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

Brian Freitas

Pan-Asia Index Rebalances/ Events/ Delta One

Quantitative Analysis

<div><p>The Asia Short Interest weekly looks at moves in market wide short interest and highlights movements in stock specific short interest across Hong Kong, Japan, Korea and Taiwan using the last available data published by the relevant authorities.</p></div><div><p>Hong Kong saw shorts rise on <a href="https://www.smartkarma.com/entities/byd-co-ltd-h" target="_blank" data-smartkarma-citation="entities:20962:1" rel="noopener">BYD (1211 HK)</a>, <a href="https://www.smartkarma.com/entities/meituan-dianping" target="_blank" data-smartkarma-citation="entities:26970:1" rel="noopener">Meituan (3690 HK)</a>, <a href="https://www.smartkarma.com/entities/tencent-holdings-ltd" target="_blank" data-smartkarma-citation="entities:26:1" rel="noopener">Tencent Holdings (700 HK)</a>, <a href="https://www.smartkarma.com/entities/alibaba-group" target="_blank" data-smartkarma-citation="entities:28434:1" rel="noopener">Alibaba Group (9988 HK)</a> and <a href="https://www.smartkarma.com/entities/hong-kong-exchanges-clearing" target="_blank" data-smartkarma-citation="entities:490:1" rel="noopener">HKEX (388 HK)</a> while there was short covering on <a href="https://www.smartkarma.com/entities/smoore-international" target="_blank" data-smartkarma-citation="entities:28241:1" rel="noopener">Smoore International (6969 HK)</a>, <a href="https://www.smartkarma.com/entities/gcl-poly-energy-holdings-limited" target="_blank" data-smartkarma-citation="entities:3708:1" rel="noopener">Gcl Poly Energy Holdings Limited (3800 HK)</a>, <a href="https://www.smartkarma.com/entities/innovent-biologics-inc" target="_blank" data-smartkarma-citation="entities:27452:1" rel="noopener">Innovent Biologics Inc (1801 HK)</a>, <a href="https://www.smartkarma.com/entities/sunny-optical-tech" target="_blank" data-smartkarma-citation="entities:13363:1" rel="noopener">Sunny Optical (2382 HK)</a> and <a href="https://www.smartkarma.com/entities/xiaomi-corp" target="_blank" data-smartkarma-citation="entities:24409:1" rel="noopener">Xiaomi Corp (1810 HK)</a>. Shorts increased on Consumer Discretionary, Communication Services, Financials, Consumer Staples and Industrials, while decreasing on Information Technology, Real Estate and Health Care.</p></div><div><p>In Japan, stocks that saw the most shorts were <a href="https://www.smartkarma.com/entities/olympus-corp" target="_blank" data-smartkarma-citation="entities:356:1" rel="noopener">Olympus Corp (7733 JP)</a>, <a href="https://www.smartkarma.com/entities/dai-ichi-life-insurance" target="_blank" data-smartkarma-citation="entities:1109:1" rel="noopener">Dai Ichi Life Insurance (8750 JP)</a>, <a href="https://www.smartkarma.com/entities/nomura-holdings-inc" target="_blank" data-smartkarma-citation="entities:742:1" rel="noopener">Nomura Holdings (8604 JP)</a> and <a href="https://www.smartkarma.com/entities/mitsubishi-ufj-financial-group" target="_blank" data-smartkarma-citation="entities:218:1" rel="noopener">Mitsubishi UFJ Financial (MUFG) (8306 JP)</a> while shorts decreased on <a href="https://www.smartkarma.com/entities/anritsu-corp" target="_blank" data-smartkarma-citation="entities:3700:1" rel="noopener">Anritsu Corp (6754 JP)</a>, <a href="https://www.smartkarma.com/entities/lasertec-corp" target="_blank" data-smartkarma-citation="entities:4126:1" rel="noopener">Lasertec Corp (6920 JP)</a>, <a href="https://www.smartkarma.com/entities/sharp-corp" target="_blank" data-smartkarma-citation="entities:391:1" rel="noopener">Sharp Corp (6753 JP)</a> and <a href="https://www.smartkarma.com/entities/square-enix-holdings-co-ltd" target="_blank" data-smartkarma-citation="entities:15003:1" rel="noopener">Square Enix Holdings (9684 JP)</a>. Sectorally, shorts increased on Financials, Industrials and Health Care, while decreasing on Information Technology and Consumer Discretionary.</p></div><div><p>In Korea, there were short positions put on in <a href="https://www.smartkarma.com/entities/lg-display-co-ltd" target="_blank" data-smartkarma-citation="entities:7145:1" rel="noopener">LG Display (034220 KS)</a>, <a href="https://www.smartkarma.com/entities/gs-engineering-construct" target="_blank" data-smartkarma-citation="entities:15916:1" rel="noopener">GS Engineering &amp; Construction (006360 KS)</a>, <a href="https://www.smartkarma.com/entities/lg-chem-ltd" target="_blank" data-smartkarma-citation="entities:3583:1" rel="noopener">LG Chem Ltd (051910 KS)</a> and <a href="https://www.smartkarma.com/entities/hyundai-mobis-co-ltd" target="_blank" data-smartkarma-citation="entities:6089:1" rel="noopener">Hyundai Mobis (012330 KS)</a> while shorts were covered in <a href="https://www.smartkarma.com/entities/netmarble-corporation" target="_blank" data-smartkarma-citation="entities:22839:1" rel="noopener">Netmarble Corporation (251270 KS)</a>, <a href="https://www.smartkarma.com/entities/samsung-biologics-co-ltd" target="_blank" data-smartkarma-citation="entities:22932:1" rel="noopener">Samsung Biologics Co., (207940 KS)</a>, <a href="https://www.smartkarma.com/entities/celltrion-inc" target="_blank" data-smartkarma-citation="entities:991:1" rel="noopener">Celltrion Inc (068270 KS)</a> and <a href="https://www.smartkarma.com/entities/kakao-corp" target="_blank" data-smartkarma-citation="entities:15002:1" rel="noopener">Kakao Corp (035720 KS)</a>. </p></div><div>
<p>Stocks in Taiwan that saw the highest increase in shorts were <a href="https://www.smartkarma.com/entities/united-microelectronics-corp" target="_blank" data-smartkarma-citation="entities:6450:1" rel="noopener">United Microelectronics Corp (2303 TT)</a>, <a href="https://www.smartkarma.com/entities/innolux-corp" target="_blank" data-smartkarma-citation="entities:4509:1" rel="noopener">Innolux Corp (3481 TT)</a>, <a href="https://www.smartkarma.com/entities/e-sun-financial-holding-co" target="_blank" data-smartkarma-citation="entities:719:1" rel="noopener">E.Sun Financial Holding Co (2884 TT)</a> and <a href="https://www.smartkarma.com/entities/taiwan-semiconductor-manufacturing-company" target="_blank" data-smartkarma-citation="entities:11230:1" rel="noopener">TSMC (2330 TT)</a> while shorts were covered on <a href="https://www.smartkarma.com/entities/evergreen-marine-corp-ltd" target="_blank" data-smartkarma-citation="entities:15428:1" rel="noopener">Evergreen Marine Corp (2603 TT)</a>, <a href="https://www.smartkarma.com/entities/acer-inc" target="_blank" data-smartkarma-citation="entities:15726:1" rel="noopener">Acer Inc (2353 TT)</a>, <a href="https://www.smartkarma.com/entities/pegatron-corp" target="_blank" data-smartkarma-citation="entities:12852:1" rel="noopener">Pegatron Corp (4938 TT)</a> and <a href="https://www.smartkarma.com/entities/ase-technology-holding-co-ltd" target="_blank" data-smartkarma-citation="entities:27270:1" rel="noopener">ASE Technology Holding Co Ltd (3711 TT)</a>.</p>
<p>Following the <a href="https://www.smartkarma.com/entities/gamestop-corp-class-a" target="_blank" data-smartkarma-citation="entities:13790:1" rel="noopener">GameStop Corp Class A (GME US)</a> saga, we have added tables in each market with the largest stocks in terms of days of ADV to cover.</p>
</div>

The Asia Short Interest weekly looks at moves in market wide short interest and highlights movements in stock specific short interest across Hong Kong, Japan, Korea and Taiwan using the last available data published by the relevant authorities.Hong Kong saw shorts rise on BYD (1211 HK), Meituan (3690 HK), Tencent Holdings (700 HK), Alibaba Group (9988 HK) and HKEX (388 HK) while there was short covering on Smoore International (6969 HK), Gcl Poly Energy Holdings Limited (3800 HK), Innovent Biologics Inc (1801 HK), Sunny Optical (2382 HK) and Xiaomi Corp (1810 HK). Shorts increased on Consumer Discretionary, Communication Services, Financials, Consumer Staples and Industrials, while decreasing on Information Technology, Real Estate and Health Care.In Japan, stocks that saw the most shorts were Olympus Corp (7733 JP), Dai Ichi Life Insurance (8750 JP), Nomura Holdings (8604 JP) and Mitsubishi UFJ Financial (MUFG) (8306 JP) while shorts decreased on Anritsu Corp (6754 JP), Lasertec Corp (6920 JP), Sharp Corp (6753 JP) and Square Enix Holdings (9684 JP). Sectorally, shorts increased on Financials, Industrials and Health Care, while decreasing on Information Technology and Consumer Discretionary.In Korea, there were short positions put on in LG Display (034220 KS), GS Engineering &amp; Construction (006360 KS), LG Chem Ltd (051910 KS) and Hyundai Mobis (012330 KS) while shorts were covered in Netmarble Corporation (251270 KS), Samsung Biologics Co., (207940 KS), Celltrion Inc (068270 KS) and Kakao Corp (035720 KS). 
Stocks in Taiwan that saw the highest increase in shorts were United Microelectronics Corp (2303 TT), Innolux Corp (3481 TT), E.Sun Financial Holding Co (2884 TT) and TSMC (2330 TT) while shorts were covered on Evergreen Marine Corp (2603 TT), Acer Inc (2353 TT), Pegatron Corp (4938 TT) and ASE Technology Holding Co Ltd (3711 TT).
Following the GameStop Corp Class A (GME US) saga, we have added tables in each market with the largest stocks in terms of days of ADV to cover.


Asia Short Interest: BYD, Smoore, GCL Poly, Olympus, Nomura, Anritsu, Netmarble, UMC, Innolux, Acer

Korea / Special Situations, Clepsydra Capital

Sanghyun Park

Korea / Special Situations

Event-Driven

<p>It seems that the Glovis/Mobis pair's ongoing diversion wouldn't stop here. This morning, Glovis is again up 5%, whereas Mobis isn't moving anywhere.</p><p>On a 20D MA, the duo is pretty much at +3σ favoring Glovis.</p><table class="table table-striped">
<colgroup>
<col width="300">
<col width="300">
</colgroup>
<tbody>
<tr><td colspan="2" data-sheets-value='{"1":2,"2":"% of sigma"}'>% of sigma</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Today"}'>Today</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.79721147999682}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">279.72%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"T-1"}'>T-1</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.90408093225351}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">290.41%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"T-2"}'>T-2</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":3.040840873644037}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">304.08%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"T-3"}'>T-3</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.181493534187003}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">218.15%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"T-4"}'>T-4</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.858730552874526}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">285.87%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"T-5"}'>T-5</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.2348493042227517}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">123.48%</td>
</tr>
<tr><td colspan="2" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><section class="figure"><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/165/349/original/chart.png?1602726889" class="editor-image img-responsive" data-smartkarma-image-id="165349"></figure></section><p>Price ratio-wise, Glovis is practically sitting at the 2-yr peak over Mobis, up 23% from the median.</p><table class="table table-striped">
<colgroup>
<col width="300">
<col width="150">
<col width="150">
</colgroup>
<tbody>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Price ratio"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Price ratio</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Today"}'>Today</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.7607758620689655}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-21]C[1]">0.76078</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"20D MA"}'>20D MA</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6404340532612001}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-22]C[2]">0.64043</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"σ"}'>σ</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.04302206310403898}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-23]C[5]">0.04302</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"+1 σ"}' data-sheets-formula='="+1 σ"'>+1 σ</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6834561163652391}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-24]C[3]">0.68346</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"-1 σ"}' data-sheets-formula='="-1 σ"'>-1 σ</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5974119901571611}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-25]C[4]">0.59741</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D mean"}'>120D mean</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5756111894671158}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C3:R100C3)">0.57561</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.321683587793472}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">32.17%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D median"}'>120D median</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5641025641025641}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R100C3)">0.56410</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.34864811912225707}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">34.86%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D high"}'>120D high</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.7607758620689655}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C3:R100C3)">0.76078</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">0.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D low"}'>120D low</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5127610208816705}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C3:R100C3)">0.51276</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.483685052270245}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">48.37%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y mean"}'>1Y mean</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5837054277414029}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C3:R248C3)">0.58371</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.30335581255894983}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">30.34%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y median"}'>1Y median</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5833333333333334}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R248C3)">0.58333</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.30418719211822653}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">30.42%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y high"}'>1Y high</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.7607758620689655}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C3:R248C3)">0.76078</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">0.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y low"}'>1Y low</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5127610208816705}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C3:R248C3)">0.51276</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.483685052270245}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">48.37%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y mean"}'>2Y mean</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6205364418447589}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C3:R476C3)">0.62054</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.22599707409172706}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">22.60%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y median"}'>2Y median</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.6187363834422658}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R476C3)">0.61874</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.22956380524526473}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">22.96%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y high"}'>2Y high</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.7777777777777778}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C3:R476C3)">0.77778</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.021859605911330054}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-2.19%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y low"}'>2Y low</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.5127610208816705}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C3:R476C3)">0.51276</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.483685052270245}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">48.37%</td>
</tr>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table><p>Glovis and Mobis are the most correlated stocks among the HMG subsidiaries despite the recent diversion (30D correlation coefficient at 0.36).</p><table class="table table-striped">
<colgroup>
<col width="300">
<col width="150">
<col width="150">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Correlation"}'>Correlation</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"Component 1"}'>Component 1</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"Component 2"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Component 2</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Name"}'>Name</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"Hyundai Glovis Co Ltd"}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula='=googlefinance(R[1]C[0], "name")'>Hyundai Glovis Co Ltd</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"HYUNDAI MOBIS CO., LTD."}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula='=googlefinance(R[1]C[0], "name")'>HYUNDAI MOBIS CO., LTD.</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Ticker"}'>Ticker</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"086280"}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula='="086280"'>086280</td>
<td style="text-align: center;" data-sheets-value='{"1":2,"2":"012330"}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula='="012330"'>012330</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Market cap (₩B)"}'>Market cap (₩B)</td>
<td style="text-align: center;" data-sheets-value='{"1":3,"3":6318.75}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=googlefinance(R[-1]C[0], "shares")*googlefinance(R[-1]C[0], "price")/1000000000'>6,318.8</td>
<td style="text-align: center;" data-sheets-value='{"1":3,"3":22005.161661}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=googlefinance(R[-1]C[0], "shares")*googlefinance(R[-1]C[0], "price")/1000000000'>22,005.2</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y"}'>2Y</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.831919620239351}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[-3]C[7]:R[489]C[7], PR!R[-3]C[8]:R[489]C[8])">0.83192</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y"}'>1Y</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.9318592319326688}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[261]C[7]:R[488]C[7], PR!R[261]C[8]:R[488]C[8])">0.93186</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"180D"}'>180D</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.9199477136645406}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[308]C[7]:R[487]C[7], PR!R[308]C[8]:R[487]C[8])">0.91995</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D"}'>120D</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.8692936956427101}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[367]C[7]:R[486]C[7], PR!R[367]C[8]:R[486]C[8])">0.86929</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"90D"}'>90D</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.8637633940567214}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[396]C[7]:R[485]C[7], PR!R[396]C[8]:R[485]C[8])">0.86376</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"30D"}'>30D</td>
<td colspan="2" rowspan="1" style="text-align: center;" data-sheets-value='{"1":3,"3":0.3569896000118052}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=correl(PR!R[455]C[7]:R[484]C[7], PR!R[455]C[8]:R[484]C[8])">0.35699</td>
</tr>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Source: KRX</td></tr>
</tbody>
</table><table class="table table-striped">
<colgroup>
<col width="300">
<col width="150">
<col width="150">
</colgroup>
<tbody>
<tr>
<td data-sheets-value='{"1":2,"2":"Liquidity (₩B)"}'>Liquidity (₩B)</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"Hyundai Glovis Co Ltd"}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-58]C[0]">Hyundai Glovis Co Ltd</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"HYUNDAI MOBIS CO., LTD."}' data-sheets-numberformat='{"1":2,"2":"#,##0","3":1}' data-sheets-formula="=R[-58]C[0]">HYUNDAI MOBIS CO., LTD.</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"MC"}'>MC</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":6318.75}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=googlefinance(R[-58]C[0], "price")*googlefinance(R[-58]C[0], "shares")/1000000000'>6,318.8</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":22005.161661}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=googlefinance(R[-58]C[0], "price")*googlefinance(R[-58]C[0], "shares")/1000000000'>22,005.2</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Avg. DTV"}'>Avg. DTV</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":211359}' data-sheets-numberformat='{"1":2,"2":"#,##0"}' data-sheets-formula='=googlefinance(R[-59]C[0], "volumeavg")'>211,359</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":428067}' data-sheets-numberformat='{"1":2,"2":"#,##0"}' data-sheets-formula='=googlefinance(R[-59]C[0], "volumeavg")'>428,067</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - Value"}'>- Value</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":35.6139915}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=R[-1]C[0]*googlefinance(R[-60]C[0], "price")/1000000000'>35.6</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":99.0975105}' data-sheets-numberformat='{"1":2,"2":"#,##0.0"}' data-sheets-formula='=R[-1]C[0]*googlefinance(R[-60]C[0], "price")/1000000000'>99.1</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":" - % of SO"}'>- % of SO</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.00563624}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula='=R[-2]C[0]/googlefinance(R[-61]C[0], "shares")'>0.56%</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.004503375709146989}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula='=R[-2]C[0]/googlefinance(R[-61]C[0], "shares")'>0.45%</td>
</tr>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX"}'>Source: KRX</td></tr>
</tbody>
</table>

It seems that the Glovis/Mobis pair's ongoing diversion wouldn't stop here. This morning, Glovis is again up 5%, whereas Mobis isn't moving anywhere.On a 20D MA, the duo is pretty much at +3σ favoring Glovis.





% of sigma

Today
279.72%


T-1
290.41%


T-2
304.08%


T-3
218.15%


T-4
285.87%


T-5
123.48%

Source: KRX

Price ratio-wise, Glovis is practically sitting at the 2-yr peak over Mobis, up 23% from the median.






Price ratio

Today
0.76078
-


20D MA
0.64043
-


σ
0.04302
-


+1 σ
0.68346
-


-1 σ
0.59741
-


120D mean
0.57561
32.17%


120D median
0.56410
34.86%


120D high
0.76078
0.00%


120D low
0.51276
48.37%


1Y mean
0.58371
30.34%


1Y median
0.58333
30.42%


1Y high
0.76078
0.00%


1Y low
0.51276
48.37%


2Y mean
0.62054
22.60%


2Y median
0.61874
22.96%


2Y high
0.77778
-2.19%


2Y low
0.51276
48.37%

Source: KRX

Glovis and Mobis are the most correlated stocks among the HMG subsidiaries despite the recent diversion (30D correlation coefficient at 0.36).







Correlation
Component 1
Component 2


Name
Hyundai Glovis Co Ltd
HYUNDAI MOBIS CO., LTD.


Ticker
086280
012330


Market cap (₩B)
6,318.8
22,005.2


2Y
0.83192


1Y
0.93186


180D
0.91995


120D
0.86929


90D
0.86376


30D
0.35699

Source: KRX









Liquidity (₩B)
Hyundai Glovis Co Ltd
HYUNDAI MOBIS CO., LTD.


MC
6,318.8
22,005.2


Avg. DTV
211,359
428,067


- Value
35.6
99.1


- % of SO
0.56%
0.45%

Source: KRX



Glovis/Mobis Diversion Is Reaching an Extreme for Three Reasons: Time to Trade on Reversion

Hyundai Mobis resumes buyback starting today (October 5).Mobis announced the 3-year shareholder return plan from 2019 to 2021, including a ₩1T buyback and ₩1.1T dividends.This time, the target is 0.96M ordinary shares, a bit less than the last one (1.3M shares for ₩323B). It represents 1.03% of the SO. At the previous close, it amounts to ₩226B, of which 28% will get canceled.The lock-up of the remaining bought-back shares is six months.It is the second buyback since the announcement. So, we will have one or two more buybacks by the end of 2021 for the remaining ₩450B to hit the ₩1T target.





Overview

Name
HYUNDAI MOBIS CO., LTD.


Ticker
012330


Shares outstanding
95,058,668


- Common
95,054,694


- Pref
3,974


Treasury shares
1,617,535


- Common
1,617,535


- Pref
0


Target qty.
983,000


- % of SO
1.03%


- Common
983,000


- % of total common shares
1.03%


- % of common treasury shares
60.77%


- Pref
0


- % of total pref shares
-


- % of pref treasury shares
-


Treasury shares after buyback
2,600,535


- % of SO
2.74%


- % of common
2.74%


- % of pref
-


Total value
₩226,090,000,000


- Common
₩226,090,000,000


- Pref
₩0


Market cap
₩21,863,493,640,000


- % of market cap
1.03%


Equity
₩23,500,426,547,075


- % of equity
0.96%


Cancellation
₩62,500,000,000


- % of total buyback
27.64%


- Qty.
271,739


Lock up for the remaining
Six months

Source: DART

The execution is until December 28, which gives us a total of 60 trading days.The daily limit is 130,000, a quarter of the 1M ADT, 11% of the target, and 0.1% of the SO.If it buys an equal quantity each day, 16K will be the number, representing 3.7% of the DTV.Hyundai Motor Securities will execute the trading, and it will buy all shares openly in the market.






Execution

Buyback begins
2020. 10. 5


Buyback ends
2020. 12. 28


Bankers
Hyundai Motor Securities


Method
Openly in the market (no off-hours block trade)


Daily limit
110,050


- % of 1M DTV
25.00%


- % of target qty.
11.20%


- % of the total common shares
0.12%


Number of trading days
60


Average daily equal buyback qty.
16,383


- % of 1M DTV
3.71%


- % of target qty.
1.67%


- % of the total common shares
0.02%


Value of average daily equal buyback qty.
₩3,768,166,667


Market cap
₩21,863,493,640,000


ADTV
₩101,511,420,000

Source: DART &amp; Google Finance


The treasury shares now account for 1.7%. The buyback/cancellation will put it at 2.5% of the SO. The major shareholders' stake will rise to 31.3% after the cancellation.








Shareholding
Before
After


Kia Motors Corporation
17.28%
17.33%


Chung Mong-koo
7.13%
7.15%


Hyundai Steel Co
5.79%
5.81%


Hyundai Glovis Co Ltd
0.69%
0.69%


Chung Eui-sun
0.32%
0.32%


- Major shareholder
31.22%
31.31%


Korea NPS
11.90%
11.93%


Mirae Asset
5.08%
5.10%


Treasury shares
1.70%
2.46%

Source: DART &amp; FnGuide



Hyundai Mobis Share Buyback: Terms & Trading Dynamics

Korea/Asia, Events, IPOs, Douglas Research Advisory

Douglas Kim

Korea/Asia, Events, IPOs

<div class="content-highlight">
<p>On 29 September, <a href="https://www.smartkarma.com/entities/hyundai-mobis-co-ltd" target="_blank" data-smartkarma-citation="entities:6089:1" rel="noopener">Hyundai Mobis (012330 KS)</a> announced that it will buy back 221 billion won (US$188 million) worth of its shares (983,000 shares), representing 1% of shares outstanding. Of the 221 billion won worth of share repurchase, it will cancel 62.5 billion won worth of shares. The share repurchase will occur from 5 October to 28 December 2020. </p>
<p>This share buyback is part of the 1 trillion won share buyback program (over 3 years period) that the company announced back in February 2019. Due to the uncertainties associated with COVID-19, Hyundai Mobis decided not to buy back shares in 1H 2020 but now with the COVID-19 partly under control in Korea, the company decided that now is the time to conduct share repurchase again. </p>
</div>


On 29 September, Hyundai Mobis (012330 KS) announced that it will buy back 221 billion won (US$188 million) worth of its shares (983,000 shares), representing 1% of shares outstanding. Of the 221 billion won worth of share repurchase, it will cancel 62.5 billion won worth of shares. The share repurchase will occur from 5 October to 28 December 2020. 
This share buyback is part of the 1 trillion won share buyback program (over 3 years period) that the company announced back in February 2019. Due to the uncertainties associated with COVID-19, Hyundai Mobis decided not to buy back shares in 1H 2020 but now with the COVID-19 partly under control in Korea, the company decided that now is the time to conduct share repurchase again. 


Hyundai Mobis - Restarts Its Big Share Buyback Program in 4Q 2020

<p>Hyundai Mobis is at -2.3σ on a 20D MA relative to its brother, Hyundai Motor ordinary share.</p><table class="table table-striped">
<colgroup>
<col width="200">
<col width="100">
</colgroup>
<tbody>
<tr><td colspan="2" rowspan="1" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"% of sigma"}'>% of sigma</td></tr>
<tr>
<td style="width: 351.818px;" data-sheets-value='{"1":2,"2":"Today"}'>Today</td>
<td style="text-align: right; width: 350.909px;" data-sheets-value='{"1":3,"3":-2.3035030515769517}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">-230.35%</td>
</tr>
<tr>
<td style="width: 351.818px;" data-sheets-value='{"1":2,"2":"T-1"}'>T-1</td>
<td style="text-align: right; width: 350.909px;" data-sheets-value='{"1":3,"3":-0.916931344299026}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">-91.69%</td>
</tr>
<tr>
<td style="width: 351.818px;" data-sheets-value='{"1":2,"2":"T-2"}'>T-2</td>
<td style="text-align: right; width: 350.909px;" data-sheets-value='{"1":3,"3":-0.5645130872563673}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">-56.45%</td>
</tr>
<tr>
<td style="width: 351.818px;" data-sheets-value='{"1":2,"2":"T-3"}'>T-3</td>
<td style="text-align: right; width: 350.909px;" data-sheets-value='{"1":3,"3":0.2465686874114751}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">24.66%</td>
</tr>
<tr>
<td style="width: 351.818px;" data-sheets-value='{"1":2,"2":"T-4"}'>T-4</td>
<td style="text-align: right; width: 350.909px;" data-sheets-value='{"1":3,"3":-0.4247825847315971}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">-42.48%</td>
</tr>
<tr>
<td style="width: 351.818px;" data-sheets-value='{"1":2,"2":"T-5"}'>T-5</td>
<td style="text-align: right; width: 350.909px;" data-sheets-value='{"1":3,"3":-0.09495037677635225}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=Data!R[-12]C[6]">-9.50%</td>
</tr>
<tr><td colspan="2" rowspan="1" style="width: 723.636px;" data-sheets-value='{"1":2,"2":"Source: KRX"}'><em>Source: KRX</em></td></tr>
</tbody>
</table><p>The price ratio between them is now practically at a 2-yr low.</p><table class="table table-striped">
<colgroup>
<col width="200">
<col width="100">
<col width="100">
</colgroup>
<tbody>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Price ratio"}' data-sheets-numberformat='{"1":2,"2":"#,##0"}'>Price ratio</td></tr>
<tr>
<td data-sheets-value='{"1":2,"2":"Today"}'>Today</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.2701949860724233}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-21]C[1]">1.27019</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"20D MA"}'>20D MA</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.3161097671656496}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-22]C[2]">1.31611</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"σ"}'>σ</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.0199325896537422}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-23]C[5]">0.01993</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"+1 σ"}' data-sheets-formula='="+1 σ"'>+1 σ</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.3360423568193918}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-24]C[3]">1.33604</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"-1 σ"}' data-sheets-formula='="-1 σ"'>-1 σ</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.2961771775119075}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=Data!R[-25]C[4]">1.29618</td>
<td style="text-align: right;" data-sheets-value='{"1":2,"2":"-"}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}'>-</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D mean"}'>120D mean</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.7010486771205928}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C3:R100C3)">1.70105</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.25328710274034383}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-25.33%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D median"}'>120D median</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.8409818569903948}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R100C3)">1.84098</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.3100448104638489}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-31.00%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D high"}'>120D high</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.0878048780487806}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C3:R100C3)">2.08780</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.391612214614844}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-39.16%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"120D low"}'>120D low</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.2691218130311614}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C3:R100C3)">1.26912</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.0008456028651014254}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">0.08%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y mean"}'>1Y mean</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.8509836907922768}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C3:R248C3)">1.85098</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.313772999518574}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-31.38%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y median"}'>1Y median</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.9119351100811124}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R248C3)">1.91194</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.3356495315269689}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-33.56%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y high"}'>1Y high</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.197309417040359}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C3:R248C3)">2.19731</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.4219316696037747}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-42.19%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"1Y low"}'>1Y low</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.2691218130311614}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C3:R248C3)">1.26912</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.0008456028651014254}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">0.08%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y mean"}'>2Y mean</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.7960316722025786}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=average(Data!R2C3:R476C3)">1.79603</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.2927769561464866}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-29.28%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y median"}'>2Y median</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.7972103004291846}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MEDIAN(Data!R2C3:R476C3)">1.79721</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.29324075998835913}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-29.32%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y high"}'>2Y high</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":2.197309417040359}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MAX(Data!R2C3:R476C3)">2.19731</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":-0.4219316696037747}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">-42.19%</td>
</tr>
<tr>
<td data-sheets-value='{"1":2,"2":"2Y low"}'>2Y low</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":1.2691218130311614}' data-sheets-numberformat='{"1":2,"2":"#,##0.00000","3":1}' data-sheets-formula="=MIN(Data!R2C3:R476C3)">1.26912</td>
<td style="text-align: right;" data-sheets-value='{"1":3,"3":0.0008456028651014254}' data-sheets-numberformat='{"1":3,"2":"0.00%","3":1}' data-sheets-formula="=(R23C[-1]-R[0]C[-1])/R[0]C[-1]">0.08%</td>
</tr>
<tr><td colspan="3" rowspan="1" data-sheets-value='{"1":2,"2":"Source: KRX &amp; Sanghyun Park"}'><em>Source: KRX</em></td></tr>
</tbody>
</table><p>The duo had undergone a harsh correction (price ratio-wise) in July. Since then, they have drifted sideways within a box.</p><p>So, this much short-term price diversion is the broadest since late July. </p><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/161/053/original/chart.png?1600897627" class="editor-image img-responsive" data-smartkarma-image-id="161053"></figure>

Hyundai Mobis is at -2.3σ on a 20D MA relative to its brother, Hyundai Motor ordinary share.





% of sigma

Today
-230.35%


T-1
-91.69%


T-2
-56.45%


T-3
24.66%


T-4
-42.48%


T-5
-9.50%

Source: KRX

The price ratio between them is now practically at a 2-yr low.






Price ratio

Today
1.27019
-


20D MA
1.31611
-


σ
0.01993
-


+1 σ
1.33604
-


-1 σ
1.29618
-


120D mean
1.70105
-25.33%


120D median
1.84098
-31.00%


120D high
2.08780
-39.16%


120D low
1.26912
0.08%


1Y mean
1.85098
-31.38%


1Y median
1.91194
-33.56%


1Y high
2.19731
-42.19%


1Y low
1.26912
0.08%


2Y mean
1.79603
-29.28%


2Y median
1.79721
-29.32%


2Y high
2.19731
-42.19%


2Y low
1.26912
0.08%

Source: KRX

The duo had undergone a harsh correction (price ratio-wise) in July. Since then, they have drifted sideways within a box.So, this much short-term price diversion is the broadest since late July. 

Hyundai Mobis/Motor At -2.3σ: Entry Point for Range Trading

South Korea

Hyundai Mobis Co., Ltd. manufactures and markets automotive parts and equipment, such as  automotive service components, modules, and systems. The Company also contractsenvironmental projects, including sewage treatment plant and industrial waste water treatment plant construction.

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

Hyundai Mobis (012330 KS)

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Price Gauge

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P/E

Dividend (Yield)

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