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 3 years (and implemented in its current state for 17 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 the beaten-down Chinese tech names such as <a href="https://www.smartkarma.com/entities/xiaomi-corp" target="_blank" data-smartkarma-citation="entities:24409:1" rel="noopener">Xiaomi Corp (1810 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>, <a href="https://www.smartkarma.com/entities/tencent-holdings-ltd" target="_blank" data-smartkarma-citation="entities:26:1" rel="noopener">Tencent (700 HK)</a> , and <a href="https://www.smartkarma.com/entities/jd-com-inc" target="_blank" data-smartkarma-citation="entities:29043:1" rel="noopener">JD.com Inc. (9618 HK)</a> as well as two Brazilian large caps in <a href="https://www.smartkarma.com/entities/vale-sa-7721577f-6c6a-4536-a829-92551c2bcd7f" target="_blank" data-smartkarma-citation="entities:27725:1" rel="noopener">Vale SA (VALE3 BZ)</a> and <a href="https://www.smartkarma.com/entities/ambev-sa" target="_blank" data-smartkarma-citation="entities:24454:1" rel="noopener">Ambev SA (ABEV3 BZ)</a>.</p><table class="table table-striped">
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<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/new-oriental-education-technology-group" target="_blank" data-smartkarma-citation="entities:32210:1" rel="noopener">New Oriental Education &amp; Technology Group (9901 HK)</a> </td>
<td>Consumer Discretionary</td>
<td>China</td>
<td style="text-align: center;">10</td>
</tr>
<tr>
<td style="text-align: center;">2</td>
<td>
<a href="https://www.smartkarma.com/entities/netease" target="_blank" data-smartkarma-citation="entities:29030:1" rel="noopener">NetEase (9999 HK)</a> </td>
<td>Communication</td>
<td>China</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/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;">16</td>
</tr>
<tr>
<td style="text-align: center;">4</td>
<td>
<a href="https://www.smartkarma.com/entities/xiaomi-corp" target="_blank" data-smartkarma-citation="entities:24409:1" rel="noopener">Xiaomi Corp (1810 HK)</a> </td>
<td>Information Technology</td>
<td>China</td>
<td style="text-align: center;">91</td>
</tr>
<tr>
<td style="text-align: center;">5</td>
<td>
<a href="https://www.smartkarma.com/entities/alibaba-group" target="_blank" data-smartkarma-citation="entities:28434:1" rel="noopener">Alibaba Group (9988 HK)</a> </td>
<td>Consumer Discretionary</td>
<td>China</td>
<td style="text-align: center;">34</td>
</tr>
<tr>
<td style="text-align: center;">6</td>
<td>
<a href="https://www.smartkarma.com/entities/vale-sa-7721577f-6c6a-4536-a829-92551c2bcd7f" target="_blank" data-smartkarma-citation="entities:27725:1" rel="noopener">Vale SA (VALE3 BZ)</a> </td>
<td>Materials</td>
<td>Brazil</td>
<td style="text-align: center;">38</td>
</tr>
<tr>
<td style="text-align: center;">7</td>
<td>
<a href="https://www.smartkarma.com/entities/ambev-sa" target="_blank" data-smartkarma-citation="entities:24454:1" rel="noopener">Ambev SA (ABEV3 BZ)</a> </td>
<td>Consumer Staples</td>
<td>Brazil</td>
<td style="text-align: center;">35</td>
</tr>
<tr>
<td style="text-align: center;">8</td>
<td>
<a href="https://www.smartkarma.com/entities/ambev-sa" target="_blank" data-smartkarma-citation="entities:24454:1" rel="noopener">Ambev SA (ABEV3 BZ)</a> </td>
<td>Communication</td>
<td>China</td>
<td style="text-align: center;">43</td>
</tr>
<tr>
<td style="text-align: center;">9</td>
<td>
<a href="https://www.smartkarma.com/entities/ping-an-insurance-grp-co-of-china-ltd" target="_blank" data-smartkarma-citation="entities:12880:1" rel="noopener">Ping An Insurance (H) (2318 HK)</a> </td>
<td>Financials</td>
<td>China</td>
<td style="text-align: center;">23</td>
</tr>
<tr>
<td style="text-align: center;">10</td>
<td>
<a href="https://www.smartkarma.com/entities/jd-com-inc" target="_blank" data-smartkarma-citation="entities:29043:1" rel="noopener">JD.com Inc. (9618 HK)</a> </td>
<td>Consumer Discretionary</td>
<td>China</td>
<td style="text-align: center;">79</td>
</tr>
<tr><td colspan="5" style="text-align: left;">Source: FactSet financial data and analytics, my estimates and calculations, Tensorflow, Keras, Google Colaboratory, pandas</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 3 years (and implemented in its current state for 17 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 the beaten-down Chinese tech names such as Xiaomi Corp (1810 HK), Alibaba Group (9988 HK), Tencent (700 HK) , and JD.com Inc. (9618 HK) as well as two Brazilian large caps in Vale SA (VALE3 BZ) and Ambev SA (ABEV3 BZ).









rank
Name
Sector
Location
prev.


1

New Oriental Education &amp; Technology Group (9901 HK) 
Consumer Discretionary
China
10


2

NetEase (9999 HK) 
Communication
China
5


3

Samsung Electronics (005930 KS) 
Information Technology
Korea (South)
16


4

Xiaomi Corp (1810 HK) 
Information Technology
China
91


5

Alibaba Group (9988 HK) 
Consumer Discretionary
China
34


6

Vale SA (VALE3 BZ) 
Materials
Brazil
38


7

Ambev SA (ABEV3 BZ) 
Consumer Staples
Brazil
35


8

Ambev SA (ABEV3 BZ) 
Communication
China
43


9

Ping An Insurance (H) (2318 HK) 
Financials
China
23


10

JD.com Inc. (9618 HK) 
Consumer Discretionary
China
79

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. 

Screening for GEMs: October 2021