China, Saudi Arabia and Vietnam are among the highest-ranked out of around 50 emerging equity markets in our new Tellimer EM Country Index.
Brazil, South Africa and Russia among large EM equities and Egypt, Nigeria, Pakistan and Turkey among small EM equities are among the lowly ranked.
Our index weights c30 factors on growth (short and long term), policy credibility, politics, sanctions, ESG, equity valuation and liquidity.
The weights in the index can be changed in order to model different global themes and portfolio styles.
In the latest version, scores for large EM range from positive 145 for top-ranked China to negative 62 for bottom-ranked Russia.
Around 85% of the index's weight covers factors relevant for all asset classes, with the remaining 15% specific to equities. For foreign direct investors wishing to assess a wide range of country risk factors, this model can be adjusted by simply applying zero weight to the equity market factors.
Because trading liquidity is a part of the equity component, and China is much more deeply traded than all other EM, this has a major bearing on China's score, as I explain below.
Some of the factors change very infrequently (eg environmental risk), some intermittently (eg growth forecasts) and some daily (eg valuation).
For example, in recent months:
China's score is broadly unchanged (145) and it keeps its top spot in the EM universe – reduced growth forecasts and incrementally higher sanctions risk pulled the score down by c10 points but much lower valuation (as trailing PB of the equity market has moved from a 5% premium to the five-year median to a 10% discount) has offset this.
Russia's score has collapsed (from positive 7 to negative 62) due to the wide-ranging sanctions and the negative growth that have resulted from its invasion of Ukraine, pushing it to near the bottom of the entire EM universe (Zimbabwe and Iran are the only countries to score less).
Commodity exporter scores, eg crude oil-dependent Saudi Arabia (from 21 to 23), have seen a significant boost from better macroeconomic variables (eg growth, fiscal and current account balances, currency risk), but some of this is offset by higher equity market valuation.
These examples obviously confirm a lot of what we already know and what markets are already pricing in.
However, the analytical power in this index, I hope, is the ability to model, by adjusting the weights applied to the different factors, how country selection changes with major directional changes in global themes or portfolio style, such as:
How precious is growth, which alters tolerance for valuation;
How accommodating is risk appetite, which alters tolerance for currency risk, low policy credibility or thin equity market liquidity;
How short or long term is the investing time horizon, which alters how much attention is paid to structural growth potential;
How stringent a screening factor is ESG (which takes certain countries off the radar entirely);
How far will the US go to weaponise trade and sanctions; or
How long can the commodity cycle last?
In this launch report of the Tellimer EM Country Index, I have adopted a fairly neutral set of weights across the different factors. For those interested in sampling and subscribing to the underlying workings of the index, there is an option to alter these weights to reflect much more bias in terms of global thematic views or portfolio style.
As always, I welcome your feedback.
A quantitative framework for heterogenous EM
Emerging market equities are often treated as a homogenous asset class. This is both because they are often viewed as a singular alternative to US equities – witness the common refrain of TINA (there is no alternative) advocates of "why bother with EM risk when the S&P keeps powering on?" – and because of the rise of passive EM ETF (exchange-traded fund) juggernaut – witness the common refrain of "why bother with active managers when so many of them underperform the benchmark".
I have argued many times before that EM is anything but homogenous and growth prospects and risk factors vary considerably across the myriad countries gathered under the umbrella of EM.
But, then, I would make that argument: as an equity strategist, my livelihood depends on an enduring audience for investment cases, data analysis, anecdotes and themes that appeal to the active EM fund manager.
Nevertheless, events over the past year demonstrate the need for active management in the largest markets that dominate the MSCI EM index, ie China-HK, which still occupies almost a 30% weight on its own, or the top four markets, when you include Taiwan, India, and South Korea, which collectively account for 71%, or the top 10, when you include Brazil, Mexico, Saudi Arabia, South Africa, Thailand and Indonesia, which collectively account for 91%. These events include:
China's regulatory crackdown, zero-Covid strategy and rare capacity for policy stimulus;
India's investment case shift from reform to a reliance on policy stimulus;
Rising US yields, which have throttled the appetite for long-duration (or, in some cases, outright speculative) Technology company cash flows;
Commodities' roaring prices (from food to fuel), which have powered the equity market performance of Brazil, Saudi Arabia and South Africa, despite the serious long-term risks faced by each;
Taiwan's concentrated geopolitical conflict risk; and, of course,
Russia's wide-ranging sanctions and subsequent MSCI and FTSE index exclusion.
And all this before one considers the tail of another 15 countries in the EM index (eg Turkey's self-defeating monetary policy, Chile and Peru's lurch to the political left, the UAE's expat liberalisation), let alone the 15 or so countries in in the MSCI FM (Frontier) index (eg Vietnam's continued growth, Pakistan's latest governance setback).
Amid all of this heterogeneity, a challenge for institutional equity fund managers in EM is how to cope with so many countries, languages, markets and such variation in depth of trading liquidity within a unified, quantitative framework.
Tellimer EM Country Index method
The Tellimer EM Country Index scores over 50 emerging market countries, using a weighted score across c30 cross-country data sets. The data is a subset of the nearly 200 data sets housed in our EM Investability Matrix. The elements used here span the following categories:
Macroeconomic outlook – near-term growth, policy credibility, currency risk, structural growth;
Political risk – legislative mandate, inequality, youth unemployment;
Geopolitical risk – sanctions;
ESG – governance, climate change exposure, pollution; and
Equities – valuation, liquidity.
All of the data is standardised to deal with different scales and, where individual country data is missing, it is imputed by using the nearest country comparables.
The data sets vary between those that change infrequently, eg governance scores are updated annually, and those that change frequently, eg equity market valuation changes daily.
The US is included as a reference because, for many asset allocators, EM equities, in general, are considered an alternative to investment in US equities.
A large part of the high scores for China and the US is due to their order of magnitude deeper equity market liquidity (daily value traded) than the rest. If China and the US were only as liquid as Taiwan, for example, then their scores would drop from 145 and 143 to 76 and 45, respectively.
Clearly, there is subjectivity in the choice of variables and the weights applied to them.
A file with the standardised data for the composite factors in the Tellimer EM Country Index, as of 21 April 2022, where the weights can be customised is accessible via the link below. In this file, for example, the distortion driven by outsized liquidity in the China and US equity can be tempered by changing the weight attributed to that factor.
Note that the underlying, non-standardised and decomposed data, with referenced sources for each factor is not displayed.
For access to the full Tellimer EM Country Index ranking model and dataset please contact your sales representative at Tellimer.
