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We scan through:

• Expected Returns

• Positioning Risks

• Short-Term Regimes

To chart a course for managing energy exposure.

Let’s dive in.

We begin with the Expected Returns. For those unfamiliar with our approach to expected-returns investing, you can find a complete breakdown here:

Energy market term structures continue to offer the most attractive risk premiums we have seen in the Russia-Ukraine War in 2022. We visualize this risk-premium below:

We can translate these expected returns into Naive Expected Sharpe Ratios, which are commensurately elevated:

We show that the distribution of these expected returns is uniform amongst the energy complex (ex-industrials):

For many investors who are native to equity and bond markets, these pro-cyclical expected returns (expected returns that rise with price rises) are unintuitive. In commodities, supply shocks drive up the spot price, while hedging pressures create a backwardated term structure. The combination of these dynamics creates a time-varying risk premium for those willing to buy the commodities into price increases. This dynamic opposes the mechanics in equities and bonds, where investors are largely rewarded for buying assets on weakness.

It is the systematic recognition of these mechanics that has allowed the Prometheus Expected Return Program to perform strongly in this environment:

Thus, we think that if there is a time to own commodities, it is in this type of backdrop. However, we need guardrails against a sudden turn in these conditions. Much of today’s regime’s dynamics are contingent upon the policy actions of the US administration and Iran's reaction function. A quick de-escalation of the military conflict will unwind speculative positioning in energy, but is unlikely to fully restore global supply in the near term or to remove the geopolitical risk premium now priced into global energy markets. As such, the biggest threat to energy exposure today is a military de-escalation-induced unwind in positioning.

To help navigate these dynamics, we share our positioning gauge (updated daily for Prometheus Institutional clients), which helps us determine whether prices are being driven by speculators or hedgers. A Speculative-Dominant oil market is more fragile than a Hedging-Dominant market:

Today, we’re in a Speculative-Dominant environment, with risk of a big positioning unwind. However, in the background, we also see a good amount of hedging from commercials. As such, we are in a positive, but not optimal, backdrop for energy positions. A modest unwind of speculative positioning, while negative in the short-term, may be the ideal backdrop for the energy complex over the medium-term— a dynamic we will continue to be on the lookout for. Until then, positioning risk abounds and should temper sizing.

Finally, we share our proprietary short-term regime recognition from the Prometheus Energy Program. To help our subscribers navigate these uncertain times, we continue to share the positions from the program via the Substack chat feature:

Based on the program's underlying signals, we can classify regimes as Bullish, Bearish, or Neutral. The objective is to identify the highest-signal periods for energy markets, not every signal:

As we can see above, our short-term regimes are good guides for the short-term price regime. Currently, these signals suggest we are in a Neutral Short-Term Regime, after being in a Bullish Short-Term Regime over the last month. This is not a bearish or bullish sign, but just an indication that short-term forward returns are less predictable than they have been recently.

Looking across Expected Returns, Positioning Risks, and Short-Term Regimes— we think energy exposure continues to make sense in the current backdrop. However, being prepared for a speculative unwind in sizing and drawdown controls remains imperative for navigating this environment optimally. If Expected Returns, Positioning, and Short-Term Regimes all align, conditions will be in place for significant long exposure. Until then, a more cautious approach is warranted. Clients of Prometheus Institutional can track the evolution of these conditions daily. Email us at info@prometheus-research.com for access.

Until next time.

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For context, we visualize the live returns for our Integrated Program below:

Our programs are operating in line with their long-term expectations. To today’s note, which we will publish in “positions-only” format.

Today, the S&P 500 Program is positioned as follows:

There are four major takeaways from these positions:

• Beta Timing: Our beta timing measures continue to show downward pressure on equity indexes coming from locally expensive equities, which are in a downtrend.

• Sector Selection: Macro markets are experiencing a sustained inflation shock, which will change the distribution of sector returns. Within the cross-section of equity sectors, our signals have moved to favour energy and builders. This signal is in its early days and does run a modest risk of reversal.

• Risk Control: Our risk control continues to guide us effectively in managing drawdowns. In a multi-standard deviation event across all our positions, our expected drawdown is 8%.

• Bond Overlay: While we face an ongoing inflation shock in market pricing, fundamental conditions are beginning to align more with a weakening growth backdrop. This weakness of growth, coupled with a modestly positive yield curve, makes treasuries and amenable exposure within a portfolio. This positioning is primarily about carry and diversification during a growth slowdown, rather than an outright alpha view.

These portfolio levers, in aggregate, create an allocation mix with a modest sector-selection bias towards rising inflation and a macro bias towards falling growth.

To this allocation, we add our Crisis Protection Program.

Read more

Subscribe now

We visualize the simulated return path for the program below:

To today’s note. Our observations are as follows:

• Macro assets have experienced a geopolitical shock in the form of the war in Iran, resulting in a shift in macro price trends to a decidedly inflationary cross-asset trend environment.

• The business cycle remains in an expansion, pressures on monetary policy to tighten have risen, and capacity utilization remains strong.

• Our forward-looking macroeconomic regime probabilities indicate a predominance of rising inflation outcomes.

• A procyclical allocation looks attractive, but with inflationary tilts.

Let’s begin sharing the data that drives our current assessment of the macro regime and our subsequent risk management and positions.

Macro Trend Monitors

Asset prices in aggregate reflect changes in conditions relative to expectations. As such, carefully monitoring macro market trends is an integral part of evaluating conditions in the macroeconomy. To do this, we use our macro trend monitors, which we share here. We begin with stocks:

Equity trends are maximally negative now. Next, we turn to bond market trends:

Bond market trends are also maximally negative. We now move on to broad commodity aggregates:

Commodity trends remain extremely strong amid geopolitical tensions. Next, we examine our macro trend signals for Gold:

Gold trends are mixed, but positive. Finally, we examine our trend signals for Bitcoin:

Bitcoin remains in a material downtrend.

Trend following is a good solution for many investors, as it is intuitive and provides solid risk control. However, the signals used in trend following are fairly basic, so we don’t think there should be a high barrier to entry for basic trend-following strategies. As such, we will provide access to a Basic Trend Program at zero cost to users for a portfolio of Stocks, Gold, Bitcoin, and Bonds. The program uses three layers of portfolio construction: a risk-parity base, a two-speed trend overlay, and a 15% maximum volatility cap. These layers are applied versus a benchmark beta of 60% Stocks, 15% Bonds, 15% Gold, and 10% Bitcoin. We will release a methodology note soon, but in the meantime, we share the summary statistics and current positioning below:

This program currently has a 0% max long position in Stocks, a 0% max long position in Bonds, a 50% max long position in Gold, and a 50% max long position in Bitcoin.

In risk-parity terms, this translates to Stocks: 0%, Bonds: 0%, Gold: 7%, Bitcoin: 5%, and Cash: 89%. This reflects an expected volatility target of 4%.

Please note that these positions do not directly reflect the Prometheus trend measures, which are relevant to our proprietary and paid programs. The positions in our Basic Trend Program use an equal split between 1-month and 6-month trends.

While basic trend following is a strong solution for many investors, there is a world of signals and strategies beyond it. We begin to address these in the following sections.

Macro Cycle Monitor

Our systems aggregate a wide range of fundamental economic data to produce timely, proprietary estimates of the current stages of the macro cycle. We share some of these gauges, starting with our signals for business cycle conditions:

Our latest readings continue to indicate an expanding business cycle. Next, we turn to monetary policy pressures. Our monetary policy gauge measures the pressures on the Federal Reserve to move monetary policy based on the trade-off between growth and inflation data. The higher our readings, the more pressure there is to hike policy rates. The lower the gauge, the more pressure there is to cut policy rates.

Pressures on monetary policy to tighten have further increased due to the energy price shock.

Read more

Subscribe now

For context, we visualize the live returns for our Integrated Program below:

Our programs are operating in line with their long-term expectations. To today’s note, which we will publish in “positions-only” format.

Today, the S&P 500 Program is positioned as follows:

There are four major takeaways from these positions:

• Beta Timing: Our beta timing measures continue to show downward pressure on equity indexes coming from locally expensive equities, which are in a downtrend.

• Sector Selection: Macro markets are experiencing a sustained inflation shock, which will change the distribution of sector returns. Within the cross-section of equity sectors, our signals have moved to favour energy and builders. This signal is in its early days and does run a modest risk of reversal.

• Risk Control: Our risk control continues to guide us effectively in managing drawdowns. In a multi-standard deviation event across all our positions, our expected drawdown is 8%.

• Bond Overlay: While we face an ongoing inflation shock in market pricing, fundamental conditions are beginning to align more with a weakening growth backdrop. This weakness of growth, coupled with a modestly positive yield curve, makes treasuries and amenable exposure within a portfolio. This positioning is primarily about carry and diversification during a growth slowdown, rather than an outright alpha view.

These portfolio levers, in aggregate, create an allocation mix with a modest sector-selection bias towards rising inflation and a macro bias towards falling growth.

To this allocation, we add our Crisis Protection Program.

Read more

Subscribe now

We visualize the simulated return path for the program below:

To today’s note. Our observations are as follows:

• Macro assets have experienced a geopolitical shock in the form of the war in Iran, resulting in a shift in macro price trends to a decidedly inflationary cross-asset trend environment.

• The business cycle remains in an expansion, pressures on monetary policy to tighten have risen, and capacity utilization remains strong.

• Our forward-looking macroeconomic regime probabilities indicate a predominance of rising inflation outcomes.

• A procyclical allocation looks attractive, but with inflationary tilts.

Let’s begin sharing the data that drives our current assessment of the macro regime and our subsequent risk management and positions.

Macro Trend Monitors

Asset prices in aggregate reflect changes in conditions relative to expectations. As such, carefully monitoring macro market trends is an integral part of evaluating conditions in the macroeconomy. To do this, we use our macro trend monitors, which we share here. We begin with stocks:

Equity trends are maximally negative now. Next, we turn to bond market trends:

Bond market trends have turned negative once again after a brief period of positivity. We now move on to broad commodity aggregates:

Commodity trends remain extremely strong amid geopolitical tensions. Next, we examine our macro trend signals for Gold:

Gold trends have deteriorated meaningfully. Finally, we examine our trend signals for Bitcoin:

Bitcoin remains in a material downtrend.

Trend following is a good solution for many investors, as it is intuitive and provides solid risk control. However, the signals used in trend following are fairly basic, so we don’t think there should be a high barrier to entry for basic trend-following strategies. As such, we will provide access to a Basic Trend Program at zero cost to users for a portfolio of Stocks, Gold, Bitcoin, and Bonds. The program uses three layers of portfolio construction: a risk-parity base, a two-speed trend overlay, and a 15% maximum volatility cap. These layers are applied versus a benchmark beta of 60% Stocks, 15% Bonds, 15% Gold, and 10% Bitcoin. We will release a methodology note soon, but in the meantime, we share the summary statistics and current positioning below:

This program currently has a 0% max long position in Stocks, a 0% max long position in Bonds, a 50% max long position in Gold, and a 50% max long position in Bitcoin.

In risk-parity terms, this translates to Stocks: 0%, Bonds: 0%, Gold: 7%, Bitcoin: 4%, and Cash: 89%. This reflects an expected volatility target of 4%.

Please note that these positions do not directly reflect the Prometheus trend measures, which are relevant to our proprietary and paid programs. The positions in our Basic Trend Program use an equal split between 1-month and 6-month trends.

While basic trend following is a strong solution for many investors, there is a world of signals and strategies beyond it. We begin to address these in the following sections.

Macro Cycle Monitor

Our systems aggregate a wide range of fundamental economic data to produce timely, proprietary estimates of the current stages of the macro cycle. We share some of these gauges, starting with our signals for business cycle conditions:

Our latest readings continue to indicate an expanding business cycle. Next, we turn to monetary policy pressures. Our monetary policy gauge measures the pressures on the Federal Reserve to move monetary policy based on the trade-off between growth and inflation data. The higher our readings, the more pressure there is to hike policy rates. The lower the gauge, the more pressure there is to cut policy rates.

Pressures on monetary policy to tighten have further increased due to the energy price shock. Next, we turn to measures of economic tightness. Our gauges of manufacturing tightness tell us whether the economy is running up against capacity constraints when its readings are high, or when there is a significant amount of economic slack when readings are low:

Our latest readings show that manufacturing capacity utilization is rising.

Combining these indicators, a Macro Cycle Allocation would be long stocks (34%), flat bonds (1%), and long commodities (34%). We visualize the simulated path of using this process below:

We turn next to our macro signal composites, which capture faster-moving price dynamics.

Macro Signal Composites

Using the macro cycle gauges, adding asset-specific factors, and leveraging carry, trend, and reversion, we can create asset-class-specific composite signals. We share these signals below and their latest readings. These signals are proportional to our conviction for a given asset and are directly tradeable. We begin with our stock signals for SPY:

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We visualize this below:

In this note, we discuss the principles driving the signal visualized above. We aim to provide a simple, actionable framework for thinking about Treasury exposure during this period of macroeconomic and geopolitical volatility.

The primary effect of the pressures in Iran has been surging energy prices across the oil complex. This surge in energy prices has two effects on the global economy and, in turn, Treasury markets:

• Inflation Shock: Energy is a core input to every economy. Energy price shocks reverberate through an economy’s cost structure, and this is reflected in inflation calculations. These shifts in inflation rates are incremental pressure on central banks worldwide to hike policy rates. This incremental pressure is reflected in Treasuries through some mix of higher real rates, breakeven inflation, or policy expectations. Regardless of the composition of the yield changes, the inflation shock mechanically drives yields higher. The inflation shock is a headwind for Treasuries.

• Demand Destruction: Inflation shocks are self-defeating. As prices spike relative to potential nominal demand, output begins to fall as real demand and output enter a downward spiral, nominal spending declines, and prices eventually fall to meet demand. The threshold at which this occurs is not knowable in advance, at least with systematic rigour; however, the signs of the turning point are apparent: deteriorating activity measures coupled with declining prices signal demand destruction and deflation. Demand destruction is a tailwind for Treasuries.

Today, market participants in fixed income are mixed on which outcome to position for: An Inflation Shock Or Demand Destruction? As quantitative systematic investors, our answer would be: Why not both, dynamically? We think our Inflation Nowcast can help us do so. As a refresher on our Inflation Nowcast:

As part of our systematic macro process, we track US CPI conditions promptly. Using market-based estimates, we can closely track the evolution of inflation pressures as reflected in the reported CPI. Our daily estimates for headline CPI closely track the official data, without the reporting delay inherent in official statistics. We find these measures particularly relevant for assessing ongoing pressures on fixed-income markets.

As noted previously, energy price spikes translate into inflation shocks that weigh on Treasuries. Our latest inflation nowcasts suggest material upward pressure on the CPI. Our latest readings suggest an annualized CPI rate of 6.1%, which is dramatically at odds with the Fed’s 2% inflation objective. Of course, we don’t expect year-over-year numbers to approach this pace, but it is nonetheless a sign of the times: we are in an inflation shock. This inflation shock will persist so long as the ongoing pace of inflation remains at odds with the Fed’s objective. Demand destruction will only take place once output contracts. Most importantly, demand destruction will be apparent as energy prices reverse, weighing on our timely CPI reads.

Combining the features of these dynamics, we expect our inflation nowcast to serve as a strong gauge of the market regime for Treasuries. The greater our latest readings exceed the Fed’s objective, the further we are into an inflation shock regime. The closer our gauges are to disinflationary or deflationary, the further we are into demand destruction. Furthermore, given our relatively short one-month window for calculating CPI, we will capture shifts in the energy components of CPI fairly quickly.

As such, we can construct a simple rule set for owning Treasuries: If our annualized CPI estimate is below 2%, we own fixed income. If not, we stay in cash. We’re not building a comprehensive trading system for treasuries using all the factors we track. Instead, we’re offering a simple, actionable roadmap for investors on how to think about their Treasury exposure during an inflation shock, which could lead to demand destruction. We show that the simulated performance of using the simple but defensible approach has been strong versus a buy-and-hold strategy:

We think that this approach, while simple, offers investors a clear guidepost to navigate treasury markets. Of course, the daily updates of our CPI Nowcast are available to Prometheus Institutional clients. However, we will also provide timely updates on this gauge here to help investors navigate these turbulent times.

Until next time.

Subscribe now

For context, we visualize the live returns for our Integrated Program below:

Our programs are operating in line with their long-term expectations. To today’s note, which we will publish in “positions-only” format.

Today, the S&P 500 Program is positioned as follows:

Read more

Subscribe now

Energy markets have begun to rally dramatically, pricing in a massive inventory shock. We see this across energy markets:

The cross-asset macro trend implications are clear: markets have moved to price an inflationary shock. We show how our macro regime probabilities have shifted in the US to reflect this shock:

This inflationary shock will eventually make its way into reported inflation data, which we show below:

Read more

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We visualize the simulated return path for the program below:

To today’s note. Our observations are as follows:

• Macro assets have experienced a geopolitical shock in the form of the war in Iran, resulting in a shift in macro price trends.

• The business cycle is now in a slowing expansion, pressures on monetary policy to tighten have risen, and capacity utilization remains strong.

• Our forward-looking macroeconomic regime probabilities indicate a predominance of rising inflation outcomes.

• A procyclical allocation looks attractive, but with inflationary tilts.

Let’s begin sharing the data that drives our current assessment of the macro regime and our subsequent risk management and positions.

Macro Trend Monitors

Asset prices in aggregate reflect changes in conditions relative to expectations. As such, carefully monitoring macro market trends is an integral part of evaluating conditions in the macroeconomy. To do this, we use our macro trend monitors, which we share here. We begin with stocks:

Equity trends are decisively negative now. Next, we turn to bond market trends:

Bond market trends have turned negative once again after a brief period of positivity. We now move on to broad commodity aggregates:

Commodity trends remain extremely strong amid geopolitical tensions. Next, we examine our macro trend signals for Gold:

Despite the chop in Gold, the trend remains intact. Finally, we examine our trend signals for Bitcoin:

Bitcoin remains in a material downtrend.

Trend following is a good solution for many investors, as it is intuitive and provides solid risk control. However, the signals used in trend following are fairly basic, so we don’t think there should be a high barrier to entry for basic trend-following strategies. As such, we will provide access to a Basic Trend Program at zero cost to users for a portfolio of Stocks, Gold, Bitcoin, and Bonds. The program uses three layers of portfolio construction: a risk-parity base, a two-speed trend overlay, and a 15% maximum volatility cap. These layers are applied versus a benchmark beta of 60% Stocks, 15% Bonds, 15% Gold, and 10% Bitcoin. We will release a methodology note soon, but in the meantime, we share the summary statistics and current positioning below:

This program currently has a 50% max long position in Stocks, a 0% max long position in Bonds, a 100% max long position in Gold, and a 50% max long position in Bitcoin.

In risk-parity terms, this translates to Stocks: 23%, Bonds: 0%, Gold: 18%, Bitcoin: 5%, and Cash: 54%. This reflects an expected volatility target of 8%.

Please note that these positions do not directly reflect the Prometheus trend measures, which are relevant to our proprietary and paid programs. The positions in our Basic Trend Program use an equal split between 1-month and 6-month trends.

While basic trend following is a strong solution for many investors, there is a world of signals and strategies beyond it. We begin to address these in the following sections.

Macro Cycle Monitor

Our systems aggregate a wide range of fundamental economic data to produce timely, proprietary estimates of the current stages of the macro cycle. We share some of these gauges, starting with our signals for business cycle conditions:

Our latest readings continue to indicate an expanding business cycle, though we see further signs of slowing. Next, we turn to monetary policy pressures. Our monetary policy gauge measures the pressures on the Federal Reserve to move monetary policy based on the trade-off between growth and inflation data. The higher our readings, the more pressure there is to hike policy rates. The lower the gauge, the more pressure there is to cut policy rates.

Pressures on monetary policy to tighten have further increased due to the energy price shock. Next, we turn to measures of economic tightness. Our gauges of manufacturing tightness tell us whether the economy is running up against capacity constraints when its readings are high, or when there is a significant amount of economic slack when readings are low:

Our latest readings show that manufacturing capacity utilization is rising.

Combining these indicators, a Macro Cycle Allocation would be long

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This week, we also offer an active overlay through our Energy Program. The Energy Program seeks to provide exposure to the energy complex using our short-term timing measures. The objective of the Energy Program is to provide dynamic exposure to energy that can complement equity and fixed-income portfolios.

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For context, we visualize the live returns for our Integrated Program below:

Our programs are operating in line with their long-term expectations. As we approach the one-year anniversary of the program, we continue to seek to add more signals and return streams to further improve long-term expected performance. Below, we share the simulated historical performance of our Integrated Program:

To today’s note. The team is hard at work on a variety of research projects; as such, we will publish in “positions-only” format. Today, the S&P 500 Program is positioned as follows:

Read more

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We visualize the simulated return path for the program below:

To today’s note.

Basic Trend Program

Trend following is a good solution for many investors, as it is intuitive and provides solid risk control. However, the signals used in trend following are fairly basic, so we don’t think there should be a high barrier to entry for basic trend-following strategies. As such, we will provide access to a Basic Trend Program at zero cost to users for a portfolio of stocks, Gold, bitcoin, and bonds. The program uses three layers of portfolio construction: a risk-parity base, a two-speed trend overlay, and a 15% maximum volatility cap. These layers are applied versus a benchmark beta of 60% Stocks, 15% Bonds, 15% Gold, and 10% Bitcoin. We will release a methodology note soon, but in the meantime, we share the summary statistics and current positioning below:

This program currently has a 50% maximum long position in Stocks, a 100% maximum long position in 30-year Treasuries, a 100% maximum long position in Gold, and a 0% position in Bitcoin.

In risk-parity terms, this translates to: Stocks: 32%, Bonds: 91%, Gold: 25%, Bitcoin: 0%. This is a leveraged portfolio targeting a 9.4% volatility.

Please note that these positions do not directly reflect the Prometheus trend measures, which are relevant to our proprietary and paid programs. The positions in our Basic Trend Program use an equal split between 1-month and 6-month trends.

While basic trend following is a strong solution for many investors, there is a world of signals and strategies beyond it. We begin to address these in the following sections.

Read more

Subscribe now

For the latest data through December, our systems place Real GDP growth at 2.88% versus one year prior. Below, we show our monthly estimates of Real GDP relative to the official data:

In December, GDP came in at -0.11% versus the prior month. Below, we show the weighted contributions to the most recent one-month change in real GDP, along with the recent history of month-on-month GDP. Additionally, we show the contribution by sector to monthly GDP in the table below:

The domestic engines of growth continue to hold steady and remain additive to real output, though we see some signs of slowing. We scan through the individual components, with a focus on domestic activity.

Consumption

In December, real consumption spending increased by 0.05%. Over the last year, consumption has added 1.2% to the GDP growth of 2.88%.

Under the aggregate data, services spending continues to support ongoing consumer spending, while goods have become a meaningful drag:

Even though aggregate consumption remains positive, some slowing is apparent, and is reflected in a narrowing of consumer spending breadth:

This narrowing breadth of consumer spending is largely coming from weak cyclical consumer spending:

In past cycles, this weakness in cyclical spending would, in itself, have been a cause of recession. However, the shifting structure of the economy towards a services-dominated one continues to keep the economy steady. Nonetheless, this is something to monitor closely.

Investment

In December, real gross investment remained flat. Over the last year, investment has added 0.65% to GDP growth of 2.88%.

Business investment remains weak, with construction and transportation spending continuing to weigh on fixed investment:

While these classically cyclical areas of the economy continue to show weakness, technology and related areas continue to show steady growth:

Finally, and most notably, industrial equipment investment has turned upwards:

Importantly, this upturn has been a broad-based one:

Much like consumer spending, business fixed investment shows readings that in past cycles have looked consistent with recessionary pressures, with declining residential construction and transportation equipment spending. However, the revival of industrial equipment investment and the stability of technology investment continue to deter recessionary downturn.

Government

In December, real government expenditures increased by 0%. Over the last year, government spending has added 0.09% to real GDP growth of 2.88%.

Government output has moderated meaningfully per the official data and diverged from our estimates. However, we find this to be a feature of the BEA's treatment of the government shutdown rather than an indication of a major shift in government output. This is because furloughed federal employees received back pay; the shutdown had no impact on nominal federal compensation and was reflected as a temporary increase in the prices paid for federal employee compensation. Below, we show how nominal spending continued despite a modest downtick:

With the resumption of regular operations of the government, we expect government spending to converge with our estimates over the next quarter.

Trade

In December, real export revenues decreased by -0.17%. Over the last year, exports have added 0.78% to GDP growth of 2.88%.

In December, real import expenditures increased by 0.02%. Over the last year, imports have added 0.13% to GDP growth of 2.88%.

The key takeaway is that trade is no longer a major incremental tailwind, but it is not exerting material drag either. The impulse from global demand has moderated, yet it remains broadly consistent with steady expansion rather than contraction.

At present, the domestic economy continues to carry this cycle. Trade is neutral-to-slightly supportive, not a source of stress.

GDP: Synthesis

Additionally, we show the composition of the monthly estimates of nominal GDP, broken into real GDP growth and inflation. Our latest estimates place nominal GDP at 5.86% versus one year prior, with real GDP growth of 2.88% and inflation of 2.98%:

For further insight into whether GDP conditions are consistent with recessionary pressures, we aggregate macroeconomic indicators, consistent with the NBER methodology of recession classification, into a recession probability monitor. This gauge gives us a real-time understanding of developing recessionary pressures. Currently, recession probabilities are at 29%:

Finally, we zoom out to offer what the mosaic of economic data says about the pervasiveness of GDP growth. Our GDP Nowcast economic data across 75 measures of real growth conditions to understand the economic conditions in a timely manner. We share both the current level of the nowcast in blue, along with a diffusion index of the underlying components in red. Currently, 51% of subcomponents are rising, consistent with early indications of a recession:

Below, we visualize the prospective paths of real GDP growth over the next twelve months using our data trajectory monitor. We share two processes. First, we extrapolate the current trend in the data to visualize the prospective trajectory of GDP based on the current trend. Additionally, we share our forward-looking estimates for real GDP growth:

GDP conditions remain mixed. Classical cyclical and rate-sensitive parts of the economy continue to show weakness, while non-cyclical areas add stability. Given these conditions, GDP growth will likely peak in the next 3 to 6 months, driven by time-series effects. A mixed, but positive outlook for the economy persists.

Equity Strategy

We translate these fundamental macro dynamics into systematic investment views for the equity market. When approaching equity markets, we think there are four major perspectives from which to take market views:

• Expected Returns

• Cyclical Regime

• Earnings Mispricing

• Tactical Positioning

These views span the spectrum of timeframes we can express our equity views on. We offer our systematic readings for each.

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For context, we visualize the live returns for our Integrated Program below:

Our programs are operating in line with their long-term expectations. As we approach the one-year anniversary of the program, we continue to seek to add more signals and return streams to further improve long-term expected performance. Below, we share a sneak preview of the next generation of tools we have in development at Prometheus:

We look forward to sharing these new programs with you soon. To today’s note. The team is hard at work on a variety of research projects; as such, we will publish in “positions-only” format.

Read more

Subscribe now

We visualize the simulated return path for the program below:

To today’s note. Our observations are as follows:

• Macro assets are experiencing cross-asset trends that are beginning to shift, with equity trends now in negative territory, commodity trends remaining strong, and bond trends remaining weak.

• The business cycle is now in a slowing expansion, pressures on monetary policy remain biased towards tightening, and capacity utilization remains strong.

• Our forward-looking macroeconomic regime probabilities indicate a predominance of disinflationary outcomes.

• It is early days, but a more cautious asset allocation looks warranted.

Let’s begin sharing the data that drives our current assessment of the macro regime and our subsequent risk management and positions.

Macro Trend Monitors

Asset prices in aggregate reflect changes in conditions relative to expectations. As such, carefully monitoring macro market trends is an integral part of evaluating conditions in the macroeconomy. To do this, we use our macro trend monitors, which we share here. We begin with stocks:

Equity trends have turned nascently negative. Next, we turn to bond market trends:

Bond market trends have turned positive. We now move on to broad commodity aggregates:

Commodity trends remain strong. Next, we examine our macro trend signals for Gold:

The gold uptrend remains intact. Finally, we examine our trend signals for Bitcoin:

Bitcoin remains in a material downtrend.

Trend following is a good solution for many investors, as it is intuitive and provides solid risk control. However, the signals used in trend following are fairly basic, so we don’t think there should be a high barrier to entry for basic trend-following strategies. As such, we will provide access to a Basic Trend Program at zero cost to users for a portfolio of stocks, Gold, bitcoin, and bonds. The program uses three layers of portfolio construction: a risk-parity base, a two-speed trend overlay, and a 15% maximum volatility cap. These layers are applied versus a benchmark beta of 60% Stocks, 15% Bonds, 15% Gold, and 10% Bitcoin. We will release a methodology note soon, but in the meantime, we share the summary statistics and current positioning below:

This program currently has a 50% maximum long position in Stocks, a 100% maximum long position in 30-year Treasuries, a 100% maximum long position in Gold, and a 0% position in Bitcoin.

In risk-parity terms, this translates to: Stocks: 20%, Bonds: 53%, Gold: 15%, Bitcoin: 0%, and Cash: 12%.

Please note that these positions do not directly reflect the Prometheus trend measures, which are relevant to our proprietary and paid programs. The positions in our Basic Trend Program use an equal split between 1-month and 6-month trends.

While basic trend following is a strong solution for many investors, there is a world of signals and strategies beyond it. We begin to address these in the following sections.

Macro Cycle Monitor

Our systems aggregate a wide range of fundamental economic data to produce timely, proprietary estimates of the current stages of the macro cycle. We share some of these gauges, starting with our signals for business cycle conditions:

Our latest readings continue to indicate an expanding business cycle, though we see further signs of slowing. Next, we turn to monetary policy pressures. Our monetary policy gauge measures the pressures on the Federal Reserve to move monetary policy based on the trade-off between growth and inflation data. The higher our readings, the more pressure there is to hike policy rates. The lower the gauge, the more pressure there is to cut policy rates.

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Below, we visualize the systematic application of these principles of expected returns to a diversified portfolio of equities, fixed income, commodities, and currencies across developed markets:

Above, we visualize returns by systematically adjusting our exposure to the expected returns of a developed-market (DM) asset basket. This DM basket contains the equities, sovereign bonds, and currencies of the US, Canada, UK, Japan, Germany, and Australia, along with global commodity exposures in WTI Crude, Brent Crude, Heating Oil, Gasoil, Copper, and Aluminium.

In this note, we outline the framework for our portfolio construction process and describe what it reveals about the global cross-asset expected-return landscape.

The Framework

In this section, we will outline the framework for systematically constructing our portfolio. The purpose of this section is not to give a step-by-step process for replicating this portfolio, but rather to offer the mechanical framework used in portfolio construction in an intuitive fashion. We visualize our portfolio construction process below:

Expected Return Measures: While conceptually expected returns are uniform across asset classes, in practice, their definitions vary. We use a combination of earnings yields (equities), bond yields (fixed income), the term structure (commodities), and rate differentials (currencies) to define expected returns. We treat gold as a currency and use a mix of the long-term realized return and real yields to measure expected returns. These measures are intentionally simple but defensible to align with discretionary intuition.

Naive Expected Sharpe Ratios: Using our expected return measures, we compute naive expected Sharpe Ratios based on local volatility levels. Our preference here is for shorter-horizon volatility lookbacks, as they better account for volatility clustering. These naive expected Sharpe Ratios are not intended as short-term timing signals, but rather as structurally grounded measures of forward risk-adjusted return.

Portfolio Allocations: Portfolio allocations are scaled proportionally to our naive Sharpe Ratios. All assets in the portfolio trade in large, liquid futures markets. As a result, the program is not subject to structural leverage constraints and is unconstrained in expressing long or short exposures.

Dynamic Volatility Targeting: The program maintains a maximum risk budget of 10% annualized volatility. The aggregate naive expected Sharpe Ratio scales portfolio-level exposure. A higher expected risk-adjusted return increases utilization of the risk budget, while a lower expected risk-adjusted return reduces exposure.

Combining these measures creates the Prometheus Expected Return Program for DM Markets. Let’s dive into the empirics and what they tell us about the global macro landscape today.

Equities: Anywhere But The US

We begin our exploration with DM equity markets. Below, we visualize the equal-weighted expected return profile of DM equity markets:

Above, we show that a DM equity basket offers positive excess returns relative to local cash rates. While positive and attractive, these expected returns are not particularly elevated relative to history, largely because realized returns in global equity markets have been high (recall that expected returns fall as realized returns rise). This basket of expected returns has been materially weighed down by US expected returns, which are effectively at zero. Meanwhile, economies with less tech-centric indexes like the UK and EU (Germany) show far more attractive return-to-risk characteristics.

Importantly, this dispersion is somewhat structural rather than cyclical. US equities have experienced a multi-year valuation expansion concentrated in a narrow group of high-growth, high-duration technology companies. As valuations rise, forward earnings yields compress mechanically, reducing embedded expected returns even if growth expectations remain strong. In contrast, UK and European indices are more heavily weighted toward financials, industrials, energy, and materials—sectors that trade at lower multiples and whose valuations have not expanded as much. As a result, their forward earnings yields remain elevated, producing higher mechanically derived expected returns.

We visualize this uneven distribution of Naive Expected Sharpe Ratios below:

Correlations across these equity markets are fairly strong; combining these assets into a portfolio offers only a mild improvement in expected risk-adjusted returns. Nonetheless, owning a basket of these equities offers a better exposure than owning any single one. Below, we show the naive expected Sharpe ratio of our portfolio of these equities:

We note three important features here. First, a global equity portfolio offers higher expected returns than a US-only portfolio— a crucial observation for US investors. Second, a mix of assets is likely to outperform any one particular asset. Finally, a mix of global equities, while more attractive than owning any individual country, offers only modest expected returns relative to history.

Fixed Income: The Most Attractive Asset Class

We next turn to developed market sovereign bond markets. Below, we visualize the equal-weighted expected return profile of DM fixed income markets.

Above, we show that a DM bond basket offers modest positive excess returns relative to local cash rates. While the opportunity set has improved materially from the deeply negative expected returns observed during the global post-COVID monetary policy hiking cycle, current expected returns remain moderate relative to history.

Importantly, dispersion across countries is again material. Markets such as Japan and Canada offer yields much more attractive than those in the US. These yield differentials largely reflect much more significant inflationary pressures in these regions relative to the US, resulting in weak realized returns. However, these weak realized returns potentiate future returns. Therefore, if these countries do not experience further inflationary acceleration, bondholders will be materially rewarded relative to US bondholders.

We visualize the distribution of Naive Expected Sharpe Ratios below:

Correlations across developed bond markets are also relatively strong, though generally lower than in equities. Combining these markets into a portfolio provides some diversification benefit, but the improvement in expected risk-adjusted return is again incremental. Nonetheless, a basket of developed sovereign bonds offers a more balanced exposure than any single market, smoothing country-specific policy and inflation risk.

Below, we show the naive expected Sharpe ratio of our portfolio of these bonds:

We note three important features here. First, a global bond portfolio currently offers a meaningfully higher expected return profile than we have seen in the post-COVID era. Second, cross-country diversification modestly improves risk-adjusted return relative to holding any individual bond market. Finally, fixed income offers a higher expected return than equities on a risk-matched basis, while offering a hedge to weaker growth conditions, which makes an expected return weighted portfolio of fixed income assets a compelling addition to our equity basket.

Currencies: Broadly Long USD

We next turn to developed market currency markets. Below, we visualize the equal-weighted expected-return profile of DM currencies through a dollar-centric lens:

Above, we show that our non-USD currency basket currently offers a modestly negative expected return profile. However, unlike equities and bonds, we find much more dispersion in currency expected returns. This is primarily driven by the variation in monetary policy measures across global central banks. In practice, short-rate differentials are the dominant driver of this dispersion. The wide gap between US and Japanese policy rates continues to embed a meaningful carry advantage for USD over JPY, reflecting the Bank of Japan’s comparatively accommodative stance relative to the Federal Reserve. In contrast, both Canada and the Euro Area have policy rates that are closer to US levels, though meaningful differentials persist. In the case of gold, real yields remain elevated relative to history, offering modest expected returns compared with cash. These varying dynamics create a healthy amount of dispersion in the distribution of Naive Expected Sharpe Ratios :

Correlations across developed currency pairs are meaningful but structurally lower than in equities or sovereign bonds. As a result, combining currencies into a portfolio offers somewhat greater diversification benefits than within-region equity or bond baskets. Nonetheless, the improvement in expected risk-adjusted return remains incremental. A diversified currency basket primarily smooths idiosyncratic policy and rate-cycle exposure rather than dramatically increasing expected Sharpe. Below, we show the naive expected Sharpe ratio of our portfolio of these currencies:

We note that the naive expected Sharpe ratio for a portfolio of currencies yields returns similar to those of equities today, while adding diversification.

Commodities: Energy Looks Attractive

We next turn to global commodity markets. Below, we visualize the equal-weighted expected return profile of major commodity contracts across energy and industrial metals.

Above, we show that the commodity basket currently offers a modestly positive expected return profile, though with significant cross-asset dispersion. Unlike equities and bonds, where valuation metrics evolve gradually, commodity expected returns are largely driven by term structure dynamics and inventory conditions. Periods of backwardation embed positive roll yield and therefore positive expected returns, while contango environments mechanically compress forward return potential.

Importantly, dispersion across individual commodities is pronounced. Energy contracts—particularly refined products such as heating oil and gasoline—exhibit stronger expected Sharpe Ratios, reflecting tighter physical markets and supportive term structures. By contrast, industrial metals such as copper and aluminum display weaker or even slightly negative expected return profiles, consistent with softer demand dynamics and flatter or contangoed curves. We visualize the distribution of Naive Expected Sharpe Ratios below:

Correlations across commodities are lower than within regional equity or bond markets, though still influenced by broad macro cycles. Combining commodities into a basket provides diversification benefits and smooths idiosyncratic supply shocks, but dispersion remains an important feature of the opportunity set. Below, we show the naive expected Sharpe ratio of our commodity sub-portfolio:

Unlike equities and fixed income, the carry embedded in the term structure of the commodities curve is not as mechanically linked to forward returns, and does not offer a persistently positive risk premium. Furthermore, after accounting for asset volatilities, our naive expected Sharpe ratios are not as compelling as a simple look at the term structure may imply. Nonetheless, a portfolio of commodities is undoubtedly value-additive to a global expected return portfolio.

Prometheus Expected-Return Program

So far, we have examined each asset class within our DM basket individually. We now combine these sub-portfolios to form the Prometheus Expected-Return Program. Below, we visualize portfolio risk allocation across the 24-asset universe:

Above, portfolio risk allocation refers to the notional exposure of each position scaled by its expected volatility. Capital is directed toward assets offering the highest expected return per unit of risk, while total portfolio risk is moderated through diversification.

We offer two perspectives to quantify this diversification benefit. First, we compare the aggregate naive expected portfolio Sharpe Ratio (blue) to the simple average Sharpe Ratio of the underlying asset classes (red):

Diversification does not change expected return; it reduces volatility. If all asset classes were perfectly correlated, there would be no diversification benefit, and the blue and red lines would coincide. The greater the gap between the aggregate Sharpe and the average Sharpe, the larger the diversification benefit.

Second, we measure diversification through the portfolio’s effective number of bets. While the program spans 24 assets, correlations across markets reduce the true number of independent return streams. The chart below shows how the effective number of bets evolves over time. When correlations rise, breadth compresses. When cross-asset opportunities become more dispersed, breadth expands. This increase in independent exposures lowers portfolio volatility relative to expected return and strengthens aggregate risk-adjusted performance.

The program currently exhibits a meaningful level of effective breadth relative to history. The combination of cross-asset dispersion and diversification benefits supports a healthy utilization of the portfolio risk budget, as shown below.

Thus, after systematically scanning across the global expected return landscape, we observe that current opportunities are concentrated primarily in global fixed income and long dollar exposures. Within both equities and fixed income, US assets offer comparatively limited expected return relative to their global peers. A dynamic expected return portfolio applied across developed markets currently exhibits a naive expected Sharpe Ratio of approximately 1.02, supported by meaningful cross-asset breadth. This breadth allows the portfolio to assume material risk while maintaining expected compensation per unit of volatility.

So, to answer the question posed in the title of this note — Where Are the Expected Returns?

Not in the US.

Until next time.

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For context, we visualize the live returns for our Integrated Program below:

Our programs are operating in line with their long-term expectations. As we approach the one-year anniversary of the program, we continue to seek to add more signals and return streams to further improve long-term expected performance. Below, we share a sneak preview of the next generation of tools we have in development at Prometheus:

We look forward to sharing these new programs with you soon. To today’s note.

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We visualize the simulated return path for the program below:

To today’s note. Our observations are as follows:

• Macro assets are experiencing cross-asset trends that are beginning to shift, with equity trends weakening, commodity trends remaining strong, and bond trends remaining weak.

• The business cycle is now in a slowing expansion, pressures on monetary policy remain biased towards tightening, and capacity utilization remains strong.

• Our forward-looking macroeconomic regime probabilities indicate a predominance of rising nominal growth outcomes.

• A procyclical asset allocation remains appropriate, but caution is warranted.

Let’s begin sharing the data that drives our current assessment of the macro regime and our subsequent risk management and positions.

Macro Trend Monitors

Asset prices in aggregate reflect changes in conditions relative to expectations. As such, carefully monitoring macro market trends is an integral part of evaluating conditions in the macroeconomy. To do this, we use our macro trend monitors, which we share here. We begin with stocks:

Equity trends have turned neutral as prices stagnate. Next, we turn to bond market trends:

Bond market trends remain negative. We now move on to broad commodity aggregates:

Commodity trends remain strong. Next, we examine our macro trend signals for Gold:

Despite the sell-off in Gold, the trend remains intact. Finally, we examine our trend signals for Bitcoin:

Bitcoin remains in a material downtrend.

Trend following is a good solution for many investors, as it is intuitive and provides solid risk control. However, the signals used in trend following are fairly basic, so we don’t think there should be a high barrier to entry for basic trend-following strategies. As such, we will provide access to a Basic Trend Program at zero cost to users for a portfolio of stocks, Gold, bitcoin, and bonds. The program uses three layers of portfolio construction: a risk-parity base, a two-speed trend overlay, and a 15% maximum volatility cap. These layers are applied versus a benchmark beta of 60% Stocks, 15% Bonds, 15% Gold, and 10% Bitcoin. We will release a methodology note soon, but in the meantime, we share the summary statistics and current positioning below:

This program currently has a 100% maximum long position in Stocks, a 100% maximum long position in 30-year Treasuries, a 100% maximum long position in Gold, and a 0% position in Bitcoin. In risk-parity terms, this translates to: Stocks: 22%; Bonds: 59%; Gold: 17%; Bitcoin: 0%; with cash at 1%.

Please note that these positions do not directly reflect the Prometheus trend measures, which are relevant to our proprietary and paid programs. The positions in our Basic Trend Program use an equal split between 1-month and 6-month trends.

While basic trend following is a strong solution for many investors, there is a world of signals and strategies beyond it. We begin to address these in the following sections.

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You can read the 27-page primer detailing the mechanics of our approach to our S&P 500 Program below:

And the primer for our Crisis Protection Program as well:

For reference, we visualize the simulated path of the integrated Prometheus S&P 500 + Crisis Protection Program below:

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And the live returns for the Integrated S&P 500 + Crisis Program:

Our program is operating in line with its long-term expectations. Today, the S&P 500 Program is positioned as follows:

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Over the years at Prometheus, we have spent a great deal of time developing timely tracking of economic conditions consistent with GDP accounting. Said differently, for every major economic data series released in the US, we have a quantitative estimate of how it flows into GDP and corporate profits, and how it is reflected in markets.

As such, we think working through these mechanics may offer some clarity to investors at a time when the aggregate picture looks unusually muddled. The objective of this note is to present our mechanical approach for examining the labor market’s effects on three areas:

• GDP Growth

• Earnings

• Markets (Stocks & Bonds)

We then apply that mechanical approach to the current context to offer a conceptual roadmap for navigating today's markets.

Before diving into the effects of the labor market, we think it is crucial to understand the labor market itself and its drivers. At Prometheus, we think the most important metric for assessing the state of the labor market is aggregate employment growth. Employment growth is the broadest measure of the labor market and reflects both secular and cyclical dynamics in the economy. We can decompose employment growth into three parts:

• Population Growth: Population growth is the driver of the long-term trend in employment. Population growth alone does not determine the pace of employment growth; it only potentiates it. How much of that population growth is harnessed through employment depends on participation and unemployment rates. Nonetheless, the secular trend in employment is determined by the pace of population growth. This trend is a slow-moving phenomenon measured over decades rather than years.

• Participation Rates: In any given population, only a certain percentage is willing and able to work or participate in the labor force. The higher this participation rate, the higher employment is likely to be at any time. The participation rate is determined by demographic factors, particularly age and nationality. While participation rates are slightly more variable than population growth rates, they too are largely secular phenomena with long, consistent trends.

• Unemployment Rates: Unemployment rates account for virtually all cyclical variation in the labor market. For a given population and participation rate, there are only so many employees corporations are willing to hire. During extremely strong business conditions, businesses increase their hiring faster than the labor force grows, so unemployment rates fall. During recessions, businesses reduce their headcounts, leading to higher unemployment rates.

The cumulative effects of changes in population, participation rates, and unemployment rates determine employment growth. Employment growth is the most important driver of economic growth over time, mechanically driving and statistically explaining most changes in output. Employment growth directly leads to income growth, which in turn leads to spending growth. Household income and consumption are the biggest drivers of US economic activity, with employment growth as the primary engine of gains in both. Population and productivity trends slowly feed into trend rates of GDP growth, while shifts in the unemployment rate define cyclical variation. Therefore, employment growth is almost linearly related to GDP growth. The only way output and employment can meaningfully deviate from one another is if output per worker dramatically increases. This rare divergence between output and employment is what we are seeing in today’s economy. We will address this topic further in a later section. Still, for now, we stay with the mechanics—with our primary takeaway that the relationship between employment and output is fairly linear.

While the linkages from employment to output are direct, the relationship between employment and earnings is more mixed. Employment directly contributes to household income, and rising employment is typically a good sign for corporate earnings. However, it is essential to recognize that every unit of wages paid to households is a cost to businesses. Whether employment is positive for earnings depends on whether households’ rate of spending outpaces their rate of income. This can happen through a reduction in households’ savings rate, the spending down of accumulated wealth, or borrowing against future income. Regardless of the source, for employment to be a net positive for earnings, the growth in wages paid by businesses must be slower than the growth of household consumption. On the same coin, labor market weakness, if offset by higher consumption spending, can often be positive for earnings. We find this to be the case today—employment has been slowing, but spending continues at a strong pace, supporting earnings. While this may be an unintuitive circumstance at the headline level, it remains consistent with our template.

So far, we have discussed the direct impacts of employment on output and earnings. These impacts can largely be traced through the macroeconomic accounts. However, when we turn to the impacts of labor on markets, the effects are less grounded in accounting linkages and more tethered to market pricing. This market pricing is largely dependent on macro market participants’ interpretation of the data and the flow-weighted average interpretation of the expected path of the data. This pricing mechanism is significantly less tight than accounting linkages, but nonetheless consistent over time. We focus on the two major markets: fixed income and equities.

Fixed-income markets are more focused on the effect of labor markets on real GDP, whereas equities are more focused on the effect of labor markets on earnings. We discuss each. Expectations for Federal Reserve policy dominate fixed-income markets (Treasuries in particular). On most days, virtually all of the returns in Treasury markets can be attributed to shifts in policy expectations. Fed policy itself is driven by the Fed’s policy objectives: maximum employment and price stability. The Fed’s full-employment objective makes labor dynamics directly tied to market pricing of expectations about Fed policy. Recall, there are three components of employment: population, participation, and unemployment. The Fed is most concerned with smoothing cyclical variation in the economy and, as such, tends to focus on the unemployment rate and its dynamics rather than on population or participation dynamics. This is because the Fed has a greater ability to influence business cycle conditions through its interest rate policy than to affect long-term demographics. As such, shifts in the unemployment rate or cyclical labor market indicators affect fixed-income markets. These cyclical shifts align with shifts in real GDP, given the fairly linear relationship between labor and output outlined in our earlier sections. As such, the primary avenue for labor concerns to be reflected in markets is via the Treasury market. This pricing also impacts all other asset classes, as expectations for monetary policy impact the discount rate used to discount cash flows across assets. Nonetheless, its effect on Treasuries is the most profound and the principal driver of the asset class.

As noted, discount rate expectations impact all asset classes—which means that cyclical labor market dynamics impact all asset classes. However, they do not necessarily form the principal risk driver for all assets. Equities fall into this category, with earnings expectations being the predominant driver of their returns over time. As described previously, labor markets do not have a direct relationship with earnings—there is a sweet spot in which labor market growth is strong enough to support incomes and spending, but not so strong as to erode corporate margins. This sweet spot is where labor markets and earnings expectations move in sync. Outside of this zone, earnings expectations (and, in turn, equities) can move in opposing directions. Crucially, unlike the Treasury market, where the unemployment rate is principally important, it is total employment (which fuels aggregate income and spending) that is the principal driver of the effect of the labor market on equities. Equities require a steady flow of labor to support corporate output, but their earnings depend on whether consumer spending outpaces labor income.

In summation, the labor market is driven by population, participation rates, and unemployment rates. GDP growth is directly driven by employment growth, as it fuels the majority of income and spending. Corporate earnings growth is not directly affected by the labor market but depends on the pace of consumption relative to income, which is supported by employment growth. Fixed-income markets primarily reflect the cyclical tightness or looseness of the labor market, best captured by the unemployment rate. Equity markets depend on the flow of total employment growth to support strong consumption relative to labor income.

Overall, the labor market does not have a homogeneous impact on the economy or markets. Today, we are seeing all of these nuanced linkages manifesting in historic levels of divergence, creating a complex environment for those not following them. We outline how we see these mechanics in motion in the next section.

Mechanics In Motion

We apply the mechanics discussed to today’s context to understand the macroeconomic circumstances. Aggregate employment has begun to falter, but this decline comes from a declining workforce rather than rising unemployment:

Said differently, this weakness isn’t coming from cyclical weakness, but rather from a secular shift in demographics over an unusually short time frame. This weakness in employment, regardless of its source, is a weight on real GDP:

However, despite weakness in labor growth, real wage growth has been strong, supporting strong real incomes:

This rise in real wages has offset the weakness in labor market growth, supporting output. Therefore, even though employment has dragged on GDP growth, output per worker has readily offset this weakness.

While output per worker has powered higher incomes, consumer spending has moved faster than incomes, resulting in a meaningfully positive impulse to corporations’ earnings:

Above, we show our estimate of the impulse to corporate profits from the balance between households’ spending and their income. This dis-saving continues to be a material support to earnings.

Turning to markets, the lack of a rise in unemployment rates continues to limit the need for the Fed to react with monetary easing:

While the profit impulse from households continues to support extremely strong earnings:

Applying our template for how labor conditions impact the economy and markets, we see a labor backdrop that is indeed weak, but weak for non-cyclical reasons. The guideposts for a regime change will be an increase in cyclical unemployment, a decline in real wage rates, and a deceleration in consumption relative to income. Until these shifts, the labor market will likely continue to support equities and weigh on fixed income.

Until next time.