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

Cross Asset Strategy

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In this analysis, we provide a detailed overview of investor positioning among 96 active Asia Ex-Japan funds with combined AUM of $80bn.  Highlights:
</div>
<div>
<ul style="list-style-type: disc;">
<li>The big four of China &amp; HK, Taiwan, South Korea and India dominate holdings in Asia Ex-Japan.  The 4 countries combined account for 85.4% of total allocations, though all but India are held underweight versus the MSCI Asia Ex-Japan index.</li>
<li>China &amp; HK's weight in Asia Ex-Japan funds stands at a 4-year low of 42.96% having fallen heavily from the high of 52% back in August 2020.</li>
<li>Allocations in Indian stocks hit a new all-time high last month of 13.54%.  India has been the go-to overweight holding since the election of Narendra Modi in 2014, though managers are much more closely aligned to benchmark today.</li>
<li>
Indonesian allocations are close to their lowest levels on record.  Only 82.8% of the Asia Ex-Japan managers in our analysis have exposure to Indonesia,  with Comgest, Barings and Vontobel closing exposure over the last 6-months.
</li>
<li>Information Technology dominates the holdings picture, being both the largest sector holding and the largest sector overweight by some distance.  Opposing this are net underweights in Health Care (-1.61%), Materials (-1.25%) and Financials (-1.17%). </li>
<li>The key antagonist in China's tech crackdown, Consumer Discretionary weights have fallen from a high of 21.35% in October 2020 to 16.84% today.  In tandem, active managers have moved from an overweight of 2.18% to an underweight of -0.12%.  Confidence has certainly taken a knock.</li>
</ul>
Also analyzed in more detail:  Thailand, Health Care, Indian Financials, South Korean Consumer Staples, China Financials, <a href="https://www.smartkarma.com/entities/baidu-inc" target="_blank" data-smartkarma-citation="entities:179:1" rel="noopener">Baidu (BIDU US)</a> , <a href="https://www.smartkarma.com/entities/sea-ltd" target="_blank" data-smartkarma-citation="entities:8509:1" rel="noopener">Sea Ltd (SE US)</a> , <a href="https://www.smartkarma.com/entities/midea-group-co-ltd-a" target="_blank" data-smartkarma-citation="entities:16185:1" rel="noopener">Midea Group Co Ltd A (000333 CH)</a> and <a href="https://www.smartkarma.com/entities/jd-com-inc-adr" target="_blank" data-smartkarma-citation="entities:446:1" rel="noopener">JD.com Inc (ADR) (JD US).</a>
Analysis taken from our Asia Ex-Japan research, covering 96 active Asia Ex-Japan funds with combined AUM of $80bn. 
</div>


In this analysis, we provide a detailed overview of investor positioning among 96 active Asia Ex-Japan funds with combined AUM of $80bn.  Highlights:



The big four of China &amp; HK, Taiwan, South Korea and India dominate holdings in Asia Ex-Japan.  The 4 countries combined account for 85.4% of total allocations, though all but India are held underweight versus the MSCI Asia Ex-Japan index.
China &amp; HK's weight in Asia Ex-Japan funds stands at a 4-year low of 42.96% having fallen heavily from the high of 52% back in August 2020.
Allocations in Indian stocks hit a new all-time high last month of 13.54%.  India has been the go-to overweight holding since the election of Narendra Modi in 2014, though managers are much more closely aligned to benchmark today.

Indonesian allocations are close to their lowest levels on record.  Only 82.8% of the Asia Ex-Japan managers in our analysis have exposure to Indonesia,  with Comgest, Barings and Vontobel closing exposure over the last 6-months.

Information Technology dominates the holdings picture, being both the largest sector holding and the largest sector overweight by some distance.  Opposing this are net underweights in Health Care (-1.61%), Materials (-1.25%) and Financials (-1.17%). 
The key antagonist in China's tech crackdown, Consumer Discretionary weights have fallen from a high of 21.35% in October 2020 to 16.84% today.  In tandem, active managers have moved from an overweight of 2.18% to an underweight of -0.12%.  Confidence has certainly taken a knock.

Also analyzed in more detail:  Thailand, Health Care, Indian Financials, South Korean Consumer Staples, China Financials, Baidu (BIDU US) , Sea Ltd (SE US) , Midea Group Co Ltd A (000333 CH) and JD.com Inc (ADR) (JD US).
Analysis taken from our Asia Ex-Japan research, covering 96 active Asia Ex-Japan funds with combined AUM of $80bn. 


Asia Ex-Japan Positioning:  India & Tech at Record Highs

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

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 a host of energy plays (<a href="https://www.smartkarma.com/entities/gazprom-pjsc" target="_blank" data-smartkarma-citation="entities:23749:1" rel="noopener">Gazprom PJSC (GAZP RX)</a>, <a href="https://www.smartkarma.com/entities/lukoil-pjsc-2bfe0130-461e-4ff3-af12-93bec12e6325" target="_blank" data-smartkarma-citation="entities:27148:1" rel="noopener">LUKOIL (LKOH RM)</a>, <a href="https://www.smartkarma.com/entities/ptt-pcl" target="_blank" data-smartkarma-citation="entities:197:1" rel="noopener">PTT PCL (PTT TB)</a>,  and <a href="https://www.smartkarma.com/entities/cnooc-ltd" target="_blank" data-smartkarma-citation="entities:175:1" rel="noopener">CNOOC Ltd (883 HK)</a>) as well as a return for South African banking group <a href="https://www.smartkarma.com/entities/firstrand-ltd" target="_blank" data-smartkarma-citation="entities:24971:1" rel="noopener">FirstRand Ltd (FSR SJ)</a>, and a recovery call for Chinese online gaming powerhouse <a href="https://www.smartkarma.com/entities/netease" target="_blank" data-smartkarma-citation="entities:29030:1" rel="noopener">NetEase (9999 HK)</a>.<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/gazprom-pjsc-6a7231a9-d5e4-4da4-bf21-aa1b9d50fbf8" target="_blank" data-smartkarma-citation="entities:27578:1" rel="noopener">Gazprom PJSC (GAZP RM)</a> </td>
<td>Energy</td>
<td>Russian Federation</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/lukoil-pjsc-2bfe0130-461e-4ff3-af12-93bec12e6325" target="_blank" data-smartkarma-citation="entities:27148:1" rel="noopener">LUKOIL (LKOH RM)</a> </td>
<td>Energy</td>
<td>Russian Federation</td>
<td style="text-align: center;">28</td>
</tr>
<tr>
<td style="text-align: center;">3</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;">30</td>
</tr>
<tr>
<td style="text-align: center;">4</td>
<td>
<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>Real Estate</td>
<td>China</td>
<td style="text-align: center;">5</td>
</tr>
<tr>
<td style="text-align: center;">5</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;">47</td>
</tr>
<tr>
<td style="text-align: center;">6</td>
<td>
<a href="https://www.smartkarma.com/entities/firstrand-ltd" target="_blank" data-smartkarma-citation="entities:24971:1" rel="noopener">FirstRand Ltd (FSR SJ)</a> </td>
<td>Financials</td>
<td>South Africa</td>
<td style="text-align: center;">68</td>
</tr>
<tr>
<td style="text-align: center;">7</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;">25</td>
</tr>
<tr>
<td style="text-align: center;">8</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;">51</td>
</tr>
<tr>
<td style="text-align: center;">9</td>
<td>
<a href="https://www.smartkarma.com/entities/mmc-norilsk-nickel-pjsc-dcb09449-eb24-4747-b1c9-77fbf35e8398" target="_blank" data-smartkarma-citation="entities:33242:1" rel="noopener">MMC Norilsk Nickel PJSC (GMKN RX)</a> </td>
<td>Materials</td>
<td>Russian Federation</td>
<td style="text-align: center;">22</td>
</tr>
<tr>
<td style="text-align: center;">10</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;">3</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>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 a host of energy plays (Gazprom PJSC (GAZP RX), LUKOIL (LKOH RM), PTT PCL (PTT TB),  and CNOOC Ltd (883 HK)) as well as a return for South African banking group FirstRand Ltd (FSR SJ), and a recovery call for Chinese online gaming powerhouse NetEase (9999 HK).









rank
Name
Sector
Location
prev.


1

Gazprom PJSC (GAZP RM) 
Energy
Russian Federation
12


2

LUKOIL (LKOH RM) 
Energy
Russian Federation
28


3

PTT PCL (PTT TB) 
Energy
Thailand
30


4

China Resources Land (1109 HK) 
Real Estate
China
5


5

NetEase (9999 HK) 
Communication
China
47


6

FirstRand Ltd (FSR SJ) 
Financials
South Africa
68


7

CNOOC Ltd (883 HK) 
Energy
China
25


8

Bank Of China Ltd (H) (3988 HK) 
Financials
China
51


9

MMC Norilsk Nickel PJSC (GMKN RX) 
Materials
Russian Federation
22


10

New Oriental Education &amp; Technology Group (9901 HK) 
Consumer Discretionary
China
3

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. 

Silver Point

Thomas J. Monaco

Independent Insight Provider

Silver Point is a boutique research firm that focuses on the broader financial services sector, with a particular focus on troubled institutions globally. 

Asia Ex Japan

Equity Bottom-Up

*Weaker Quarter: Industrial and Commercial Bank of China (1398.HK) [ICBC] reported 2Q21 bottom-line results of CNY 77.7 bn, decreasing CNY 8.0 bn or 9.3% linked quarter. The linked quarter weakness, in our view, can be attributed to negative operating jaws as costs increased CNY 9.4 bn (14.8%) and revenues declined CNY 589 mn (0.3%); and*Credit Risk Continues to Rise: The level of net new NPLs increased 46.4% on annualized basis and remains elevated. When one considers the break-down in credit quality, reserves would appear to be light – in the neighborhood of CNY 86.1 bn, amounting to about one quarter of pre-tax results at ICBC.

*Weaker Quarter: Industrial and Commercial Bank of China (1398.HK) [ICBC] reported 2Q21 bottom-line results of CNY 77.7 bn, decreasing CNY 8.0 bn or 9.3% linked quarter. The linked quarter weakness, in our view, can be attributed to negative operating jaws as costs increased CNY 9.4 bn (14.8%) and revenues declined CNY 589 mn (0.3%); and*Credit Risk Continues to Rise: The level of net new NPLs increased 46.4% on annualized basis and remains elevated. When one considers the break-down in credit quality, reserves would appear to be light – in the neighborhood of CNY 86.1 bn, amounting to about one quarter of pre-tax results at ICBC.   

Industrial and Commercial Bank of China – Negative Jaws Pressure Results

Postal Savings Bank of China C / Equity Bottom-Up

*Excess Provisioning Eats Away At 2Q21 Results: Established in 2007, Postal Savings Bank of China (1658.HK) [PSB] is mainland China’s youngest large commercial bank. PSB reported 2Q21 bottom-line results of CNY 19.9 bn – declining CNY 1.4 bn (6.6%) linked quarter. Excluding gains, PSB’s core operating results declined CNY 6.0 bn (36.0%) over the period. Results were impacted by significantly higher loss provisions and negative operating jaws; and
*Credit Quality Turns, But Reserves More Than Adequate: Net new NPLs increased CNY 14.9 bn and equate to an elevated 116.6% annualized – quite the difference from the CNY 9.3 bn or 18.4% annualized posted at year-end. Despite the accelerated increase in net new NPLs, it would appear that PSB’s reserves exceed known and potential credit risk to the tune of CNY 89.5 bn or over a year of pre-tax profits – begging the question of why the increase in loss provisions?

*Excess Provisioning Eats Away At 2Q21 Results: Established in 2007, Postal Savings Bank of China (1658.HK) [PSB] is mainland China’s youngest large commercial bank. PSB reported 2Q21 bottom-line results of CNY 19.9 bn – declining CNY 1.4 bn (6.6%) linked quarter. Excluding gains, PSB’s core operating results declined CNY 6.0 bn (36.0%) over the period. Results were impacted by significantly higher loss provisions and negative operating jaws; and
*Credit Quality Turns, But Reserves More Than Adequate: Net new NPLs increased CNY 14.9 bn and equate to an elevated 116.6% annualized – quite the difference from the CNY 9.3 bn or 18.4% annualized posted at year-end. Despite the accelerated increase in net new NPLs, it would appear that PSB’s reserves exceed known and potential credit risk to the tune of CNY 89.5 bn or over a year of pre-tax profits – begging the question of why the increase in loss provisions?

Postal Savings Bank of China – Way Too Conservative

*Bank Results Decline Linked Quarter: Ping An Bank (000001.CH) [PAB], the Ping An Insurance (2318.HK) [Ping An] banking subsidiary, continues to feel the challenges of a slowing mainland Chinese economy. For 2Q21, PAB reported results of CNY 7.5 bn – decreasing CNY 2.7 bn (26.4%) linked quarter. From our vantage point, higher loss provisions and weaker net interest income weighed heavily on results; and*Negative Credit Delta Could Accelerate Capital Raise: By our analysis, we find that credit remains incredibly challenged as net new NPLs have accelerated 102.2% annualized - up from 53.6% in 1Q21. Assuming the accelerated credit break in the PAB portfolio continues to remain at its current level, we find that PAB’s reserves still remain quite light by CNY 16 bn. This shortfall represents about two quarter of pre-tax earnings.

*Bank Results Decline Linked Quarter: Ping An Bank (000001.CH) [PAB], the Ping An Insurance (2318.HK) [Ping An] banking subsidiary, continues to feel the challenges of a slowing mainland Chinese economy. For 2Q21, PAB reported results of CNY 7.5 bn – decreasing CNY 2.7 bn (26.4%) linked quarter. From our vantage point, higher loss provisions and weaker net interest income weighed heavily on results; and*Negative Credit Delta Could Accelerate Capital Raise: By our analysis, we find that credit remains incredibly challenged as net new NPLs have accelerated 102.2% annualized - up from 53.6% in 1Q21. Assuming the accelerated credit break in the PAB portfolio continues to remain at its current level, we find that PAB’s reserves still remain quite light by CNY 16 bn. This shortfall represents about two quarter of pre-tax earnings.   

Ping An Insurance – Credit Mixed, But Still Worrisome

China

Bank of China Ltd provides a complete range of banking and other financial services to individual and corporation customers worldwide.  The bank's services include retail banking, Great Wall credit card and debit card services, consumer credit, foreign currency transaction, corporate banking, settlement and clearing,investment banking, and fund management businesses.

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Bank Of China Ltd (H) (3988 HK)

Asia Ex-Japan Positioning: India & Tech at Record Highs

In this analysis, we provide a detailed overview of investor positioning among 96 active Asia Ex-Japan funds with combined AUM of $80bn.

Steven Holden

Screening for GEMs: September 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

Industrial and Commercial Bank of China – Negative Jaws Pressure Results

ICBC: ICBC reported a QOQ 2Q21 bottom-line decline of 9.3% due to negative operating jaws. The level of net new NPLs increased 46.4% annualized...

Thomas J. Monaco

Postal Savings Bank of China – Way Too Conservative

POSTAL SAVINGS BANK: PSB's 2Q21QOQ core result increased 36.0% due to higher loss provisions and negative jaws. Despite the increase in net new...

Thomas J. Monaco

Ping An Insurance – Credit Mixed, But Still Worrisome

PING AN INSURANCE: Ping An Bank reported a 26.4% QOQ results decline for 2Q21 reflecting higher provisions. Credit is challenged as net new NPLs...

Thomas J. Monaco

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