Outlook 2024
What’s in store for investors in 2024? Despite lingering uncertainty and volatility, find out why it’s not all doom and gloom.
Asset allocation
13 November 2023
A sudden pandemic, invasion or election result can throw markets into a tailspin in days, and seemingly turn an investor’s strategy upside down. Can the relationships between different aspects of macroeconomics and financial market indices help investors to allocate assets more robustly at such times?
By Lukas Gehrig, Zurich Switzerland, Quantitative Strategist; Nikola Vasiljevic, Ph.D, Zurich Switzerland, Head of Quantitative Strategy
Please note: This article is more technical in nature than our typical articles, and may require some background knowledge and experience in investing to understand the themes that we explore below. All data referenced in this article is sourced from Bloomberg unless otherwise stated, and is accurate at the time of publishing.
The wealth advisory world is at a crossroads, it seems. Investors are coming to terms with whether the COVID-19 pandemic and the current geopolitical uncertainty will ultimately lead to a world of persistent higher inflation, excessively higher rates and ever increasing government debt; or if the economic effects of the virus will unwind soon and return the economy to an era of slow growth and structurally weak inflation.
In addition, the financial community is coming to terms with an altered equity-bond correlation, a key measure for asset allocation strategies, that has shot up to levels last seen twenty years ago (see chart). This has implications for the roles of equities and bonds in a portfolio. At current levels of correlation, bonds do not act as the shock absorbers to equities as they have done over the last twenty years.
The correlation of monthly returns for US equities and US government bonds over one-, two- and five-year rolling windows since 1975 (where 1 or -1 implies a perfect correlation between the assets, and zero implies no correlation)
The health of the economy will ultimately drive the course of financial markets, the former determining the supply and demand for raw materials and financing, the pricing of finished goods and the creditworthiness of businesses and governments.
The course an economy takes may change, but the effects that different parts of it have on the pricing of financial instruments, evolve only slowly. For example, the intensity of oil production might change and affect the sensitivity of oil prices to different levels of activity, but these shifts usually occur at a snail’s pace. Therefore, understanding the economy can help to make sense of financial markets.
Economic data can be difficult to interpret. For every data release, there is a story that could involve revisions of past data, that shines fresh light on current data, an unexpected political effect, a seasonal distortion or just the statistical noise of a bustling nation.
Hence, it can pay to listen closely and ignore the noise by looking at various indicators and cross-checking them, as well as smoothing the regular data beats by studying the momentum built up over many months rather than every snapshot on its own.
To help get to the bottom of macroeconomic data more, many readily available monthly or weekly data prints1 have been collected for leading economies. They have been classified to show the different aspects of an economy: hard activity (output measurements), soft activity (survey-derived), consumption, labour, housing, monetary policy and prices.
Within each aspect, momentum gauges comparing data released in the last three months, versus those published in the last six months, have been assembled and then boiled down to one single momentum indicator2.
Heatmap of aggregated momentum indicators for the US and Chinese economies. Green (red) colours indicate acceleration (deceleration) in momentum
Negative (red) readings show the aspects of the economy that are slowing, while positive (green) readings highlight those aspects that are quickening in pace. This means that even though an economy may still be expanding, if it does so more slowly than six months ago, the activity momentum reading will be negative.
The momentum in US prices has re-accelerated recently. However, consumption and housing have tipped over into deceleration, while activity indicators have gained momentum. For China, on the other hand, activity indicators imply a stagnating economy while the housing and consumption gauges suggest deceleration.
The usefulness of short-term momentum snapshots for asset allocation, which tends to be a long-term game, lies in the reaction of market participants to new data. A series of odd tunes may alter the key that financial markets are humming to.
As seen recently, it is not always the same parts of the music score that carry the melody. Inflation, which was more a background noise for decades, has taken centre stage since 2022. As such, analysis has been carried out into how different parts of financial markets react to each aspect of economic momentum separately3.
The analysis shows that for the US economy and its effect on global financial markets, positive momentum in survey data and consumption are the most conducive aspects to positive returns in risky assets such as high yielding bonds, equities and equity-like hedge funds (see table).
In something of a surprise, hard activity data like industrial production is less of a driver for risky assets, but instead acts more as confirmation of conditions that drive the returns of safer bonds. Quickening US prices have had a positive effect on the returns of commodity indices while hurting the returns of (global) government bonds.
Partial correlations of three-month-ahead returns of broad financial market indices to the three-month over six-month momentum indicators for the US economy
Temporary macro tunes will not in themselves determine the long-term success of an investment strategy. While it takes more than a single melody to write a symphony, the sensitivities to momentum don’t change quickly. So, a long-term investment arch is nothing more than a series of shorter momentum melodies.
This brings us back to the recent momentous changes seen in equity-bond correlations, highlighted at the top of the article. Just why have such correlations bounced back into positive territory, as seen for large parts of the 70s, early 80s and early 90s?
The answer pertains to economic indicators that are back in the macro headlines, as was the case a few decades ago: inflation is the main worry for investors and it comes at a time when economic activity is anaemic at best. This drives equities and bonds in the same direction.
To explore the usefulness of the momentum indicators for tactical portfolio overlays, the US Macroeconomic Momentum Indicators (MMIs) were tested as inputs to a ‘random forest classifier’ model. The goal was to determine whether the respective financial market indices would decline, remain stable or increase over the following three-month period after the release of the respective macro data.
Looking at the most important MMI for each asset class suggests that the classifier model has built an understanding of various economic cycles. As such, activity indicators are preferred for signals on corporate bond prices and metals, while labour appears to be more important for equities.
In the out-of-sample tests, MMIs were most useful at producing signals for developed market equities, US dollar (USD) cash and real estate, and performed worst for hedge funds and commodities. This discrepancy could be due to the overall commodity index being composed of more diverse components than, for example, the developed market equity index.
With the current set of US momentum data shown in the heatmap above, the classifier model sees the highest probability of capital gains over the upcoming three months to be in developed market equities, emerging market equities and direct real estate indices. Less probability for capital gain is seen in commodity indices and developed government bonds.
The outlook for growth can be summarised as elevated, if softening inflation, a slowdown in growth, a weakening labour market and somewhat restrictive monetary policy are likely to persist as headwinds. In such a stagflationary backdrop, one would expect equity-bond correlations to remain elevated and that bonds will act more as a substitute to equities, rather than as a complement to them, in a portfolio well into 2024.
This calls for different sources of portfolio diversification. Simply diversifying is unlikely to be enough, without identifying what it is against. Some commodity exposure can help to shield against bouts of inflation, but at the cost of additional risk when activity weakens.
A well-diversified portfolio needs to be constructed with different macroeconomic risks in mind. Understanding the way that markets react to different macro tunes does not help to forecast the future. However, it means that investors can be better prepared for whatever the future holds in store.
What’s in store for investors in 2024? Despite lingering uncertainty and volatility, find out why it’s not all doom and gloom.
For the US models referenced in the article, the following series are used. Activity hard: Industrial Production, Industrial Production Survey Surprise, Factory Orders, Capacity Utilisation. Activity soft: ISM New Orders, ISM Services New Orders, ISM Manufacturing, ISM Services, Empire Manufacturing, Philadelphia Fed Business Outlook, Small Business Optimism. Consumption: Personal spending, Retail sales advance, Durable goods orders, Michigan Sentiment. Housing: Housing starts, New home sales, Existing home sales, Building permits, FHFA house price index, NAHB housing market index. Labour: Nonfarm payrolls, Unemployment rate, Job openings, ISM Employment, personal income, initial jobless claims, Continuing claims, ADP Employment. Monetary policy: Fed funds Rate, M2. Prices: Producer price index final demand, ISM Prices paid, Citi Inflation Surprise Index, CPI index, CPI index survey surpriseReturn to reference
Principal component analysis is used to condense information contained within many input series to one resulting output seriesReturn to reference
To this end, partial correlations are computed, which represent the correlation of one macroeconomic aspect of momentum to the returns of a financial market index in three-months’ time, while cancelling out the interference from all of the other macroeconomic aspectsReturn to reference