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

<ul>
<li>An overview (and output) of our machine learning-driven GEM screening model, which seeks to find the best medium-term long ideas within the top100 stocks in the MSCI GEM Index.</li>
<li>The model is based on 1) a quantitative multifactor screening model, enhanced by two AI Technology-based approaches; 2) a Deep Neural Network model, and 3) a Recurrent Neural Network model.</li>
<li>Developed over nearly 4 years and implemented in its current state for nearly 2 years, the model has a solid real-world alpha-generating performance track record, discussed in detail below.</li>
</ul>


An overview (and output) of our machine learning-driven GEM screening model, which seeks to find the best medium-term long ideas within the top100 stocks in the MSCI GEM Index.
The model is based on 1) a quantitative multifactor screening model, enhanced by two AI Technology-based approaches; 2) a Deep Neural Network model, and 3) a Recurrent Neural Network model.
Developed over nearly 4 years and implemented in its current state for nearly 2 years, the model has a solid real-world alpha-generating performance track record, discussed in detail below.


<ul>
<li>An overview (and output) of our machine learning-driven GEM screening model, which seeks to find the best medium-term long ideas within the top100 stocks in the MSCI GEM Index.</li>
<li>The model is based on 1) a quantitative multifactor screening model, enhanced by two AI Technology-based approaches; 2) a Deep Neural Network model, and 3) a Recurrent Neural Network model.</li>
<li>Developed over the past 3 years, and implemented in its current state for 20 months, the model has a solid real-world alpha-generating performance track record, set out in detail below.</li>
</ul>


An overview (and output) of our machine learning-driven GEM screening model, which seeks to find the best medium-term long ideas within the top100 stocks in the MSCI GEM Index.
The model is based on 1) a quantitative multifactor screening model, enhanced by two AI Technology-based approaches; 2) a Deep Neural Network model, and 3) a Recurrent Neural Network model.
Developed over the past 3 years, and implemented in its current state for 20 months, the model has a solid real-world alpha-generating performance track record, set out in detail below.


<ul>
<li>An overview (and output) of our machine learning-driven GEM screening model, which seeks to find the best medium-term long ideas within the top100 stocks in the MSCI GEM Index.</li>
<li>The model is based on 1) a quantitative multifactor screening model, enhanced by two AI Technology-based approaches; 2) a Deep Neural Network model, and 3) a Recurrent Neural Network model.</li>
<li>Developed over the past 3 years, and implemented in its current state for 18 months, the model has a solid real-world alpha-generating performance track record, set out in detail below.</li>
</ul>


An overview (and output) of our machine learning-driven GEM screening model, which seeks to find the best medium-term long ideas within the top100 stocks in the MSCI GEM Index.
The model is based on 1) a quantitative multifactor screening model, enhanced by two AI Technology-based approaches; 2) a Deep Neural Network model, and 3) a Recurrent Neural Network model.
Developed over the past 3 years, and implemented in its current state for 18 months, the model has a solid real-world alpha-generating performance track record, set out in detail below.


<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 Russian internet company <a href="https://www.smartkarma.com/entities/yandex-nv-a" target="_blank" data-smartkarma-citation="entities:414:1" rel="noopener">Yandex (YNDX US)</a>, Indian IT Services company <a href="https://www.smartkarma.com/entities/hcl-technologies-ltd" target="_blank" data-smartkarma-citation="entities:20025:1" rel="noopener">Hcl Technologies (HCLT IN)</a>, and a return to the top 10 for <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>.</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/lg-household-health-care" target="_blank" data-smartkarma-citation="entities:6501:1" rel="noopener">LG Household &amp; Health Care (051900 KS)</a> </td>
<td>Consumer Staples</td>
<td>Korea (South)</td>
<td style="text-align: center;">12</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;">2</td>
</tr>
<tr>
<td style="text-align: center;">3</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;">10</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;">4</td>
</tr>
<tr>
<td style="text-align: center;">5</td>
<td>
<a href="https://www.smartkarma.com/entities/yandex-nv-a" target="_blank" data-smartkarma-citation="entities:414:1" rel="noopener">Yandex (YNDX US)</a> </td>
<td>Communication</td>
<td>Russian Federation</td>
<td style="text-align: center;">49</td>
</tr>
<tr>
<td style="text-align: center;">6</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;">1</td>
</tr>
<tr>
<td style="text-align: center;">7</td>
<td>
<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> </td>
<td>Information Technology</td>
<td>Taiwan</td>
<td style="text-align: center;">16</td>
</tr>
<tr>
<td style="text-align: center;">8</td>
<td>
<a href="https://www.smartkarma.com/entities/al-rajhi-bank" target="_blank" data-smartkarma-citation="entities:27038:1" rel="noopener">Al Rajhi Bank (RJHI AB)</a> </td>
<td>Financials</td>
<td>Saudi Arabia</td>
<td style="text-align: center;">33</td>
</tr>
<tr>
<td style="text-align: center;">9</td>
<td>
<a href="https://www.smartkarma.com/entities/magazine-luiza-sa" target="_blank" data-smartkarma-citation="entities:27676:1" rel="noopener">Magazine Luiza SA (MGLU3 BZ)</a> </td>
<td>Consumer Discretionary</td>
<td>Brazil</td>
<td style="text-align: center;">15</td>
</tr>
<tr>
<td style="text-align: center;">10</td>
<td>
<a href="https://www.smartkarma.com/entities/hcl-technologies-ltd" target="_blank" data-smartkarma-citation="entities:20025:1" rel="noopener">Hcl Technologies (HCLT IN)</a> </td>
<td>Information Technology</td>
<td>India</td>
<td style="text-align: center;">83</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 Russian internet company Yandex (YNDX US), Indian IT Services company Hcl Technologies (HCLT IN), and a return to the top 10 for TSMC (2330 TT).

      


rank
Name
Sector
Location
prev.


1

LG Household &amp; Health Care (051900 KS) 
Consumer Staples
Korea (South)
12


2

NetEase (9999 HK) 
Communication
China
2


3

JD.com Inc. (9618 HK) 
Consumer Discretionary
China
10


4

Xiaomi Corp (1810 HK) 
Information Technology
China
4


5

Yandex (YNDX US) 
Communication
Russian Federation
49


6

New Oriental Education &amp; Technology Group (9901 HK) 
Consumer Discretionary
China
1


7

TSMC (2330 TT) 
Information Technology
Taiwan
16


8

Al Rajhi Bank (RJHI AB) 
Financials
Saudi Arabia
33


9

Magazine Luiza SA (MGLU3 BZ) 
Consumer Discretionary
Brazil
15


10

Hcl Technologies (HCLT IN) 
Information Technology
India
83


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.

<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 bottom-fishing in Chinese education through <a href="https://www.smartkarma.com/entities/new-oriental-education-tech-grp-adr" target="_blank" data-smartkarma-citation="entities:531:1" rel="noopener">New Oriental Education (EDU US)</a>, Russian internet play <a href="https://www.smartkarma.com/entities/yandex-nv-a" target="_blank" data-smartkarma-citation="entities:414:1" rel="noopener">Yandex (YNDX US)</a>, Brazilian beverages giant <a href="https://www.smartkarma.com/entities/ambev-sa" target="_blank" data-smartkarma-citation="entities:24454:1" rel="noopener">Ambev SA (ABEV3 BZ)</a>, and a rebound call on <a href="https://www.smartkarma.com/entities/tencent-holdings-ltd" target="_blank" data-smartkarma-citation="entities:26:1" rel="noopener">Tencent (700 HK)</a>.</p><table class="table table-striped">
<colgroup>
<col>
<col>
<col>
<col>
<col>
</colgroup>
<tbody>
<tr>
<td style="text-align: center; width: 74.9062px;">rank</td>
<td style="width: 262.578px;">Name</td>
<td style="width: 185.766px;">Sector</td>
<td style="width: 147.797px;">Location</td>
<td style="text-align: center; width: 74.9531px;">prev.</td>
</tr>
<tr>
<td style="text-align: center; width: 74.9062px;">1</td>
<td style="width: 262.578px;">
<a href="https://www.smartkarma.com/entities/tata-consultancy-svcs-ltd" target="_blank" data-smartkarma-citation="entities:18708:1" rel="noopener">Tata Consultancy Svcs (TCS IN)</a> </td>
<td style="width: 185.766px;">Information Technology</td>
<td style="width: 147.797px;">India</td>
<td style="text-align: center; width: 74.9531px;">19</td>
</tr>
<tr>
<td style="text-align: center; width: 74.9062px;">2</td>
<td style="width: 262.578px;">
<a href="https://www.smartkarma.com/entities/shenzhou-intl-group-holdings-ltd" target="_blank" data-smartkarma-citation="entities:10415:1" rel="noopener">Shenzhou Intl Group Holdings (2313 HK)</a> </td>
<td style="width: 185.766px;">Consumer Discretionary</td>
<td style="width: 147.797px;">China</td>
<td style="text-align: center; width: 74.9531px;">12</td>
</tr>
<tr>
<td style="text-align: center; width: 74.9062px;">3</td>
<td style="width: 262.578px;">
<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 style="width: 185.766px;">Consumer Discretionary</td>
<td style="width: 147.797px;">China</td>
<td style="text-align: center; width: 74.9531px;">92</td>
</tr>
<tr>
<td style="text-align: center; width: 74.9062px;">4</td>
<td style="width: 262.578px;">
<a href="https://www.smartkarma.com/entities/yandex-nv-a" target="_blank" data-smartkarma-citation="entities:414:1" rel="noopener">Yandex (YNDX US)</a> </td>
<td style="width: 185.766px;">Communication</td>
<td style="width: 147.797px;">Russian Federation</td>
<td style="text-align: center; width: 74.9531px;">88</td>
</tr>
<tr>
<td style="text-align: center; width: 74.9062px;">5</td>
<td style="width: 262.578px;">
<a href="https://www.smartkarma.com/entities/china-resources-land-ltd" target="_blank" data-smartkarma-citation="entities:418:1" rel="noopener">China Resources Land (1109 HK)</a> </td>
<td style="width: 185.766px;">Real Estate</td>
<td style="width: 147.797px;">China</td>
<td style="text-align: center; width: 74.9531px;">33</td>
</tr>
<tr>
<td style="text-align: center; width: 74.9062px;">6</td>
<td style="width: 262.578px;">
<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 style="width: 185.766px;">Consumer Staples</td>
<td style="width: 147.797px;">Brazil</td>
<td style="text-align: center; width: 74.9531px;">56</td>
</tr>
<tr>
<td style="text-align: center; width: 74.9062px;">7</td>
<td style="width: 262.578px;">
<a href="https://www.smartkarma.com/entities/ncsoft-corp" target="_blank" data-smartkarma-citation="entities:5169:1" rel="noopener">NCSOFT Corp (036570 KS)</a> </td>
<td style="width: 185.766px;">Communication</td>
<td style="width: 147.797px;">Korea (South)</td>
<td style="text-align: center; width: 74.9531px;">18</td>
</tr>
<tr>
<td style="text-align: center; width: 74.9062px;">8</td>
<td style="width: 262.578px;">
<a href="https://www.smartkarma.com/entities/tencent-holdings-ltd" target="_blank" data-smartkarma-citation="entities:26:1" rel="noopener">Tencent (700 HK)</a> </td>
<td style="width: 185.766px;">Communication</td>
<td style="width: 147.797px;">China</td>
<td style="text-align: center; width: 74.9531px;">61</td>
</tr>
<tr>
<td style="text-align: center; width: 74.9062px;">9</td>
<td style="width: 262.578px;">
<a href="https://www.smartkarma.com/entities/hindustan-unilever-ltd" target="_blank" data-smartkarma-citation="entities:13828:1" rel="noopener">Hindustan Unilever (HUVR IN)</a> </td>
<td style="width: 185.766px;">Consumer Staples</td>
<td style="width: 147.797px;">India</td>
<td style="text-align: center; width: 74.9531px;">70</td>
</tr>
<tr>
<td style="text-align: center; width: 74.9062px;">10</td>
<td style="width: 262.578px;">
<a href="https://www.smartkarma.com/entities/maruti-suzuki-india-ltd" target="_blank" data-smartkarma-citation="entities:733:1" rel="noopener">Maruti Suzuki India (MSIL IN)</a> </td>
<td style="width: 185.766px;">Consumer Discretionary</td>
<td style="width: 147.797px;">India</td>
<td style="text-align: center; width: 74.9531px;">89</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 bottom-fishing in Chinese education through New Oriental Education (EDU US), Russian internet play Yandex (YNDX US), Brazilian beverages giant Ambev SA (ABEV3 BZ), and a rebound call on Tencent (700 HK).









rank
Name
Sector
Location
prev.


1

Tata Consultancy Svcs (TCS IN) 
Information Technology
India
19


2

Shenzhou Intl Group Holdings (2313 HK) 
Consumer Discretionary
China
12


3

New Oriental Education &amp; Technology Group (9901 HK) 
Consumer Discretionary
China
92


4

Yandex (YNDX US) 
Communication
Russian Federation
88


5

China Resources Land (1109 HK) 
Real Estate
China
33


6

Ambev SA (ABEV3 BZ) 
Consumer Staples
Brazil
56


7

NCSOFT Corp (036570 KS) 
Communication
Korea (South)
18


8

Tencent (700 HK) 
Communication
China
61


9

Hindustan Unilever (HUVR IN) 
Consumer Staples
India
70


10

Maruti Suzuki India (MSIL IN) 
Consumer Discretionary
India
89

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.

Netherlands

Nebius Group is a technology company providing infrastructure and services to AI builders globally. The group's core business, Nebius, is an AI-centric cloud platform built for AI workloads. Nebius Group serves customers worldwide.

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Nebius Group (NBIS US)

Screening for GEMs: February 2022

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

Screening for GEMs: January 2022

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

Screening for GEMs: December 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

Screening for GEMs: November 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

Screening for GEMs: August 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

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