Technical Analyst, Vermilion Research

Joe Jasper

Technical Analyst

Technical and Quantitative Research

Vermilion Research

Vermilion’s objective is to deliver timely, actionable, and unique technical research to professional investors through the application of our various technical indicators.

Our research strategists seek to highlight securities which we believe are at major inflection points, based on our various technical and quantitative indicators, and offer asymmetric risk/return profiles. Our unique research methodology, centered on relative strength, enables our strategists to deliver superior investment recommendations.

Our process begins by organizing the universe of actively traded stocks into discrete sectors, then into industry groups. We then apply our technical and quantitative tools to identify developing price trends. Once attractive trends are identified within a selected sector or group, we screen for individual stocks which we believe offer the best risk/reward profile. We provide a historical perspective that often reveals, through our long-term charts, how price patterns often repeat themselves over time.

Technical Analysis

iShares MSCI ACWI ex US ETF / Technical Analysis

<ul>
<li>Many major indexes have broken below critical supports, including MSCI ACWI (ACWI-US), EURO STOXX 50, STOXX Europe 600, and the DAX.</li>
<li>Odds suggest a bearish downside continuation, and a bearish outlook is appropriate as long as the YTD downtrend remains intact on the ACWI-US, MSCI ACWI ex-US (ACWX-US), and EAFE (EFA-US).</li>
<li>There is bounce potential given these broad global indexes are testing their respective downtrend channel supports, but the fact remains that they <em>are</em> in downtrends, a major problem longer-term.</li>
</ul>


Many major indexes have broken below critical supports, including MSCI ACWI (ACWI-US), EURO STOXX 50, STOXX Europe 600, and the DAX.
Odds suggest a bearish downside continuation, and a bearish outlook is appropriate as long as the YTD downtrend remains intact on the ACWI-US, MSCI ACWI ex-US (ACWX-US), and EAFE (EFA-US).
There is bounce potential given these broad global indexes are testing their respective downtrend channel supports, but the fact remains that they are in downtrends, a major problem longer-term.


MSCI ACWI Ex-US, EAFE Testing Downtrend Channel Supports -- Bounce Potential

IPOs and Catalysts/Events, Global Equity Research Ltd

Arun George

IPOs and Catalysts/Events

Uncompromised, Independent, Conflict-Free Research

Global Equity Research Ltd

Global Equity Research was started in 2017 by a group of experienced research professionals. It was founded on a passionate belief in the importance and the need for uncompromised, independent, conflict-free research. We aim to provide differentiated and actionable primary and bottom up fundamental research.

Equity Capital Markets

<ul>
<li>
<a href="https://www.smartkarma.com/entities/thai-beverage-pcl" target="_blank" data-smartkarma-citation="entities:3656:1" rel="noopener">Thai Beverage (THBEV SP)</a>’s BeerCo is once again pre-marketing an SGX IPO to raise US$0.8-1.0 billion (vs US$2 billion previously), according to press reports. </li>
<li>In 1HFY2022, the group revenue returned to growth due to Vietnam. The easing of restrictions in Thailand should boost volumes in 2HFY2022.  </li>
<li>Creditably despite rising raw material costs, the margins remained steady helped by forward buying contracts. However, the unwinding of the forward contracts will likely lead to margin pressures in FY2023.</li>
</ul>



Thai Beverage (THBEV SP)’s BeerCo is once again pre-marketing an SGX IPO to raise US$0.8-1.0 billion (vs US$2 billion previously), according to press reports. 
In 1HFY2022, the group revenue returned to growth due to Vietnam. The easing of restrictions in Thailand should boost volumes in 2HFY2022.  
Creditably despite rising raw material costs, the margins remained steady helped by forward buying contracts. However, the unwinding of the forward contracts will likely lead to margin pressures in FY2023.


ThaiBev’s BeerCo IPO: Third Time’s the Charm?

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 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.


<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">
<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/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. 

<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.

Brazil

Ambev SA primary business is the production and distribution of beer. The Company also operates in the soft drinks and non-alcoholic and non-carbonated businesses with proprietary brands. Ambev has exclusive bottler and distributor rights for Pepsi CSD products in Brazil.

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

Ambev (ABEV US)

MSCI ACWI Ex-US, EAFE Testing Downtrend Channel Supports -- Bounce Potential

Bounce potential given $ACWX $EFA testing downtrend channel supports, but it would likely be a short-term trading opportunity due to the fact that...

Vermilion Research

ThaiBev’s BeerCo IPO: Third Time’s the Charm?

BeerCo is once again pre-marketing an SGX IPO to raise US$0.8-1.0 billion. In this note, we look at the latest set of results and highlight the key...

Arun George

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: October 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

Price Gauge

52-week Range

Market Cap (USDm)

P/E

Dividend (Yield)