One of the key metrics we look for when building our portfolios is how correlated our positions are. Do we have many stocks in the overall same category such as Nasdaq, which then means that even if we have 25 such stocks, in effect, because of the very high correlation between them (95-99%), we actually own just one stock! And that’s hugely risky. Therefore, central to building a durable investment strategy is to constantly build several streams of uncorrelated or low correlated assets that still directionally beat the market, and yet have a very low chance of falling together. Think, JSW Steel and IndiaMART together.
This is possible because of a wide dispersion in asset class returns even at the same time. Cross-asset investing is a strategy that is basically built on the premise that the correlation between various asset classes such as equities, fixed income, commodities and currencies remain low enough most of the time to allow for investors to benefit from diversification. Some ultra-sophisticated investment strategies, driven by vast computing power, tend to be built around this assumption and thus, end up applying the famous Markowitz model in their cross-asset portfolios.
The model assists in the selection of the most efficient portfolio by analysing various portfolios of the given securities/assets. By choosing securities that do not ‘move’ exactly together (think low correlation), the model shows investors how to reduce their risk. But, does this actually hold true when we look at the data?
1997 was something investors couldn’t have imagined. The crisis started in Thailand on 2 July with the collapse of the baht after the government was forced to float the baht due to lack of foreign currency to support its currency peg to the US dollar. The contagion spread across the region and we saw equity markets in Indonesia, Malaysia, South Korea and the Philippines crash 60-75% in dollar terms!
One would assume that such an extreme event would lead to broader sell-offs. But the amazing thing was that dispersion was large not only across asset classes but also across global markets. Non-Asian emerging markets (EMs) and European markets were on a tear. We saw Turkey, Greece and Mexico surge 85%, 58% and 53%, respectively. Even the US (S&P 500) advanced by 47%. Cross-asset class divergence was also on display as US treasuries (10-year) outperformed commodities by managing to edge 3% higher, while crude and gold dropped 30% and 21%, respectively.
Of course, blind diversification does not help. That only kills returns, while reducing risk. Tactical positioning by understanding the drivers of cross-asset moves, vulnerability to correlation spikes and being cognizant of tail risks are key to achieving true global and cross-asset diversification.
Let’s now jump ahead to the tech bubble of 2000. This was the year of the correlation spike! Anything and everything sold off except US treasuries, which benefited from the flight to safety like a classic textbook move. We saw EMs crack 30-40%, Nasdaq plunged 36% and even gold couldn’t have saved you.
From 2010 began the unravelling of the long EMs/short US equities trade. The next 10 years belonged solidly to the US markets, with most EMs delivering zero returns over a decade. So, again, we see massive dispersion of returns, even within the equity class itself. FAANG (Facebook, Amazon, Apple, Netflix and Google) and Nasdaq became the go-to trade for investors.
And then came 2020. A look at the top performers in 2020 is instructive. Vietnam was No. 1, with 80% returns. South Korea was No. 2 with nearly 50%. And from the last quarter of 2020, the data becomes even more dramatic: The crowded Nasdaq long trade delivered only 16%, while the broader US markets returned 16% too, therefore, it was clear that Nasdaq was beginning to lose steam rapidly. However, EMs gave almost 2x the return.
What the analysis shows is that investing is never a static game. It’s a game of several possible coexisting outcomes, of which only one/few will come true and usually, that will be the one that’s least expected. The FAANG bull market from 2016 to 2019 convinced everybody that Nasdaq and FAANGs were the only money-making games in town. 2020 showed a completely different picture as most of the FAANGs went into hibernation.
The long-term analysis shows only one recurrent theme: leadership keeps changing almost every single year. Global investing is a complicated game, and an oversimplified, under-analysed approach can lead to very poor return payoffs.
Shankar Sharma is vice chairman and joint MD, First Global. Devina Mehra and Harsh Shivlani contributed to this column.
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