Global Asset Allocation, Politics & Governance, Ecstrat

John-Paul Smith

Global Asset Allocation, Politics & Governance

Ecstrat

Ecstrat is a consultancy advising on asset allocation between global equity markets, with a focus on the intersection of governments, geopolitics, governance and markets.
 
Over the past few years and more especially since the Great Financial Crisis (GFC), investors have become more focused on short-term market movements and real-time returns and have consequently neglected the analysis of the underlying structural themes that underpin longer term performance.
​
More specifically we believe that the evolution of governance-based relationships between investors, controlling shareholders, labour and the state is one of the primary determinants of both relative and absolute performance between individual equity markets.
 
We will endeavour to provide investors with some of the context surrounding governance-related issues which encompass many different disciplines including history, economics and political science, as well as the financial metrics which are the most obvious manifestation of the structural characteristics of each market.
 
We will pay particular attention to the shifts and potential inflection points for governance in individual markets as these are often the best lead indicators for both economic and market performance.

Cross Asset Strategy

In January’s ‘Government and Markets’ report, we used the themes in the 2016 GEM overview and China outlooks to introduce our intra-GEM country weightings.We provide more detail on each of these countries in the full version of this report, focusing on the economic, financial and structural governance issues that we believe will be the most important market drivers over the course of this year and beyond.

In January’s ‘Government and Markets’ report, we used the themes in the 2016 GEM overview and China outlooks to introduce our intra-GEM country weightings.We provide more detail on each of these countries in the full version of this report, focusing on the economic, financial and structural governance issues that we believe will be the most important market drivers over the course of this year and beyond.

Governance, Valuations and the Crisis of State Capitalism

Our bearish outlook for 2016 predicated on the rising risk of a “sudden stop” for China and uncontrolled FX depreciation across EM is unfortunately starting to play out; although markets currently feel very oversold and could rally sharply over the short term, we believe that there is further downside for EM equities in absolute and relative terms over the remainder of the year.

Our bearish outlook for 2016 predicated on the rising risk of a “sudden stop” for China and uncontrolled FX depreciation across EM is unfortunately starting to play out; although markets currently feel very oversold and could rally sharply over the short term, we believe that there is further downside for EM equities in absolute and relative terms over the remainder of the year.

Pan-Asia Catalysts/Events, Quiddity Advisors

Travis Lundy

Pan-Asia Catalysts/Events

Quiddity Advisors

Event-Driven

<ul>
<li>Major global indices have decided to relegate Russia to the "standalone" and "unclassified" market status due to sanctions and restrictions on transfer/payment/clearing.</li>
<li>Talk of significant flows into major non-Russia EM markets such as China, Taiwan, Korea, etc is misguided. </li>
<li>Russia was a non-negligible weight in global EM a few months ago, but GDRs have fallen dramatically and Russia-listed are effectively now portfolio pocket lint.</li>
</ul>


Major global indices have decided to relegate Russia to the "standalone" and "unclassified" market status due to sanctions and restrictions on transfer/payment/clearing.
Talk of significant flows into major non-Russia EM markets such as China, Taiwan, Korea, etc is misguided. 
Russia was a non-negligible weight in global EM a few months ago, but GDRs have fallen dramatically and Russia-listed are effectively now portfolio pocket lint.


Russia Gets the Boot from Major Indices - Minimal Impact But World's Largest Small Sidepocket?

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.


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 <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>.<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;">Source: FactSet financial data and analytics, my estimates and calculations, Tensorflow, Keras, Google Colaboratory, pandas</td></tr>
</tbody>
</table>As usual, please feel free to reach out for the full output table, any questions, clarifications needed or suggestions.

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.

Russia

MMC Norilsk Nickel PJSC produces nickel, palladium, platinum and copper. The Company also produces various by-products such as cobalt, rhodium, silver, gold, iridium, ruthenium, selenium, tellurium and sulfur.

Price Gauge
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Mmc Norilsk Nickel Pjsc (Adr) (MNOD LI)

Governance, Valuations and the Crisis of State Capitalism

In January’s ‘Government and Markets’ report, we used the themes in the 2016 GEM overview and China outlooks to introduce our intra-GEM country...

John-Paul Smith

China and the EM Ugly Contest

Our bearish outlook for 2016 predicated on the rising risk of a “sudden stop” for China and uncontrolled FX depreciation across EM is unfortunately...

John-Paul Smith

Russia Gets the Boot from Major Indices - Minimal Impact But World's Largest Small Sidepocket?

Russia is getting deleted from major indices after brief consultation given sanctions from outside Russia and prohibitions on transfer inside...

Travis Lundy

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: 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

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