0


Bonus issue
0


- Common
0


- Pref
0


Per-share allocation
0.0000000


Total shares after bonus issue
188,919,389


- Common
188,919,389


- Pref
0


ESOP allocation
15,737,800


- %
20.00%


Stockholder allocation
62,951,200


- %
80.00%

Source: DART







Timetable

BOD meeting
2021. 3. 29


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


Stockholder subscription
2021. 6. 3


Public subscription
2021. 6. 8


Payment
2021. 6. 11


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



Hanwha Systems ₩1.2T Rights Offer Summary & Dynamics

Korea/Asia, Events, IPOs, Douglas Research Advisory

Douglas Kim

Korea/Asia, Events, IPOs

Cross Asset Strategy

<div class="content-highlight"><p>In this insight, we discuss about the winners and losers among the top 100 stocks in KOSPI, especially in the most recent <strong>"KOSPI Box trading range"</strong> lasting from 8 January to 10 February 2021 (see chart below). Sometimes, finding out what stocks and sectors outperform in a box trading range could lead to some<strong> clues</strong> in helping to understand what stocks and sectors could outperform in the coming weeks. From 8 January to 10 February, KOSPI has been trading in a box range and its is down slightly (1.6%) in this period. </p></div>

In this insight, we discuss about the winners and losers among the top 100 stocks in KOSPI, especially in the most recent "KOSPI Box trading range" lasting from 8 January to 10 February 2021 (see chart below). Sometimes, finding out what stocks and sectors outperform in a box trading range could lead to some clues in helping to understand what stocks and sectors could outperform in the coming weeks. From 8 January to 10 February, KOSPI has been trading in a box range and its is down slightly (1.6%) in this period. 

Winners & Losers in the KOSPI Box Trading Range & Return of Money Velocity Post End of Lock Down?

Global Special Situations & Strategy, SR Services Ltd

David Lepper

Global Special Situations & Strategy

SR Services Ltd

SR Services provides Strategic Knowledge and Solutions services for Family Offices and Corporate Business. 

We deliver this via advisory services, strategic planning, opportunity analysis/sourcing, as well as solution implementation. 

Whilst, we create intellectual discipline and operational leverage for your projects or daily activities, our ultimate objective is to empower whilst enhancing your decision making. 

Strategic Knowledge and Solutions

<p>Whilst Q4's list posted strong price performance it was a case that a rising tide floated most boats. As in the previous few quarters, we are on the watch for the risk of deteriorating credit metrics, but in particular during H1 2021. In Q1, the Altman Z score is at a market-cap-weighted 1.03 times, a significant decrease on the 1.52 in Q4. This deterioration needs to be monitored since earnings continue to be adjusted by analysts and their limited visibility of any bottoming. 25 stocks appear in our Q1 2021 screen, versus 15 in Q4 2020.</p>

Whilst Q4's list posted strong price performance it was a case that a rising tide floated most boats. As in the previous few quarters, we are on the watch for the risk of deteriorating credit metrics, but in particular during H1 2021. In Q1, the Altman Z score is at a market-cap-weighted 1.03 times, a significant decrease on the 1.52 in Q4. This deterioration needs to be monitored since earnings continue to be adjusted by analysts and their limited visibility of any bottoming. 25 stocks appear in our Q1 2021 screen, versus 15 in Q4 2020.

Screening the Silk Road: Q1 2021 High Risk Names to Avoid

<p><strong>Q3 delivered marked underperformance</strong></p><p>Our Q3-2020 Small-Mid Cap High-Risk list of stocks produced an average price increase of 0.3%. In comparison, the MSCI Asia Pacific Index posted an increase of 6.3% over the same period. 15 stocks appear in our Q4 2020 screen, versus 21 in Q3 2020. As we highlighted in the previous three quarters, we are specifically on the watch for the risk of deteriorating credit metrics during 2020. This screen presents names which are worthy of investigation as they present with fundamentals which are at risk.</p>

Q3 delivered marked underperformanceOur Q3-2020 Small-Mid Cap High-Risk list of stocks produced an average price increase of 0.3%. In comparison, the MSCI Asia Pacific Index posted an increase of 6.3% over the same period. 15 stocks appear in our Q4 2020 screen, versus 21 in Q3 2020. As we highlighted in the previous three quarters, we are specifically on the watch for the risk of deteriorating credit metrics during 2020. This screen presents names which are worthy of investigation as they present with fundamentals which are at risk.

Screening the Silk Road: Q4 2020 High Risk Names to Avoid

South Korea

Korea Aerospace Industries Ltd. designs and produces aircraft parts including fixed wings for aircrafts and rotary wings for helicopters. The Company also engages in aircraft upgrade and modification business and satellite development business.

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

Korea Aerospace Industries (047810 KS)

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This post summarizes Hanwha Systems' massive rights offer (₩1.2T) and examines the questionable aspects for trading approach.

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Our Q3 screen delivered 600bps of under performance. With volatility is set to increase as we head into H1 2020, which stocks are most at risk in...

David Lepper

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