investment viewpoints

    The macro drivers wagging the correlation tail

    The macro drivers wagging the correlation tail
    François Chareyron - Portfolio Manager

    François Chareyron

    Portfolio Manager
    Florian Ielpo - Head of Macro, Multi Asset

    Florian Ielpo

    Head of Macro, Multi Asset

    In the latest instalment of Simply put, where we make macro calls with a multi-asset perspective, we use intra-day data analysis to explore the macro forces behind this year’s sharp breakdown of normal equity-bond correlation. 

     

    Need to know:

    •    The equity-bond correlation has surged in 2022. It can be measured using daily data, but the key moments of its rise can only properly be captured through intra-day measures
    •    The surge has actually happened through four key jumps which correspond with the release of US inflation and monetary policy moves
    •    This highlights that while inflation is driving markets, the diversification power of bonds will be limited. We believe it will take an economic slowdown to change this situation

     

    One of the main market puzzles this year is the joint behaviour of bonds and equities. The supposed “correlation breakdown” that most quantitative strategies on the planet have eyes on is impacting both passive and active multi-asset investment solutions alike. While “econo-physics” experts would suggest there is a quant disruption in the structure of markets, simple economists only see the duration effect originating from the necessity to tighten monetary policy to fight inflation. Can both of these lenses be tied together in a consistent story? We think they can through the route of intra-day data.

    Since early 2000, intra-day data sets have received increased attention from the quant industry and academia. They have been widely leveraged to gain a better understanding of two key elements:

    • How prices dynamically integrate information news flow, particularly how announcements affect prices. These can range from corporate announcements to macro updates. Intra-day data have made it possible to better understand how this process works and that has been ground-breaking.
    • Intra-day data has also been heavily used to calculate risk metrics such as volatility at a higher frequency. It carries an immense advantage: these measures are model-risk free and therefore reinforce the trust investors have in them. Realised volatility is probably the best-known example, but there are many more, such as realised correlation or more complex versions of them that also incorporate intra-day seasonality.

    From our perspective, intra-day correlation measures are very interesting: they are less dependent on correlation models when exploiting the information-heavy content of intra-day price action. This is not just a quant conviction, discretionary portfolio managers have long been known to observe intra-day patterns between markets to better understand the “mood” of the market – they are basically a sentiment tool. Quants have made the analysis of this information content more systematic, unveiling the greater extent of its potential. An essential feature of these measures is that by using a large number of data points, it is possible to look at much shorter timeframes and identify regime-changes or short-lived breakdowns more quickly that would otherwise have been obscured by a large timeframe of daily data.

    Chart 1 depicts correlation estimates based on 5 minute sampled data for Treasury-notes futures and S&P 500 futures for 2022 so far. This chart raises many interesting conclusions which can be summarised in three key points:

    • Firstly, there is no doubt that correlation has increased from the beginning of the year to now. It was in the -20 to -80% region until the end of January and has risen to +40% currently. Given the negative performance of equities, this means that bonds and equities have provided investors with a negative return, challenging the 50 / 50 portfolio dynamic.
    • Secondly, and more importantly, this increase is not a one-way move but has been done amid much turbulence. The chart shows a period of decline around Russia’s invasion of Ukraine – which started on 14 February, a week before the actual invasion. The indicators’ subsequent recovery has happened in rather large jumps.
    • Thirdly, it is these jumps that provide most of the messages behind this year’s price action. Many of them are tied to the publication of economic news. More interestingly, this news flow also relates to the conduct of monetary policy.  The four largest correlation jumps happened on the release of the US inflation report (on 11 May and 10 June) and the Federal Open Market Committee meetings in early May and mid-June.

    The message here is: the equity-bond correlation spiking higher is a symptom rather than the disease itself. While many see it as a correlation shock, equities and bonds are actually only jointly reacting to a common factor: expected monetary policy tightening. The macro message here is clear: bonds will not be a diversifying source of performance so long as duration is the main driving factor of markets. This also means that equity-bond correlation should normalise as soon as both bonds and equities start reacting to the other main market factor: expected earnings. This could very well drive the next leg of the cycle.

     

    Chart 1. Intra-day data-based correlation between equities and bonds in 2022

    Multi-Asset-simply-put-Intraday bond equities correlation-01.svg

    Source: Bloomberg, LOIM

     

     
    Simply put, the equity-bond correlation has surged on the back of tighter monetary policy. This situation could be temporary if the world economy starts to slow down.

     



    Macro/Nowcasting Corner

    The most recent evolution of our proprietary nowcasting indicators for world growth, world inflation surprises and world monetary policy surprises are designed to keep track of the latest macro drivers making markets tick. Along with it, we wrap up the macro news of the week.

    This week saw a mixed bag of macro data in the US. The Chicago Fed National Activity Index edged lower, showing a continuum of lower values that pointed to a period of declining growth. The Conference Board’s Leading Index did not say otherwise and new home sales also showed a continuous decline. The only time series moving in the opposite direction was the capacity utilisation rate that has not declined for the moment and the Kansas Fed Leading Indicators which remains consistent with a high growth situation. Our growth nowcaster for the US remains at a high level for the time being as employment data is solid.

    In the Eurozone, there were not many data points to crunch this week. Only the German IFO was really worth looking at, displaying a consistent level of uncertainty; we have rarely seen such a wide level of disagreement between the expectation and current situation components of the survey. In France, the manufacturing confidence survey continued to show an elevated level of economic activity in the country.

    The news flow in China was muted over the week.

    Factoring in these new data points, our nowcasting indicators currently point to:

    • Worldwide growth remaining solid. The US and Eurozone are still showing high numbers, but are now clearly declining in the Eurozone. In China, growth momentum remains subdued, but the majority of data is now improving – which is good news.
    • Inflation surprises should remain positive only for the Eurozone.
    • Monetary policy is set to remain on the hawkish side, mirroring the strength of economic activity.

    World Growth Nowcaster: Long-Term (left) and Recent Evolution (right)

    Multi-Asset-simply-put-Growth nowcaster-07June-01.svg

     

    World Inflation Nowcaster: Long-Term (left) and Recent Evolution (right)

    Multi-Asset-simply-put-Inflation nowcaster-07June-01.svg

     

    World Monetary Policy Nowcaster: Long-Term (left) and Recent Evolution (right)

    Multi-Asset-simply-put-Monetary Policy nowcaster-07June-01.svg

    Reading note: LOIM’s nowcasting indicator gather economic indicators in a point-in-time manner in order to measure the likelihood of a given macro risk – growth, inflation surprises and monetary policy surprises. The Nowcaster varies between 0% (low growth, low inflation surprises and dovish monetary policy) and 100% (the high growth, high inflation surprises and hawkish monetary policy).

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