01 October 2021
By Lukas Gehrig, Zurich Switzerland, Quantitative Strategist; Nikola Vasiljevic, Zurich, Switzerland, Head of Quantitative Strategy
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Financial markets are far more correlated than they were in the 2000s. This poses challenges for diversification that needs an additional lens to analyse dependencies. General macroeconomic indicators can inform macro-dependent investment decisions.
The best advice for building a robust portfolio has always been to diversify across different asset classes rather than putting all your eggs into one basket.
As we have argued several times in previous Market Perspectives, diversification has become even more important with the increased globalisation of financial markets. It is well known that diversifying investments beyond a simple mix of equities and bonds offers both opportunities and risks that can strengthen the robustness of a portfolio.
A less well-known fact is that the correlation between asset classes has increased considerably since the early 2000s. Looking at three distinct periods this century, before the global financial crisis (GFC), between then and the pandemic onset and then since, shows the different correlations between the returns on one-out-of-eight key asset classes against the others (see chart). We have chosen the broad asset classes that would be represented in a typical US dollar.
The blue bars represent the years 2000 until the onset of the GFC. Asset classes like government or investment grade bonds and commodities exhibited only benign correlation to the returns of the other asset classes. This implies that they are good diversifiers for riskier assets, such as high yield credit or equities.
The green bars for the inter-crises period show a significant increase in correlation across asset classes. And, while still very short in history, the dark blue bars for the post-COVID-19 period suggest that cross- correlations have risen even more since the outbreak of COVID-19 and the policy responses to it.
This change in correlations, brought about by quantitative easing intended for asset price stabilisation and unprecedented government spending programmes, has undoubtedly made diversification more difficult to achieve.
While there are sources of uncorrelated opportunities that can be tapped in private markets, these are tailored solutions, which would be difficult to replicate for many investors. Another popular solution to the above-mentioned diversification problem does not actually introduce new, uncorrelated risks, but seeks to better understand the drivers of the co-movement.
Traditionally, growth and inflation are used as macroeconomic indicators, driving returns in financial markets. Indeed, growth (or surprises therein) can explain a large share of the co-movement of risky assets, while inflation can be cited for outperformance of real assets such as commodities. But there is a third driver: monetary policy (see chart).
In building these macroeconomic indicators, we made a host of assumptions that can influence any subsequent analysis. We selected well-known US indicators, transformed them to year-on-year change basis (where necessary) and normalised the indicators to a mean of zero and comparable variance.
These indicators work well in explaining co-movement in our key asset classes at a medium-term horizon (say six months), where many single event-shocks not captured by the indicators are smoothed out. A much more reactive set of macroeconomic indicators would be needed to explain co-movement on a monthly, weekly or even daily basis.
This chart visualises the partial correlations between the returns of each asset class and the three macroeconomic indicators. The highlighted black circle marks the zero-line. Points outside of this circle mean positive correlation and vice-versa.
It should come as no surprise that inflation is most negatively correlated with fixed income assets, while being positively correlated with commodities. Growth is most positively related with equities, cyclical commodities and real estate while weighing on returns of gold. Easy monetary policy created an environment where riskier fixed income and equities thrive, while returns on developed government bonds falter.
The prior analysis shows that asset classes have become more correlated over time and that groups of asset classes (perhaps risky, cyclical or real assets) are associated with specific macro “weather”. We can use this information to help devise a tactical overlay to any given portfolio, overweighting assets that benefit from the current environment.
The above macroeconomic indicators have become more correlated over time: especially inflation, which has been more correlated to growth and monetary policy in the last decade. Clearly, when everything is correlated, including the underlying macroeconomic drivers, one would be tempted to focus on the high-returning assets.
However, this correlation of macro indicators may reverse. If so, it may be worth making diversification decisions in a portfolio context dependent on both the prevalence and co-movement of macro indicators. But this is something for a later article in this series.
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