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    GSAM Connect

    CHINA: TIME TO FLY SOLO?

    July 18, 2022  |  10 Minute Read

     

     

    Executive Summary

    China’s representation in the MSCI Emerging Markets (EM) Index has been on the rise over the last two decades; from a mere 7% in 2000 to approximately one third today. This is set to rise further over time given the ongoing phased inclusion of A-Shares which currently stands at 20%.1 At 100% A-Share inclusion, China could make up 45% of MSCI EM Index. China is also the second largest equity market globally with a market capitalization near $18 trillion made up of close to 5,900 listed stocks. Historically, for most investors investing in EM equities, overall EM market performance has been closely correlated to China’s domestic market. However, the relationship has uncoupled to some extent over the last two years. China equities fared much better than the rest of the EM complex in 2020 during the worst of the COVID-19 pandemic, but much worse a year later due to regulatory tightening and a strict zero-Covid policy. As a result, many investors are questioning whether it is time to look at China as a standalone allocation. While the question is perhaps motivated by the recent market performance divergence, we believe key structural changes are providing compelling reasons to look at China in isolation.

     

    In this paper, we first look at the lessons learnt from Japan’s separation from the MSCI Asia Index 20 years ago before then examining how China as a standalone allocation looks in a broader equity portfolio. Finally, we highlight the potential benefits of having China separated from EM to allow for macro tactical tilts based on a model capturing factors such as GDP growth, rates and commodities.

     

    Exhibit 1. Emerging Market Equity Performance Over Time

     

    Source: Bloomberg and Goldman Sachs Asset Management. As of April 30, 2022. Past performance does not guarantee future results, which may vary.

     

    Lessons Learned from Japan

    In January 2001, MSCI launched its Asia ex-Japan Index. At that point, Japan accounted for approximately 70% of the All Country Asia Index and many investors were seeking an index that was not dominated by a single market. Foreign portfolio flows following the introduction of the Asia ex-Japan index in 2001 show that both Japan and the region (ex-Japan) continued to receive cumulative net inflows at a fairly consistent (roughly 60%/40%)2 proportion. In addition, the correlation2 of foreign portfolio flows to Japan and Asia ex-Japan markets gradually reduced from a high of over 0.70 in the early 2000s to a 0.10-0.20 range more recently, until the common shock of the Covid outbreak drove correlations back to the 40% level.

     

    We conclude that it appears likely that both China and EM ex-China can be viable indices and attract investment flows.

     

    China Uniqueness

    At Goldman Sachs Asset Management, we have been stressing the importance of implicit sector and style biases coming from top-down views resulting in geographical exposure divergence from the traditional MSCI World Index benchmark. Indeed, some equity markets have unique equity styles and/or sector composition. For instance, investing in the UK relative to the World leads to a noteworthy implicit investment thesis: a strong bearish view on tech (circa 0% in the MSCI UK) while taking a sizeable overweight of 8 percentage points on the energy sector from 4% to 12% relative to the MSCI World. Looking at China and EM ex-China, we noticed significant nuances. The tech hardware and semiconductor sectors are the largest sector with ~29%3 for EM ex-China but only ~5%4 in the MSCI China. On the other hand, internet and consumer retail/tech (which are included within the consumer discretionary and communication services sectors) categories jointly account for ~43% in the MSCI China but only 6% in EM ex-China.3

     

    Exhibit 2. Equity market sector over/underweights relative to MSCI World

     

    Source: Bloomberg, MSCI, and Goldman Sachs Asset Management. Sectors weights are represented according the MSCI Global Industry Classification Standard (GICS®), as of February 28,2022. World refers to the MSCI World Index. UK refers to the MSCI UK Index. Percentage weights may not add to 100% due to rounding.

     

    Furthermore, while most investors typically break down developed market (DM) equity into the following regions US/Europe ex-UK/UK/Japan, it is interesting to note that the correlation across those markets is high (Exhibit 3). For instance, the 10-year correlation of the US and Europe ex-UK stands at 0.83 and Europe ex-UK and UK at 0.90. However, when we look at China, it is a different story. China correlation is the lowest across both DM and EM ex-China, and the correlation of China with EM ex-China is much lower relative to the correlation within DM markets.

     

     Exhibit 3: Equity Market Correlation table

     

    Source: Bloomberg and Goldman Sachs Asset Management. Analysis as of February 28, 2022. Past correlations are not indicative of future correlations, which may vary. For illustrative purposes only. 

     

    We conclude this section with the view that China has the highest diversification potential across major equity markets and a unique sector composition, strengthening the case to consider China as a unique asset class.

     

    Allowing for Better Tactical Macro View Implementations

    In this section, we have leveraged a multi-factor model from Goldman Sachs Global Investment Research.4 Based on this four-factor macro model we can identify the key macro drivers that have influenced EM ex-China returns and how they vary from China. While the MSCI China Index is unsurprisingly most sensitive to China growth, EM ex-China is relatively more negatively sensitive to US rates than China. This is largely because of the ASEAN and select LatAm markets (like Brazil) which have historically been sensitive to higher US interest rates. Similarly, we note that EM ex-China equities are more positively sensitive to commodities than China equities and the broader EM index. While this may seem surprising at first given China’s large share in global demand for metals, EM ex-China has large weights in oil-exporting EMs, such as, Brazil, Mexico, and the Middle East region. Moreover, sector composition corroborates that the MSCI EM ex-China Index has a higher exposure to commodity sectors: MSCI EM ex-China has approximately 20% weight in commodity sectors compared to only 5% for China.

     

    Additionally, the R-squared value for the EM ex-China macro model is approximately 58%, which is far higher than the China models at 32%. This means that, statistically, those factors explained 58% of the equity market return for EM ex-China, which is almost double compared to China alone, suggesting that some other idiosyncratic factors drive China equity performance.

     

    With the current environment of growth slowing down, high inflation, rising US rates, and higher commodity prices, it seems an opportune time to evaluate macro view implementations. Splitting China from rest of EM may be one way to do this given the EM ex-China region’s higher sensitivity to those factors.

     

    Exhibit 4: Equity Market Return Sensitivity to Selected Macro Variables

     

    Source: Goldman Sachs Global Investment Research. The model results are based on a 4-factor model with China CAI, Global LCAI, UST10Y & GSCI (rolling 3-month change since 2006) as the independent variables and the MSCI index USD price returns (3-month) as the dependent variables (local price return for CSI300). Data points of China CAI and Global LCAI are winsorized to reduce the effect of extreme outliers in the COVID-19 period. Values of coefficients which are statistically insignificant at 90% significance level are not shown (i.e. have absolute values of t-stats < ~1.65). Past performance does not guarantee future results, which may vary.

     

    Conclusion

    In our view, the rise of China in the MSCI EM Index has reached a level too big to ignore and is set to become even bigger in the future. While size alone is not enough to justify splitting China from the EM broader index, we believe China’s uniqueness is. Indeed, China has presented the lowest correlation of returns across mainstream equity sleeves and a unique sector composition. In addition, China’s idiosyncratic factors (e.g., geopolitics, regulatory policy) have created significant divergence for China market performance, which in some instances has been challenging for investors willing to express views on China and/or ex-China segments. Finally, lessons learned from the Japanese market are comforting, and show that 1) this has happened in the past and 2) flows initially go into both categories reasonably consistently until reaching a more mature phase. So is it time for China to fly solo? We think so.

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    1 Source: MSCI. As of June 30, 2022.

    2 Source: Goldman Sachs Global Investment Research. Paper: EM ex-China as a separate equity asset class (October 2021).

    3 Source: FactSet, MSCI, Goldman Sachs Global Investment Research. As of October 8, 2921.

    4 Source: Goldman Sachs Global Investment Research. Paper: EM ex-China as a separate equity asset class (October 2021).

     

    Glossary

    Tactical Tilts refers to a style of investing for the relatively short term based on anticipated market trends or relatively short-lived changes in outlook based on fundamental or technical analysis. Tactical tilts may involve taking long or short positions in a range of markets, from equities and fixed income to commodities and currencies.

    Bearish – to have a bearish view in trading means to believe that a market, asset or financial instrument is going to experience a downward trajectory.

    R-Squared value – a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable or variables in a regression model.

    Multi-factored model – A multi-factor model is a financial model that employs multiple factors in its calculations to explain market phenomena and/or equilibrium asset prices.

    T-stat - t-statistic is the ratio of the departure of the estimated value of a parameter from its hypothesized value to its standard error. The t-statistic is used in a t-test to determine whether to support or reject the null hypothesis. It is also used along with p-value when running hypothesis tests where the p-value tells us what the odds are of the results to have happened.

    rsq – same as R-Squared value

    GDP - The value of finished goods and services produced within a country's borders over one year.

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