Global Emerging Market Equities, Propitious Research

Wium Malan, CFA

Global Emerging Market Equities

Independent, Fundamental Quantitative Research

Propitious Research

Fully independent, fundamental and quantitative equity research, focused on companies in the Telecommunication, Media, Technology, Internet and Healthcare sectors in the Global Emerging Markets. Idea generation focused on Quality stocks, trading below their intrinsic Value, with sound Corporate Governance.

Quantitative Analysis

<p>This insight provides the output, and an overview of our, machine learning-driven, proprietary GEM screening model, which takes a three-pronged approach to find the best medium-term long ideas within the top100 largest stocks in the MSCI GEM Index. </p><p>The model is based on 1) a typical quantitative multifactor screening model, enhanced by two Artificial Intelligence Technology-based approaches using 2) a Deep Neural Network model, and 3) a Recurrent Neural Network model. </p><p>This model, which has been developed and tweaked over the past 24 months (and implemented in its current state for &gt;12 months), has a solid real-world performance track record, which I set out in the detail below. </p><p>Notable new entrants to the top decile this month include Russian energy plays <a href="https://www.smartkarma.com/entities/gazprom-pjsc-6a7231a9-d5e4-4da4-bf21-aa1b9d50fbf8" target="_blank" data-smartkarma-citation="entities:27578:1" rel="noopener">Gazprom PJSC (GAZP RM)</a> and <a href="https://www.smartkarma.com/entities/lukoil-pjsc" target="_blank" data-smartkarma-citation="entities:24141:1" rel="noopener">Lukoil PJSC (LKOD LI)</a>, Brazilian securities exchange <a href="https://www.smartkarma.com/entities/b3-sa-brasil-bolsa-balcao" target="_blank" data-smartkarma-citation="entities:24580:1" rel="noopener">B3 Sa - Brasil Bolsa Balcao (B3SA3 BZ)</a>, and <a href="https://www.smartkarma.com/entities/china-construction-bank-h" target="_blank" data-smartkarma-citation="entities:45:1" rel="noopener">China Construction Bank H (939 HK)</a>.</p><table class="table table-striped">
<colgroup>
<col>
<col>
<col>
<col>
<col>
</colgroup>
<tbody>
<tr>
<td style="text-align: center; width: 74.7344px;">rank</td>
<td style="width: 263.203px;">Name</td>
<td style="width: 185.312px;">Sector</td>
<td style="width: 147.938px;">Location</td>
<td style="text-align: center; width: 74.8125px;">prev.</td>
</tr>
<tr>
<td style="text-align: center; width: 74.7344px;">1</td>
<td style="width: 263.203px;">
<a href="https://www.smartkarma.com/entities/sk-hynix-inc" target="_blank" data-smartkarma-citation="entities:16955:1" rel="noopener">SK Hynix (000660 KS)</a> </td>
<td style="width: 185.312px;">Information Technology</td>
<td style="width: 147.938px;">Korea (South)</td>
<td style="text-align: center; width: 74.8125px;">3</td>
</tr>
<tr>
<td style="text-align: center; width: 74.7344px;">2</td>
<td style="width: 263.203px;">
<a href="https://www.smartkarma.com/entities/china-mobile-ltd" target="_blank" data-smartkarma-citation="entities:27:1" rel="noopener">China Mobile (941 HK)</a> </td>
<td style="width: 185.312px;">Communication</td>
<td style="width: 147.938px;">China</td>
<td style="text-align: center; width: 74.8125px;">9</td>
</tr>
<tr>
<td style="text-align: center; width: 74.7344px;">3</td>
<td style="width: 263.203px;">
<a href="https://www.smartkarma.com/entities/cnooc-ltd" target="_blank" data-smartkarma-citation="entities:175:1" rel="noopener">CNOOC Ltd (883 HK)</a> </td>
<td style="width: 185.312px;">Energy</td>
<td style="width: 147.938px;">China</td>
<td style="text-align: center; width: 74.8125px;">1</td>
</tr>
<tr>
<td style="text-align: center; width: 74.7344px;">4</td>
<td style="width: 263.203px;">
<a href="https://www.smartkarma.com/entities/posco" target="_blank" data-smartkarma-citation="entities:208:1" rel="noopener">Posco (005490 KS)</a> </td>
<td style="width: 185.312px;">Materials</td>
<td style="width: 147.938px;">Korea (South)</td>
<td style="text-align: center; width: 74.8125px;">21</td>
</tr>
<tr>
<td style="text-align: center; width: 74.7344px;">5</td>
<td style="width: 263.203px;">
<a href="https://www.smartkarma.com/entities/kia-motors-corp" target="_blank" data-smartkarma-citation="entities:156:1" rel="noopener">Kia Motors Corp (000270 KS)</a> </td>
<td style="width: 185.312px;">Consumer Discretionary</td>
<td style="width: 147.938px;">Korea (South)</td>
<td style="text-align: center; width: 74.8125px;">4</td>
</tr>
<tr>
<td style="text-align: center; width: 74.7344px;">6</td>
<td style="width: 263.203px;">
<a href="https://www.smartkarma.com/entities/bank-of-china-ltd-h" target="_blank" data-smartkarma-citation="entities:656:1" rel="noopener">Bank Of China Ltd (H) (3988 HK)</a> </td>
<td style="width: 185.312px;">Financials</td>
<td style="width: 147.938px;">China</td>
<td style="text-align: center; width: 74.8125px;">5</td>
</tr>
<tr>
<td style="text-align: center; width: 74.7344px;">7</td>
<td style="width: 263.203px;">
<a href="https://www.smartkarma.com/entities/gazprom-pjsc-6a7231a9-d5e4-4da4-bf21-aa1b9d50fbf8" target="_blank" data-smartkarma-citation="entities:27578:1" rel="noopener">Gazprom PJSC (GAZP RM)</a> </td>
<td style="width: 185.312px;">Energy</td>
<td style="width: 147.938px;">Russian Federation</td>
<td style="text-align: center; width: 74.8125px;">14</td>
</tr>
<tr>
<td style="text-align: center; width: 74.7344px;">8</td>
<td style="width: 263.203px;">
<a href="https://www.smartkarma.com/entities/lukoil-pjsc" target="_blank" data-smartkarma-citation="entities:24141:1" rel="noopener">Lukoil PJSC (LKOD LI)</a> </td>
<td style="width: 185.312px;">Energy</td>
<td style="width: 147.938px;">Russian Federation</td>
<td style="text-align: center; width: 74.8125px;">32</td>
</tr>
<tr>
<td style="text-align: center; width: 74.7344px;">9</td>
<td style="width: 263.203px;">
<a href="https://www.smartkarma.com/entities/b3-sa-brasil-bolsa-balcao" target="_blank" data-smartkarma-citation="entities:24580:1" rel="noopener">B3 Sa - Brasil Bolsa Balcao (B3SA3 BZ)</a> </td>
<td style="width: 185.312px;">Financials</td>
<td style="width: 147.938px;">Brazil</td>
<td style="text-align: center; width: 74.8125px;">70</td>
</tr>
<tr>
<td style="text-align: center; width: 74.7344px;">10</td>
<td style="width: 263.203px;">
<a href="https://www.smartkarma.com/entities/china-construction-bank-h" target="_blank" data-smartkarma-citation="entities:45:1" rel="noopener">China Construction Bank H (939 HK)</a> </td>
<td style="width: 185.312px;">Financials</td>
<td style="width: 147.938px;">China</td>
<td style="text-align: center; width: 74.8125px;">41</td>
</tr>
<tr><td colspan="5" style="text-align: left; width: 746px;"><em>Source: FactSet financial data and analytics, my estimates and calculations, Tensorflow, Keras, Google Colaboratory, pandas</em></td></tr>
</tbody>
</table><p><em>As usual, please feel free to reach out for the full output table, any questions, clarifications needed or suggestions.</em></p>

This insight provides the output, and an overview of our, machine learning-driven, proprietary GEM screening model, which takes a three-pronged approach to find the best medium-term long ideas within the top100 largest stocks in the MSCI GEM Index. The model is based on 1) a typical quantitative multifactor screening model, enhanced by two Artificial Intelligence Technology-based approaches using 2) a Deep Neural Network model, and 3) a Recurrent Neural Network model. This model, which has been developed and tweaked over the past 24 months (and implemented in its current state for &gt;12 months), has a solid real-world performance track record, which I set out in the detail below. Notable new entrants to the top decile this month include Russian energy plays Gazprom PJSC (GAZP RM) and Lukoil PJSC (LKOD LI), Brazilian securities exchange B3 Sa - Brasil Bolsa Balcao (B3SA3 BZ), and China Construction Bank H (939 HK).









rank
Name
Sector
Location
prev.


1

SK Hynix (000660 KS) 
Information Technology
Korea (South)
3


2

China Mobile (941 HK) 
Communication
China
9


3

CNOOC Ltd (883 HK) 
Energy
China
1


4

Posco (005490 KS) 
Materials
Korea (South)
21


5

Kia Motors Corp (000270 KS) 
Consumer Discretionary
Korea (South)
4


6

Bank Of China Ltd (H) (3988 HK) 
Financials
China
5


7

Gazprom PJSC (GAZP RM) 
Energy
Russian Federation
14


8

Lukoil PJSC (LKOD LI) 
Energy
Russian Federation
32


9

B3 Sa - Brasil Bolsa Balcao (B3SA3 BZ) 
Financials
Brazil
70


10

China Construction Bank H (939 HK) 
Financials
China
41

Source: FactSet financial data and analytics, my estimates and calculations, Tensorflow, Keras, Google Colaboratory, pandas

As usual, please feel free to reach out for the full output table, any questions, clarifications needed or suggestions.

Korea/Asia, Events, IPOs, Douglas Research Advisory

Douglas Kim

Korea/Asia, Events, IPOs

Cross Asset Strategy

<div class="content-highlight"><p>According to the KRX, it plans to launch new indices which would include the top 10 stocks in KOSPI including <a href="https://www.smartkarma.com/entities/samsung-electronics-co-ltd" target="_blank" data-smartkarma-citation="entities:191:1" rel="noopener">Samsung Electronics (005930 KS)</a>. The name of this index is expected to be called <strong>KOSPI 200 Top 10.</strong> There will also be 2x levered indices based off the KOSPI 200 Top 10 index. These indices will be catered for those investors that are interested in the highest market cap companies within KOSPI 200.</p></div><p>Currently, the top 10 constitutents of the KOSPI 200 Top 10 Index will be expected to be composed of the following:</p><ol>
<li>
<a href="https://www.smartkarma.com/entities/samsung-electronics-co-ltd" target="_blank" data-smartkarma-citation="entities:191:1" rel="noopener">Samsung Electronics (005930 KS)</a> </li>
<li>
<a href="https://www.smartkarma.com/entities/sk-hynix-inc" target="_blank" data-smartkarma-citation="entities:16955:1" rel="noopener">SK Hynix (000660 KS)</a> </li>
<li>
<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> </li>
<li>
<a href="https://www.smartkarma.com/entities/naver-corp" target="_blank" data-smartkarma-citation="entities:16029:1" rel="noopener">Naver Corp (035420 KS)</a> </li>
<li>
<a href="https://www.smartkarma.com/entities/hyundai-motor-co" target="_blank" data-smartkarma-citation="entities:155:1" rel="noopener">Hyundai Motor Co (005380 KS)</a> </li>
<li>
<a href="https://www.smartkarma.com/entities/samsung-sdi-co-ltd" target="_blank" data-smartkarma-citation="entities:503:1" rel="noopener">Samsung SDI (006400 KS)</a> </li>
<li>
<a href="https://www.smartkarma.com/entities/celltrion-inc" target="_blank" data-smartkarma-citation="entities:991:1" rel="noopener">Celltrion Inc (068270 KS)</a> </li>
<li>
<a href="https://www.smartkarma.com/entities/kakao-corp" target="_blank" data-smartkarma-citation="entities:15002:1" rel="noopener">Kakao Corp (035720 KS)</a> </li>
<li>
<a href="https://www.smartkarma.com/entities/kia-motors-corp" target="_blank" data-smartkarma-citation="entities:156:1" rel="noopener">Kia Motors Corp (000270 KS)</a> </li>
<li>
<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> </li>
</ol>

According to the KRX, it plans to launch new indices which would include the top 10 stocks in KOSPI including Samsung Electronics (005930 KS). The name of this index is expected to be called KOSPI 200 Top 10. There will also be 2x levered indices based off the KOSPI 200 Top 10 index. These indices will be catered for those investors that are interested in the highest market cap companies within KOSPI 200.Currently, the top 10 constitutents of the KOSPI 200 Top 10 Index will be expected to be composed of the following:

Samsung Electronics (005930 KS) 

SK Hynix (000660 KS) 

LG Chem Ltd (051910 KS) 

Naver Corp (035420 KS) 

Hyundai Motor Co (005380 KS) 

Samsung SDI (006400 KS) 

Celltrion Inc (068270 KS) 

Kakao Corp (035720 KS) 

Kia Motors Corp (000270 KS) 

Hyundai Mobis (012330 KS) 


KRX Plans to Launch a New Index Called 'KOSPI 200 Top 10'

<p>This insight provides the output, and an overview of our, machine learning-driven, proprietary GEM screening model, which takes a three-pronged approach to find the best medium-term long ideas within the top100 largest stocks in the MSCI GEM Index. </p><p>The model is based on 1) a typical quantitative multifactor screening model, enhanced by two Artificial Intelligence Technology-based approaches using 2) a Deep Neural Network model, and 3) a Recurrent Neural Network model. </p><p>This model, which has been developed and tweaked over the past 24 months (and implemented in its current state for &gt;12 months), has a solid real-world performance track record, which I set out in the detail below. </p><p>Notable new entrants to the top decile this month include South Korean auto names, <a href="https://www.smartkarma.com/entities/kia-motors-corp" target="_blank" data-smartkarma-citation="entities:156:1" rel="noopener">Kia Motors Corp (000270 KS)</a> and <a href="https://www.smartkarma.com/entities/hyundai-motor-co" target="_blank" data-smartkarma-citation="entities:155:1" rel="noopener">Hyundai Motor Co (005380 KS)</a> as well as Brazilian state-owned energy giant, <a href="https://www.smartkarma.com/entities/petroleo-brasileiro-sa" target="_blank" data-smartkarma-citation="entities:24459:1" rel="noopener">Petroleo Brasileiro Sa (PETR3 BZ)</a>.</p><table class="table table-striped">
<colgroup>
<col>
<col>
<col>
<col>
<col>
</colgroup>
<tbody>
<tr>
<td style="text-align: center; width: 48pt;">rank</td>
<td style="width: 169pt;">Name</td>
<td style="width: 119pt;">Sector</td>
<td style="width: 95pt;">Location</td>
<td style="text-align: center; width: 48pt;">prev.</td>
</tr>
<tr>
<td style="text-align: center;">1</td>
<td><a href="https://www.smartkarma.com/entities/cnooc-ltd" target="_blank" data-smartkarma-citation="entities:175:1" rel="noopener">CNOOC Ltd (883 HK)</a></td>
<td>Energy</td>
<td>China</td>
<td style="text-align: center;">1</td>
</tr>
<tr>
<td style="text-align: center;">2</td>
<td><a href="https://www.smartkarma.com/entities/mediatek-inc" target="_blank" data-smartkarma-citation="entities:772:1" rel="noopener">Mediatek Inc (2454 TT)</a></td>
<td>Information Technology</td>
<td>Taiwan</td>
<td style="text-align: center;">5</td>
</tr>
<tr>
<td style="text-align: center;">3</td>
<td><a href="https://www.smartkarma.com/entities/sk-hynix-inc" target="_blank" data-smartkarma-citation="entities:16955:1" rel="noopener">SK Hynix (000660 KS)</a></td>
<td>Information Technology</td>
<td>Korea (South)</td>
<td style="text-align: center;">23</td>
</tr>
<tr>
<td style="text-align: center;">4</td>
<td><a href="https://www.smartkarma.com/entities/kia-motors-corp" target="_blank" data-smartkarma-citation="entities:156:1" rel="noopener">Kia Motors Corp (000270 KS)</a></td>
<td>Consumer Discretionary</td>
<td>Korea (South)</td>
<td style="text-align: center;">60</td>
</tr>
<tr>
<td style="text-align: center;">5</td>
<td><a href="https://www.smartkarma.com/entities/bank-of-china-ltd-h" target="_blank" data-smartkarma-citation="entities:656:1" rel="noopener">Bank Of China Ltd (H) (3988 HK)</a></td>
<td>Financials</td>
<td>China</td>
<td style="text-align: center;">25</td>
</tr>
<tr>
<td style="text-align: center;">6</td>
<td><a href="https://www.smartkarma.com/entities/ptt-pcl" target="_blank" data-smartkarma-citation="entities:197:1" rel="noopener">PTT PCL (PTT TB)</a></td>
<td>Energy</td>
<td>Thailand</td>
<td style="text-align: center;">4</td>
</tr>
<tr>
<td style="text-align: center;">7</td>
<td><a href="https://www.smartkarma.com/entities/samsung-electronics-co-ltd" target="_blank" data-smartkarma-citation="entities:191:1" rel="noopener">Samsung Electronics (005930 KS)</a></td>
<td>Information Technology</td>
<td>Korea (South)</td>
<td style="text-align: center;">9</td>
</tr>
<tr>
<td style="text-align: center;">8</td>
<td><a href="https://www.smartkarma.com/entities/hyundai-motor-co" target="_blank" data-smartkarma-citation="entities:155:1" rel="noopener">Hyundai Motor Co (005380 KS)</a></td>
<td>Consumer Discretionary</td>
<td>Korea (South)</td>
<td style="text-align: center;">80</td>
</tr>
<tr>
<td style="text-align: center;">9</td>
<td><a href="https://www.smartkarma.com/entities/china-mobile-ltd" target="_blank" data-smartkarma-citation="entities:27:1" rel="noopener">China Mobile (941 HK)</a></td>
<td>Communication</td>
<td>China</td>
<td style="text-align: center;">29</td>
</tr>
<tr>
<td style="text-align: center;">10</td>
<td><a href="https://www.smartkarma.com/entities/petroleo-brasileiro-sa" target="_blank" data-smartkarma-citation="entities:24459:1" rel="noopener">Petroleo Brasileiro Sa (PETR3 BZ)</a></td>
<td>Energy</td>
<td>Brazil</td>
<td style="text-align: center;">59</td>
</tr>
<tr><td colspan="5" style="text-align: left;"><em>Source: FactSet financial data and analytics, my estimates and calculations, Tensorflow, Keras, Google Colaboratory, pandas</em></td></tr>
</tbody>
</table><p><em>As usual, please feel free to reach out for the full output table, any questions, clarifications needed or suggestions.</em></p>

This insight provides the output, and an overview of our, machine learning-driven, proprietary GEM screening model, which takes a three-pronged approach to find the best medium-term long ideas within the top100 largest stocks in the MSCI GEM Index. The model is based on 1) a typical quantitative multifactor screening model, enhanced by two Artificial Intelligence Technology-based approaches using 2) a Deep Neural Network model, and 3) a Recurrent Neural Network model. This model, which has been developed and tweaked over the past 24 months (and implemented in its current state for &gt;12 months), has a solid real-world performance track record, which I set out in the detail below. Notable new entrants to the top decile this month include South Korean auto names, Kia Motors Corp (000270 KS) and Hyundai Motor Co (005380 KS) as well as Brazilian state-owned energy giant, Petroleo Brasileiro Sa (PETR3 BZ).









rank
Name
Sector
Location
prev.


1
CNOOC Ltd (883 HK)
Energy
China
1


2
Mediatek Inc (2454 TT)
Information Technology
Taiwan
5


3
SK Hynix (000660 KS)
Information Technology
Korea (South)
23


4
Kia Motors Corp (000270 KS)
Consumer Discretionary
Korea (South)
60


5
Bank Of China Ltd (H) (3988 HK)
Financials
China
25


6
PTT PCL (PTT TB)
Energy
Thailand
4


7
Samsung Electronics (005930 KS)
Information Technology
Korea (South)
9


8
Hyundai Motor Co (005380 KS)
Consumer Discretionary
Korea (South)
80


9
China Mobile (941 HK)
Communication
China
29


10
Petroleo Brasileiro Sa (PETR3 BZ)
Energy
Brazil
59

Source: FactSet financial data and analytics, my estimates and calculations, Tensorflow, Keras, Google Colaboratory, pandas

As usual, please feel free to reach out for the full output table, any questions, clarifications needed or suggestions.

Korea / Special Situations, Clepsydra Capital

Sanghyun Park

Korea / Special Situations

Korea / Special Sits, Pairs, Index Rebalancing

Clepsydra Capital

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

Event-Driven

<p>Hyundai mobis continues to be in a harsh diversion relative to its siblings, Kia Corp and Hyundai Motor. It is at a -2.25σ on a 20-day moving average vs. Kia Corp. The 20-day sigma relative to Hyundai Motor is -1.55 now. </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: 147.682px;" data-sheets-value='{"1":2,"2":"Comp 1 (Long)"}'>Comp 1 (Long)</td>
<td style="width: 115.56px;" data-sheets-value='{"1":2,"2":"Comp 2 (Short)"}'>Comp 2 (Short)</td>
<td style="text-align: right; width: 117.552px;" 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: 127.604px;" data-sheets-value='{"1":2,"2":"180-day correlation coefficient"}'>180-day correlation coefficient</td>
<td style="text-align: right; width: 133.659px;" 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: 147.682px;" data-sheets-value='{"1":2,"2":"HYUNDAI MOBIS CO., LTD."}' data-sheets-formula="=Data!R[-1]C[1]"><strong>HYUNDAI MOBIS CO., LTD.</strong></td>
<td style="width: 115.56px;" data-sheets-value='{"1":2,"2":"Kia Corp"}' data-sheets-formula="=Data!R[-1]C[1]"><strong>Kia Corp</strong></td>
<td style="text-align: right; width: 117.552px;" data-sheets-value='{"1":3,"3":-2.2518639492767143}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-2.25</strong></td>
<td style="text-align: right; width: 127.604px;" data-sheets-value='{"1":3,"3":0.7480010585761807}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula='=correl(index(googlefinance(R[0]C[2], "price",today()-200, today()), 0,2), index(googlefinance(R[0]C[3], "price",today()-200, today()), 0,2))'>0.75</td>
<td style="text-align: right; width: 133.659px;" data-sheets-value='{"1":3,"3":0.5563729124603229}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[2]C[-3]">0.56</td>
</tr>
<tr>
<td style="width: 147.682px;" data-sheets-value='{"1":2,"2":"HYUNDAI MOBIS CO., LTD."}' data-sheets-formula="=Data!R[-2]C[3]"><strong>HYUNDAI MOBIS CO., LTD.</strong></td>
<td style="width: 115.56px;" data-sheets-value='{"1":2,"2":"Hyundai Motor Co"}' data-sheets-formula="=Data!R[-2]C[3]"><strong>Hyundai Motor Co</strong></td>
<td style="text-align: right; width: 117.552px;" data-sheets-value='{"1":3,"3":-1.5544482164241549}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=R[8]C[-1]"><strong>-1.55</strong></td>
<td style="text-align: right; width: 127.604px;" data-sheets-value='{"1":3,"3":0.929675478057548}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula='=correl(index(googlefinance(R[0]C[2], "price",today()-200, today()), 0,2), index(googlefinance(R[0]C[3], "price",today()-200, today()), 0,2))'>0.93</td>
<td style="text-align: right; width: 133.659px;" data-sheets-value='{"1":3,"3":0.7886057127133221}' data-sheets-numberformat='[null,2,"#,##0.00",1]' data-sheets-formula="=Beta!R[1]C[-1]">0.79</td>
</tr>
<tr><td colspan="5" style="width: 726.016px;">Source: KRX</td></tr>
</tbody>
</table><p>The current price ratio is 19.25% and 9.09% below the 180-day mean vs. Kia Corp and Hyundai Motor, respectively. Mobis is currently at a 180-day low to both Kia and Hyundai Motor.</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: 149.466px;" data-sheets-value='{"1":2,"2":"Comp 1 (Long)"}'>Comp 1 (Long)</td>
<td style="width: 120.391px;" data-sheets-value='{"1":2,"2":"Comp 2 (Short)"}'>Comp 2 (Short)</td>
<td style="text-align: right; width: 118.372px;" data-sheets-value='{"1":2,"2":"Price ratio %Δ to 180-day mean"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]'>Price ratio %Δ to 180-day mean</td>
<td style="text-align: right; width: 128.398px;" data-sheets-value='{"1":2,"2":"Price ratio %Δ to 180-day high"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]'>Price ratio %Δ to 180-day high</td>
<td style="text-align: right; width: 125.43px;" data-sheets-value='{"1":2,"2":"Price ratio %Δ to 180-day low"}' data-sheets-numberformat='[null,4,"[$₩]#,##0"]'>Price ratio %Δ to 180-day low</td>
</tr>
<tr>
<td style="width: 149.466px;" data-sheets-value='{"1":2,"2":"HYUNDAI MOBIS CO., LTD."}' data-sheets-formula="=R[-16]C[0]"><strong>HYUNDAI MOBIS CO., LTD.</strong></td>
<td style="width: 120.391px;" data-sheets-value='{"1":2,"2":"Kia Corp"}' data-sheets-formula="=R[-16]C[0]"><strong>Kia Corp</strong></td>
<td style="text-align: right; width: 118.372px;" data-sheets-value='{"1":3,"3":-0.19253623208265946}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C6-R[0]C[4])/R[0]C[4]"><strong>-19.25%</strong></td>
<td style="text-align: right; width: 128.398px;" data-sheets-value='{"1":3,"3":-0.3974244135311329}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C6-R[0]C[4])/R[0]C[4]">-39.74%</td>
<td style="text-align: right; width: 125.43px;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C6-R[0]C[4])/R[0]C[4]">0.00%</td>
</tr>
<tr>
<td style="width: 149.466px;" data-sheets-value='{"1":2,"2":"HYUNDAI MOBIS CO., LTD."}' data-sheets-formula="=R[-16]C[0]"><strong>HYUNDAI MOBIS CO., LTD.</strong></td>
<td style="width: 120.391px;" data-sheets-value='{"1":2,"2":"Hyundai Motor Co"}' data-sheets-formula="=R[-16]C[0]"><strong>Hyundai Motor Co</strong></td>
<td style="text-align: right; width: 118.372px;" data-sheets-value='{"1":3,"3":-0.09085981735173156}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C6-R[0]C[4])/R[0]C[4]"><strong>-9.09%</strong></td>
<td style="text-align: right; width: 128.398px;" data-sheets-value='{"1":3,"3":-0.18788573693448832}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C6-R[0]C[4])/R[0]C[4]">-18.79%</td>
<td style="text-align: right; width: 125.43px;" data-sheets-value='{"1":3,"3":0}' data-sheets-numberformat='[null,3,"0.00%",1]' data-sheets-formula="=(R[0]C6-R[0]C[4])/R[0]C[4]">0.00%</td>
</tr>
<tr><td colspan="5" style="width: 726.016px;">Source: KRX</td></tr>
</tbody>
</table><section class="figure"><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/209/837/original/HYUNDAI+MOBIS+CO.%2C+LTD.+vs.+Kia+Corp.png?1622273377" class="editor-image img-responsive" data-smartkarma-image-id="209837"></figure></section><section class="figure"><figure class="editor-figure mceNonEditable"><img src="https://static-prod.smartkarma.com/images/media/000/209/838/original/HYUNDAI+MOBIS+CO.%2C+LTD.+vs.+Hyundai+Motor+Co.png?1622273387" class="editor-image img-responsive" data-smartkarma-image-id="209838"></figure></section>

Hyundai mobis continues to be in a harsh diversion relative to its siblings, Kia Corp and Hyundai Motor. It is at a -2.25σ on a 20-day moving average vs. Kia Corp. The 20-day sigma relative to Hyundai Motor is -1.55 now. 









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


HYUNDAI MOBIS CO., LTD.
Kia Corp
-2.25
0.75
0.56


HYUNDAI MOBIS CO., LTD.
Hyundai Motor Co
-1.55
0.93
0.79

Source: KRX

The current price ratio is 19.25% and 9.09% below the 180-day mean vs. Kia Corp and Hyundai Motor, respectively. Mobis is currently at a 180-day low to both Kia and Hyundai Motor.









Comp 1 (Long)
Comp 2 (Short)
Price ratio %Δ to 180-day mean
Price ratio %Δ to 180-day high
Price ratio %Δ to 180-day low


HYUNDAI MOBIS CO., LTD.
Kia Corp
-19.25%
-39.74%
0.00%


HYUNDAI MOBIS CO., LTD.
Hyundai Motor Co
-9.09%
-18.79%
0.00%

Source: KRX



Korea Sector Pair: Hyundai Mobis Vs. Kia and Hyundai Motor

Asset Allocation & Fund Positioning, Copley Fund Research

Steven Holden

Asset Allocation & Fund Positioning

Copley Fund Research

Copley Fund Research provide research and data on asset allocation among Global and Emerging Market equity funds.  The analysis details absolute and relative positioning across countries, sectors and industries together with highly granular data on single stock and single fund allocations.  The data is updated monthly with time series going back to January 2011.

Global Research - Analysis of 165 prominent Global equity funds, combined AUM $335bn
GEM Research - Analysis of 127 prominent global EM equity funds, combined AUM $250bn

Asset Allocation - Global and GEM Equity

Thematic (Sector/Industry)

<p>EM Autos are the 10th largest industry group weight among active EM managers, with average weights of 1.55%.  The more interesting metric however, is the extent to which Autos have become one of the largest industry level underweights across global EM.  The increased underweight has almost exclusively been driven by two stocks, <a href="https://www.smartkarma.com/entities/nio-inc" target="_blank" data-smartkarma-citation="entities:27399:1" rel="noopener">NIO Inc (NIO US)</a> and <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>, with both seeing benchmark weights rise on the back of strong price increases.</p><p>Such outright volatility has created a challenge for active managers who are benchmarked to the MSCI Emerging Markets Index.   Namely, how do you position yourself in a prominent index component that rises 900% in the space of 12 months?  The temptation might be to add <a href="https://www.smartkarma.com/entities/nio-inc" target="_blank" data-smartkarma-citation="entities:27399:1" rel="noopener">NIO Inc (NIO US)</a> to a portfolio to dampen some of that benchmark risk, and indeed we have seen that happening among managers with low active shares.</p><p>However, so far, high active managers have remained on the sidelines, sticking instead with more established autos stocks of <a href="https://www.smartkarma.com/entities/kia-motors-corp" target="_blank" data-smartkarma-citation="entities:156:1" rel="noopener">Kia Motors Corp (000270 KS)</a> , <a href="https://www.smartkarma.com/entities/geely-automobile-holdings-ltd" target="_blank" data-smartkarma-citation="entities:127:1" rel="noopener">Geely Auto (175 HK)</a> and <a href="https://www.smartkarma.com/entities/hero-motocorp-ltd" target="_blank" data-smartkarma-citation="entities:2391:1" rel="noopener">Hero Motocorp (HMCL IN)</a>.  Therefore, there is very little peer group risk in avoiding either <a href="https://www.smartkarma.com/entities/nio-inc" target="_blank" data-smartkarma-citation="entities:27399:1" rel="noopener">NIO Inc (NIO US)</a> or <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> .  In fact, if a high active manager decides to invest in either stock, it will represent an out-of-consensus long compared to the majority of your active peers.</p>

EM Autos are the 10th largest industry group weight among active EM managers, with average weights of 1.55%.  The more interesting metric however, is the extent to which Autos have become one of the largest industry level underweights across global EM.  The increased underweight has almost exclusively been driven by two stocks, NIO Inc (NIO US) and BYD (1211 HK, with both seeing benchmark weights rise on the back of strong price increases.Such outright volatility has created a challenge for active managers who are benchmarked to the MSCI Emerging Markets Index.   Namely, how do you position yourself in a prominent index component that rises 900% in the space of 12 months?  The temptation might be to add NIO Inc (NIO US) to a portfolio to dampen some of that benchmark risk, and indeed we have seen that happening among managers with low active shares.However, so far, high active managers have remained on the sidelines, sticking instead with more established autos stocks of Kia Motors Corp (000270 KS) , Geely Auto (175 HK) and Hero Motocorp (HMCL IN).  Therefore, there is very little peer group risk in avoiding either NIO Inc (NIO US) or BYD (1211 HK) .  In fact, if a high active manager decides to invest in either stock, it will represent an out-of-consensus long compared to the majority of your active peers.

EM Autos Underweight:  Ignore Benchmark Risk and Focus on Peers

South Korea

Kia Corporation manufactures, sells, and exports passenger cars, mini-buses, trucks and commercial vehicles. The Company also manufactures auto-parts and tools using hybrid electric and fuel cell technology. Kia markets its products worldwide.

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Kia Corp (000270 KS)

Screening for GEMs: July 2021

This insight provides an overview of our, machine learning-driven, proprietary GEM screening model, based on a Multifactor model, a Deep Neural...

Wium Malan, CFA

KRX Plans to Launch a New Index Called 'KOSPI 200 Top 10'

According to the KRX, it plans to launch new indices which would include the top 10 stocks in KOSPI. The name of this index is expected to be...

Douglas Kim

Screening for GEMs: June 2021

This insight provides an overview of our, machine learning-driven, proprietary GEM screening model, based on a Multifactor model, a Deep Neural...

Wium Malan, CFA

Korea Sector Pair: Hyundai Mobis Vs. Kia and Hyundai Motor

This post examines the continued diversion in Hyundai Mobis vs. Kia Corp and Hyundai Motor and discusses why we should see a reversion at this point.

Sanghyun Park

EM Autos Underweight: Ignore Benchmark Risk and Focus on Peers

EM Autos have become one of the largest industry level underweights across global EM. The increased underweight has almost exclusively been driven...

Steven Holden

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