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From a comprehensive assessment of the oil shock on the macro data to how to structure and trade it in markets, Aahan and Bob covered it all. Check it out:

Until next time.

Prometheus continues to grow and remains committed to bringing institutional-grade systematic investment strategies and research to everyday investors. This week, we hit another big milestone: 15,000 readers. To welcome you all, we’re offering a discount to new subscribers for the next year:

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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.

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The conversation went deep on many topics, including:

• The Divergence “under the hood” of the macro aggregates.

• The Dichotomy of a strong nominal economy and a weak real economy.

• The Whipsaw of the bond market.

• The Indomitability of corporate profits.

And of course, they dedicate a significant amount of time discussing why investors should Pay For Portfolios, Not For “Content”.

Topics worth reflecting on:

Until next time.

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The forces behind the reflation—strong households and AI capex—now face a labor-market drag that’s hard to ignore. The issue isn’t that growth is about to collapse. It’s that pricing has moved beyond what the economy can deliver.

This reflation came after a tariff-driven growth scare, when the economy surprised to the upside and markets had to reprice that strength. In that environment, the data consistently exceeded expectations baked into markets.

Two clear engines powered the entire reflation trade:

• Stable, resilient household incomes and spending

• A massive AI capex boom that offset traditional cyclical weakness

Together, they produced growth far stronger than markets expected after the tariff scare.

That outperformance created a clean setup: the data was stronger than the pricing. You didn’t have to overthink it—long equities and commodities simply worked. But the key question now is whether that strength relative to expectations can continue.

We are more skeptical of whether this can continue today. Our skepticism is not about recession risk. It’s about the gap between economic reality and what’s now embedded in equity prices. Driving the gap between the current pricing and the likely economic path are two forces pulling in opposing directions:

1. AI-driven business investment — a large positive

2. Labor supply — a growing structural negative

We start with labor. Employment growth is determined by population growth, participation, and hiring. Over long horizons, population growth does most of the work.

And this is where the drag appears. Population growth is slowing mainly because immigration has slowed. Immigration doesn’t just add people—it adds workers, because immigrants participate in the labor force at much higher rates than the native-born population.

So when immigration drops, you lose two things at once: the number of new people entering the country and the number of new workers entering the labor force. This slowing immigration growth creates a meaningful headwind for overall job growth and, in turn, GDP.

Now the other side: AI capex. This investment boom is unusual because it doesn’t create an equivalent rise in labor income today. The spending shows up as business investment, while the “cost” (depreciation) comes later. So AI capex flows straight into profits in the present. That’s why earnings expectations surged and why the market has anchored to the AI-capex story.

Earlier in the year, equities were undervalued based on that profit impulse. The rally corrected that. But now earnings expectations have moved beyond what a labor-constrained economy can sustainably deliver. This has first shown in cyclicals, particularly small caps and homebuilder stocks. Small caps and homebuilders don’t benefit from the AI-capex profit cycle, and they remain tied to the more traditional, interest-rate-driven business cycle. As economic activity outside tech slows, these sectors begin to feel the weight.

So the question before us today is whether the equity market—primarily dominated by a profit impulse coming almost solely from technology capex—can continue to offset the headwinds coming from the labor-supply overhang. To be direct: we don’t have a clear answer. However, it is worth recognizing that even AI consumption is fueled by labor growth—and without an ongoing expansion of labor, even AI capex cannot continue indefinitely. Said more plainly: AI capex can account for a large majority of growth, but it cannot sustainably account for more than 100% of GDP and earnings growth on a multi-quarter basis. This will likely be resolved either through lower aggregate growth or rising “non-AI growth.” Both require technology and related companies to take a smaller share of the total pie.

That’s why the Prometheus Multi-Strategy Program has initiated negative beta exposure this week, not because of a top-down bearish view, but because bottom-up cyclical signals deteriorated together. To be clear, while this may be a turn for the equity market, we do not think it is a meaningful turn for the economy.

The economy is still fine. But the pricing of the economy—especially earnings—is stretched. With structural labor constraints in place, markets may be asking more of profits than the real economy can deliver.

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Prometheus is built on years of consistent and diligent tracking of every piece of macroeconomic data and translating that data into actionable investment strategies. This process involves creating a systematic framework for tracking the economy and markets, understanding the nuances of hundreds of data releases, mapping the effects of these data on individual markets, and quantitatively forecasting markets on a daily basis. The accumulation of all the things we have learned, from small nuances around the way CPI data is calculated, to cross-asset phenomena like trend following, is embodied in the Prometheus Multi-Strategy Program:

Having spent years turning macroeconomic views into market views, we came to a conclusion a long time ago:

Long-term economic views are useless as standalone investment tools.

Long-term forecasting is an inherently fragile exercise, riddled with statistical uncertainty. Even if one could forecast the economy perfectly over the long run—a heroic assumption—the improvement to an investor’s portfolio would be marginal at best, and often negative. This is deeply counterintuitive for many investors. Further, it runs directly against the foundation of an entire industry built around selling long-term macro opinions to investors, branding narrative conviction as portfolio edge. As always, our views are grounded in quantitatively verified observations. We share some of these observations below.

We focus on the equity market for these observations due to its centrality to global investors. We begin by asking the question, “What if we could perfectly predict real GDP growth?” Surely, we would be able to time the market exceptionally well. Reality deviates meaningfully from this expectation, which we visualize below:

Above, we compare the excess returns (over cash) of a buy-and-hold S&P 500 position with a dynamic strategy based on a perfect directional prediction of real GDP one year forward (Perfect Prediction). If real GDP over the next year is positive, the strategy goes long the S&P 500; if real GDP is negative, it goes short the S&P 500. Rebalanced daily. As we can see, perfectly predicting the direction of real GDP since 1985 does indeed yield some additional benefits, but it just barely moves the risk-adjusted return of the portfolio. Modestly decreasing the hit rate of the GDP forecast would effectively nullify any improvements to total returns. Therefore, unless you’re sure that a one-year forecast will have a 100% hit rate, you’re better off just owning passive exposure.

Some may argue that it's not about the binary level of growth, but rather about the direction of the rate of change. We find this approach to be empirically worse, largely because it reduces beta exposure dramatically:

Here, we compare the excess returns (over cash) of a buy-and-hold S&P 500 position with a dynamic strategy based on a perfect directional prediction of the rate of change of real GDP one year forward (Perfect Prediction). If real GDP growth one year forward accelerates relative to its 12-month trailing average, the strategy goes long the S&P 500; if real GDP decelerates, it goes short the S&P 500. Rebalanced daily. As we can see, perfectly predicting the direction of the rate of change in real GDP since 1985 would destroy wealth over time.

We take this evaluation even further, and ask, “What if we knew whether the price of the S&P 500 would be up or down over the next year?”. Of course, this approach must generate exceptional returns(?). We find intuition denied once again here:

Above, we compare the excess returns (over cash) of a buy-and-hold S&P 500 position with a dynamic strategy based on a perfect directional prediction of S&P 500 total returns over the next one year (Perfect Prediction). If total returns for the S&P 500 are positive over the next year, the strategy goes long the S&P 500; if the returns are negative, it goes short the S&P 500. Rebalanced daily. We see this approach underperforms a simple buy-and-hold strategy. The reason for this underperformance is subtle. While we may know whether the S&P 500 will be down over the next year, we don’t know how that price action will be distributed over the next day, week, or month. Navigating the path of returns is essential for market timing, and long-term forecasts do not provide insight into this path.

While we have focused on equity markets for these observations due to their centrality to global finance, our results are relatively uniform across markets. Long-term forecasts of growth, inflation, and asset prices consistently yield relatively mediocre outcomes compared to passive exposure—even with 100% accuracy on the direction of travel.

Yet, we find that there is an entire industry built around the notions that i) the long-term is more predictable than the short-term, and ii) that adjusting allocations based on these long-term predictions has significant value to investor portfolios. Furthermore, research services built around these ideas often share their long-term views, leaving clients to solve for positioning on their own—which is empirically the most challenging part, as demonstrated above. Often, macro research providers focus entirely on the big picture, with little regard for the intricacies of positioning.

We think these conditions create a misalignment of interest between long-term macro forecasters and their clients. The long-term forecaster remains focused on generating the best possible long-term forecast, despite the fact that this has minimal impact on investor portfolios. Often, this exercise is biased by the need to deviate from consensus, which has an asymmetric business payoff. Predict a boom or bust that nobody else predicts, and your business will benefit massively. The times it doesn’t come along, it matters little because you don’t recommend positions anyway. Meanwhile, the client must contend with the reality that long-term forecasts aren’t reliable ways to manage a portfolio, and even if they were, their accuracy is severely lacking. All of these dynamics come together to make much of the independent macro research business a content-driven business rather than an investment-driven one.

Does this mean that we think all macro research or long-term forecasting is useless and the industry should shut down? Absolutely not. However, we believe that real skill lies in translating macroeconomic views into tradable portfolios with an edge over simply holding beta. Any macro research provider that strives to do that, or enables an investor to do that, is worth every penny they charge. In the near future, we will provide a list of providers that fall into this category. This is also what we endeavour to do with our paid products. Note, this doesn’t mean that every research shop should begin role-playing as a hedge fund manager— but they do need to make sure they are offering value.

At Prometheus, our entire tracking and nowcasting of the economy is built around creating systematic tradeable views. That’s what our process is built for. Given that’s what it’s built for, we understand that basic tracking of the economy and some forecasting is not something you should pay for. Translating macro into forward-looking asset allocations is a complex endeavour requiring skill, which you should pay for, especially if you find someone who does it well.

So if your macro research provider performs exclusively big-picture analysis and leaves you high and dry on what to do in markets— you can get all that for free at Prometheus.

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US Treasuries have been some of the most challenging markets to navigate for investors over the last few years. The weakness in bonds began in 2022, with the Fed’s initiation of one of the fastest and largest tightening cycles in decades. The hiking cycle in itself caused significant damage to the treasury market, leading to drawdowns we haven’t seen since the 1970s in fixed income markets. However, to the surprise of market participants, bond markets did not recover and continued to face significant chop for several years, crowned by treasuries actually falling as the Fed began its easing cycle in late 2024.

These conditions created a somewhat novel dynamic relative to the long-term history of bonds: one where the price action in bonds was dominated by mean reversion. Those expressing views in line with these mechanics were significantly rewarded, with mean reversion strategies far outperforming simply holding bonds. We visualize this outperformance below, from the prior peak in the Fed Funds rate in 2023:

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In this note, we discuss the reasons we think this anomaly has existed, and most importantly: we evaluate whether it can continue.

Let us begin with our decomposition of bond returns sources over time:

As we can see above, there has been a significant upward shift in the share of our decomposition of bond returns explained by mean reversion since the 2022 hiking cycle. This is what enabled the previously illustrated bond-mean reversion strategy to perform so well. However, without this shift, the performance of this strategy was far weaker:

As we can see above, bond mean-reversion is not a standalone strategy that can continue to deliver excess returns. Unless the macro environment remains conducive.

To understand the macro factors driving these conditions, we begin with our macroeconomic decomposition of the returns of a treasury security. The changes in its yield drive the returns on a treasury bond. This yield is driven by changes in the short rate, expectations for the changes in the short rate, and the term premium. The expectations for the short rate are driven primarily by the evolution of the drivers of monetary policy. The term premium is driven by liquidity constraints of those further out on the curve and their ability to absorb treasury supply. Between the short rate expectation and the term premium, short rate expectations are by far the dominant driver of variation in the total returns of a bond.

This is where we have also seen the most action in terms of bond mean-reversion, i.e., expectations for monetary policy have continued to whipsaw dramatically over the last few years, to an extent seen before in history. The driving force behind this has been the stark contrast between the expected path of monetary policy, which has consistently anticipated easing, and the backdrop of elevated nominal activity, which has consistently suggested tighter or stable monetary policy. Markets have essentially expected three or more cuts ever since the hiking cycle began in 2022, regardless of the level of nominal GDP. This pricing, by historical measure, is almost always consistent with a recession:

The notable exception is, of course, the period from 1984 to 1986. However, this was a period of dramatic growth deceleration.

Nonetheless, the pricing of treasuries over the last few years has largely been consistent with a significantly slowing economy. While the economy has indeed slowed, it has largely not met the expectations embedded in the bond market.

Below, we show how meaningful monetary policy easing, including “insurance easing”, typically follows the NGDP path in terms of its delta:

As ever, the purpose of our Macro Mechanics is not to give you a market view, but rather to share our mechanical approach to markets.

Thus, when we examine the question: Will Bond Markets Continue to Mean-Revert? Our answer is: it depends on whether they are pricing the most likely path of nominal GDP. The greater the divergence between the growth expectations embedded in monetary policy and the future pace of nominal GDP, the greater the mean reversion potential.

Until next time.

Consistent with this idea, we present our Macro Mechanics, a series of notes that describe our mechanical understanding of how the economy and markets work. These mechanics form the principles that guide the construction of our systematic investment strategies. We hope sharing these provides a deeper understanding of our approach and ongoing macro conditions.

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Thus far in this series, we have covered a wide variety of topics, some of which we list below:

Thus far in our Macro Mechanics series, we have provided our understanding of the following subjects:

• Growth

• Inflation

• Liquidity

• Integrating Growth, Inflation, & Liquidity

• What is Beta?

• What is Alpha?

• Where Do Recessions Come From?

• What’s Priced In? The Bridge Between Beta & Alpha

• What Drives Bond Markets?

• What Drives Stock Markets?

• What Drives Commodities?

• What Is A Market Regime?

• How Do Valuations Impact Stock Markets?

• How Do You Beat The Stock Market?

• How Do Tariffs Impact The Economy?

• Are We In A Recession?

If you’re unfamiliar with our approach, we suggest checking out some of these notes, as they offer insight into our approach to markets. Let’s dive in.

A significant part of investing involves recognizing the risk of being wrong about one's portfolio positions, assessing the expected losses of those potential mistakes, and creating contingencies to protect against significant losses.

In our most recent Macro Mechanics note, we evaluated the risk of recession based on conflicting expansionary and contractionary forces in the economy. If you haven’t already read the note, we recommend doing so here:

We assessed that we are not in a business cycle downturn, but immigration shifts put us at risk of an idiosyncratic downturn regardless.

Consistent with this assessment, our systematic programs have been biased towards long equity exposure this entire year, and remain biased in that direction. However, we have begun to see indications of a significant slowdown in the labor market. In the event that such a slowdown metastasizes into a sudden recession, it would put our current positions at risk of losses. However, our process is dynamic and likely to adapt to sudden recessionary pricing. We outline the likely path if indeed our current equity bias is wrong-sided.

We see two extremes in terms of how a potential labor-shock-induced recession may manifest:

• A Rapid Sell-Off: These have become more typical since the GFC in 2008, lasting only a few months.

• A Prolonged Bear-Market: A bear market of 6-18 months was more typical during recessionary events prior to 2008.

We believe there are three key levers to pull to mitigate losses across various potential equity-sell-off archetypes, even with a starting bias towards being long equities as the recession unfolds:

1. Diversification: Diversification is the gold standard for protecting a portfolio from large and persistent drawdowns. The key to protecting equity market downside is selecting assets that have a positive long-term expected return and are economically biased to outperform during environments where equities underperform. A mix of Gold and TIPS offers these characteristics over time. Nominal bonds may be considered as well, but they continue to face challenges in today’s more inflationary backdrop.

2. Crisis Protection: During rapid sell-offs, equity markets often fall precipitously due to idiosyncratic, non-business cycle phenomena. These types of sell-offs are usually a sign of significant financial stress, and can be seen in short-term funding spreads, extremely elevated local cross-asset volatility, and inverted volatility curves. During these brief but severe periods of stress, owning long volatility via VIX futures may offer significant rewards and hedge any equity market downside, particularly if your portfolio enters these periods with long equity exposures.

3. Market-Timing: When in a rapid sell-off or prolonged bear market, adding a layer of market timing on top of a fundamentals-based process is essential. During an actual recession and bear market, price-based measures of market trends are critical to mitigating and potentially benefiting from equity market downside. Even if your investment process did not predict an ongoing drawdown in equity markets, it is essential to recognize it and adjust risk shortly after it begins.

Combining these three levers, we think that an active investment process can significantly mitigate the impact of a recession-induced equity market drawdown. As ever, these insights are backed by our own systematic study and implementation of these mechanics. Given that holding gold and TIPs are mechanical benefits and require no active investing, we isolate our price-based market timing and long volatility exposure to show the empirical benefits of such an approach:

The above only isolates a small part of our process aimed at dealing with equity market downside; as such, it does not deal with upside capture optimally. Recall, the focus of this note is on minimizing downside capture with a starting bias of being long equities.

Thus, when we take a step back and evaluate our long equity exposure, in the face of potential risks coming from the labor market, we expect a combination of diversification and market timing to enable us to adapt well if the situation requires it. For now, we continue to see the business cycle as expanding, and are positioned accordingly across programs.

These concepts can be applied regardless of whether you’re following our systematic programs, but if you’re interested in a programmatic process that applies all these principles, you can check out our integrated Prometheus S&P 500 + Crisis Protection Program:

Until next time.

Prometheus Crisis Protection: 33% Off

If you’ve already studied the Prometheus Crisis Protection Program Primer, you may be familiar with some of this content. If you haven’t checked out the primer yet, you can find it at the link below:

In a recent note, we described a process for how a passive equity investor can keep all of their S&P 500 returns while reducing their drawdowns by leveraging the Prometheus Crisis Protection Program. This approach uses leveraged S&P 500 exposure to create capital efficiency and allocates the remaining to the Crisis Protection Program. By its nature, this approach is an “offense-first” program— prioritizing constant exposure to the equity market. Today, we share the other side of that proverbial coin— the Defense-First Program.

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A Defense-First approach to investing prioritizes the mitigation of adverse macro conditions, such as recessions, stagflation, and market crashes, while treating long exposure to pro-cyclical assets as a secondary concern.

Every week, our Crisis Protection Program determines the allocation to Gold, TIPS, and VIX. The combined package of these assets performs best during crisis dynamics: recessions, stagflationary shocks, and financial crises. The inherent bias of this mix of assets is the exact opposite of equities, which prefer rising real growth and stable financial conditions. As such, positive return expectations for these assets often signal weaker return expectations for equities. Said more plainly, when our signals allocate heavily to Gold, TIPS, and VIX, it is usually indicative of a weak environment for stocks. The converse is also true; when our signals allocate minimally to Gold, TIPS, and VIX, it is usually indicative of a strong environment for stocks. Therefore, when our Crisis Protection Program has low holdings of Gold, TIPS, and VIX, it can be used as a signal to allocate to stocks.

Therefore, we can take the dynamic cash holdings from our Prometheus Crisis Protection Program and invest them in the S&P 500. We show the simulated performance profile of doing so:

As we can see above, this Defense-First approach to investing generates strong risk-adjusted returns versus holding equitie passively. This outperformance come through two features. First, scaling equity exposure after considering “defense-first” introduces a modest amount of timing alpha, effectively improving the risk adjusted returns of our equity holdings. Second, the diversification characteristics of blending equities with assets mechanically biased to outperform when equities underperform has a signficant impact on risk, reducing volatility and drawdowns. Putting these features together, our Defense-First Program shows outperformance versus equities, while still maintaining relatively elevated correlations to the S&P 500.

We think this approach to investment may be align with those that have a Defense-First mindset to investing. Further, this type of approach may be valuable in a time of historically anomalous macroeconomic conditions and elevated uncertainty. You can read our assesment of those conditions below:

If you’re interested in the Defence-First Program, you can avail of it via the Prometheus Crisis Protection Program. In the spirit of the program’s official release, we are offering a one-time discount of 33% on our monthly price for new annual subscribers. You can avail of this offer at the link below. The offer will expire very soon.

Prometheus Crisis Protection: 33% Off

Until next time.

Consistent with this idea, we present our Macro Mechanics, a series of notes that describe our mechanical understanding of how the economy and markets work. These mechanics form the principles that guide the construction of our systematic investment strategies. We hope sharing these provides a deeper understanding of our approach and ongoing macro conditions.

Subscribe now

Thus far in this series, we have covered a wide variety of topics, some of which we list below:

Thus far in our Macro Mechanics series, we have provided our understanding of the following subjects:

• Growth

• Inflation

• Liquidity

• Integrating Growth, Inflation, & Liquidity

• What is Beta?

• What is Alpha?

• Where Do Recessions Come From?

• What’s Priced In? The Bridge Between Beta & Alpha

• What Drives Bond Markets?

• What Drives Stock Markets?

• What Drives Commodities?

• What Is A Market Regime?

• How Do Valuations Impact Stock Markets?

• How Do You Beat The Stock Market?

• How Do Tariffs Impact The Economy?

If you’re unfamiliar with our approach, we suggest checking out some of these notes, as they offer insight into our approach to markets. Let’s dive in.

The US labor market is showing signs that are typically consistent with recessions— declining employment, rising unemployment, and cyclical weakness. Yet, nominal and real GDP conditions continue to remain positive, corporate earnings continue to expand, and risk assets stay within range of all-time highs. This constellation of macroeconomic conditions is largely inconsistent with the historical template of cause-and-effect linkages that have driven recessions through history. However, it is crucial to recognize that all recessions are driven and defined by a contraction of the labor market. As such, we think it is essential for investors to work through the mechanics of a recessionary process to contextualize today’s dynamics.

We start by outlining a typical recession process. For a detailed note on recession mechanics, we highly recommend reading our prior note describing recessions:

A business cycle recession typically begins with a tightening of financial conditions. This tightening of financial conditions elicits a drag on investment in the real economy. Over time, the dominant driver of corporate profits at the macro level is businesses’ own investment. With a prolonged decline in this investment, business profits begin to slow. This adverse chain of events is not experienced by the entire economy homogenously, but rather impacts industries with capital intensity much more so than others. These industries, if placed under enough pressure, begin to lay off their employees, but this does not cement the recession process in itself. For a recessionary spiral to start, the size of the layoffs needs to be adequate to put pressure on other areas of the economy, beyond those feeling the direct effects of declining investment levels. Once this pressure turns into economy-wide firing, due to declining economy-wide activity, it manifests primarily via rising unemployment rates for a given level of labor force participation and population growth. When rising unemployment drives a decline in employment alongside falling output, the recessionary process is underway.

Today, we have the unique circumstance in which financial conditions are loose, real investment conditions are mixed, corporate profits are elevated, and yet, employment has begun to show meaningful indications of weakness. In particular, both the household and establishment surveys have begun to show significant weakness. The household survey, in particular, shows signs that are consistent with the onset of a recession. Therefore, the question before investors today is: Can we have a recession without the typical sequence of events that define a business cycle downturn?

We believe the answers likely lie in understanding what is driving the current weakness in employment growth. When we triangulate across data, we see the following:

• Slowing population and participation rates are driving weaker employment growth, not the rising unemployment rates.

• Cyclical job sectors (manufacturing, construction, trade) have begun to see declining jobs, but the weakness is still small versus other sectors.

The combination of these labor conditions is indicative of a weak labor market environment, but the weakness is not business-cycle induced. In contrast to the labor data:

• Consumer spending continues at a strong pace.

• Business investment is positive but mixed. Industrial & construction activities are harmful, but information and intellectual property investments are very elevated.

The combination of these spending conditions suggests a mixed backdrop for the primary sources of corporate profits.

Therefore, we think that a case can be made for a slowing of the business cycle, but not a contraction of the business cycle. Furthermore, the weakness in the labor market is not driven by cyclical weakness— but rather by an immigration shift, changing both the pace and composition of labor market growth.

This backdrop warrants significant caution. While spending and income may well result in a positive profit backdrop, economic activity remains centered around the labor force. Regardless of whether the economy follows the archetypal business cycle template, the weakness of the labor market is noteworthy and concerning. For now, this weakness is not enough to create a self-reinforcing downwards spiral because we have yet to see adverse profit conditions. As such, we continue to view the business cycle as an expanding one, but one that’s at risk due to a labor force contraction.

We believe that navigating these dynamics effectively requires a combination of active investment strategies and diversification to protect the potential downside for risk assets. In an environment that is anomalous relative to most of history, we think diversifying against downside equity risk is imperative. In that spirit, we released our Crisis Protection Program. The Prometheus Crisis Protection program seeks to offer a portfolio diversifier during periods of economic and financial instability by blending active, long-only exposure to Gold, TIPS, and VIX. You can read all about it here:

Prometheus Crisis Protection: 33% Off

Until next time.

Welcome: 40%, Ends Friday

If you’ve already studied the Prometheus Crisis Protection Program Primer, you may be familiar with some of this content. If you haven’t checked out the primer yet, you can find it at the link below:

The S&P 500 is the core exposure for many investors. While the S&P 500 is a good asset over the long term, it can have large drawdowns. What if we can diversify the downside risk while maintaining the upside capture? Enter the Prometheus Crisis Protection Program.

Many investors want to maintain passive exposure to the S&P 500, but the market can go through periods of very weak performance. The Crisis Protection Program is designed to diversify during those periods of underperformance.

The program rotates between gold, TIPS, and VIX futures. These diversifiers, while valuable, often come at a cost—reduced upside in equity rallies. With some portfolio engineering, however, you can maintain the equity upside while reducing a portion of the downside.

The key is to use leverage intelligently—not to increase risk, but to allocate capital more efficiently. A straightforward implementation is to allocate 30% of capital to SPXL, a 3x S&P 500 ETF. Alternatively, the same can be achieved using S&P 500 Futures. That provides roughly 100% S&P 500 exposure financed at the risk-free rate plus a spread, leaving the remaining 70% of capital to allocate to the Crisis Protection Program. We show the simulated results of this portfolio below:

As we can see above, using the Crisis Protection Program as an overlay to S&P 500 exposure delivers higher absolute returns with lower risk and smaller drawdowns than holding the index alone. The drawdown benefits during periods of equity market stress are especially significant.

So what’s the catch?

You give up some of the cash rate plus a spread to finance the leveraged equity exposure. Crucially, this applies only to the 30% of the portfolio allocated to leveraged equities. Therefore, as long as you expect a mix of gold, TIPS, and VIX futures to outperform cash over the long term, this overlay will be value-additive. That’s before accounting for any potential active investing alpha. Of course, from time to time, the Crisis Protection Program itself will draw down. So, you may lag the index because Gold, TIPS, and VIX drag on performance for a while—but over time, they are likely to outperform cash and thus add value.

Given the low hurdle to add diversification, increase returns, and reduce drawdowns for a passive S&P 500 allocation, the Prometheus Crisis Protection Program is a strong complement for stock market investors.

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Until next time.

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This was a wide-ranging conversation, touching on a variety of topics, including the pros and cons of systematic versus discretionary macro, our tariff stress tests, and the nuances of our systematic macro approach.

If you're interested in systematic macro investing, navigating economic regimes, or building a repeatable and robust investment process, this episode is for you.

Until next time.

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If you are a professional investor interested in access to our institutional work or want a copy of this note, email us at info@prometheus-research.com.

Prometheus Equity Program Dynamic Equities

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In this note, we share a brief overview of our Dynamic Equity program. You can find the full note below:

There are two primary ways to generate returns independent of beta: by harnessing relative value opportunities or through market timing. Both these approaches can offer significant benefits versus passive beta. In addition to being durable approaches to generating alpha, they also provide diversification properties to one another. The Prometheus Equity Program seeks to leverage these mechanical relationships to create a balanced but dynamic exposure to cross-sectional and directional opportunities in equity markets across US equity sectors and global equity indexes. We show the summary sheet below for this program:

And the rolling performance statistics to evaluate return consistency:

We discuss the portfolio construction process in the next section.

The Prometheus Dynamic equity programs seek to invest dynamically in both cross-sectional and directional market opportunities. While we do not offer the specifics of our underlying signal construction, we describe the two major categories of signals that drive the program:

• Relative-Value: The programs use fundamental measures of earnings, value, carry, and macro fundamentals to assess the relative attractiveness of securities, creating cross-sectional signals.

• Market-Timing: The programs will also use measures of macro trend and mean reversion to generate directional signals.

Our dynamic equity programs aggregate the signals from these two sleeves to create portfolio views. This combination of relative value and market-timing signals allows our programs to choose to move exposures towards the most attractive opportunities. When there is a high degree of inter-market dispersion, our programs will favor a long/short stance. When macro conditions lead to large opportunities in beta via trend following or mean reversion, the programs will trade more directionally.

When it comes to position sizing, we’ve made a concerted effort to have all our signals in our Prometheus Institutional programs be directly proportional to their conviction. As such, all positions are sized in proportion to their signal strength. The only risk control that is applied to these positions is a 15% maximum volatility cap for each individual line item. Finally, gross portfolio exposures are leveraged 2X to achieve risk that is comparable to equity risk over time. We do not adjust or constrain risk beyond these measures. While it is suboptimal not to have risk control at the portfolio level, it is more beneficial to clients to receive raw portfolios and then manage their risk budget based on their appropriate circumstances, as this eliminates the path dependency from interfering with gross portfolio risk.

This process is applied to two distinct equity universes:

• US Equity Sectors: Information Technology, Healthcare, Consumer Discretionary, Telecommunications, Financial Services, Industrials, Consumer Staples, Utilities, Homebuilders, & Energy.

• Global Equities: United States, United Kingdom, Japan, Canada, China, Italy, France, Germany, India, & Australia.

Our Dynamic Equity program allocates these two strategies equally, treating them as an independent portfolio. These two sub-portfolios are available independently as part of the Prometheus Institutional Multistrategy Program. Please feel free to reach out to us if you’re an institutional investor and this program aligns with your investment mandate.

Until next time.

Consistent with this idea, we present our Macro Mechanics, a series of notes that describe our mechanical understanding of how the economy and markets work. These mechanics form the principles that guide the construction of our systematic investment strategies. We hope sharing these provides a deeper understanding of our approach and ongoing macro conditions.

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Thus far in our Macro Mechanics series, we have provided our understanding of the following subjects:

• Growth

• Inflation

• Liquidity

• Integrating Growth, Inflation, & Liquidity

• What is Beta?

• What is Alpha?

• Where Do Recessions Come From?

• What’s Priced In? The Bridge Between Beta & Alpha

• What Drives Bond Markets?

• What Drives Stock Markets?

• What Drives Commodities?

• What Is A Market Regime?

• How Do Valuations Impact Stock Markets?

• How Do You Beat The Stock Market?

• How Do Tariffs Impact The Economy?

We highly recommend reading these previous notes if you are unfamiliar with our approach. Today, we revisit a subject that has significantly impacted global macro markets: tariffs.

In our last Macro Mechanics note, we outlined our thoughts on the mechanical effects of tariffs and their likely pass-through to the economy. We highly recommend reading that note if you haven’t already, as it will offer vital context for the analysis presented in this note.

In today’s note, we assess the announced tariffs to determine whether the full slate of tariffs, if implemented, would have a material impact on economic conditions. The objective of this note is to evaluate the reasonable worst-case effects for corporate profits, trade balance, and overall activity.

Our takeaways are as follows:

• Tariffs, if implemented, will significantly weigh on gross trade. However, the effects on the trade balance may well be positive. This may result in a cosmetic boost to GDP, while total trade suffers.

• The tax effect of tariffs on corporations is insufficient to overcome business cycle forces in determining cyclical outcomes.

• While the linear impact of tariffs on corporate profits is modest, the non-linear effects on fixed investment are potentially much more negative. Currently, they imply a material weakening of the economic growth rates, but not a recessionary outcome.

Adding up these drivers, the tariffs’ impact on the trade balance has the potential to add approximately 0.64 % to annualized GDP. In comparison, the fixed investment impacts have the potential to detract approximately 1.3% from annualized GDP Growth. The net effect is a 0.66% drag on GDP growth. Our current systematic projection, based on domestic business cycle conditions, stands at 2.4%, excluding this drag. Accounting for this drag and time series factors, our estimate falls to 1.09 % GDP Growth over the next year.

It is essential to recognize that this projection is based upon the worst-case outcomes of tariff implementation, rather than the baseline projection. We find the confidence effects to be more significant, with both potential negative impacts on consumption and investment. These prospective impacts outweigh the impacts from trade itself. In large part, these confidence effects will be contingent on financial market outcomes across stocks, bonds, and the dollar. In this environment, the best forward-looking reading of the economy will likely come from cross-asset, macro market trends.

Let’s dive into the data driving this assessment. We begin with our evaluation of the tax effects of tariffs, i.e, the prospective drain on corporate profits. As systematic investors, we focus on the predominant cause-and-effect relationships that offer predictability for markets. One of these is whether business cycle conditions provide insights into the future of equity markets. Estimating the trajectory of corporate profits is a crucial component of this approach. Upon the announcement of tariffs, we needed to determine whether the outlier nature of tariffs was sufficient to override traditional business cycle forces and become the dominant driver of corporate profits. Tariffs are a tax paid by businesses, which they pass on to consumers. However, the first burden is paid by companies. As such, we sought to determine whether extremely high tariffs could have a significant impact on the structure of corporate profit growth rates. To create this understanding, we identified what we believed to be a substantial outlier event, namely a 10-fold increase in tariff rates, and estimated the impact on corporate profit growth if this rate had been applied throughout history. We found there to be minimal change to corporate profits even at a 10-fold increase. We visualize this below:

Above, we show corporate profit growth in blue, and corporate profit growth after subtracting a ten-fold increase in tariff rates. As we can see, our stress test indicates that the tax effect of tariffs is likely to be minimal, even in an outlier event such as a tenfold increase.

The announced tariff rates came out in line with this stress test, shocking markets and global policymakers. The weighted average effective import tariff rate, as announced, stands at

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During the interview, they dove deep on how we think about the major drivers of the macroeconomic cycle: Growth, Inflation, & Liquidity. They discussed practical steps for tracking these variables, their applications to various markets, and how they are shaping the current environment.

If you’re trying to build or enhance your macro framework, this podcast is for you.

Until next time.

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Consistent readers and clients will likely be familiar with our approach to using market regime monitors to identify trends. For those who are unfamiliar with this approach, we suggest reading through this Macro Mechanics note:

Our new Macro Regime Monitors are a continuation and improvement of our market-implied regime probabilities. Defining them concisely:

Our Macro regime monitors combine measures of macro trend, macro mean reversion, expected returns, and fundamental economic conditions to estimate tomorrow’s cross-asset, macro market environment.

We think this comprehensive approach to regime recognition captures all the major drivers of asset markets into a single definition. As a refresher, we believe two economic factors determine the relative returns between asset classes: growth & inflation. The permutations of growth and inflation:

• (+) G (-) I: Rising Growth & Falling Inflation

• (+) G (+) I: Rising Growth & Rising Inflation

• (-) G (-) I: Falling Growth & Falling Inflation

• (-) G (+) I: Falling Growth & Rising Inflation

Note that we have excluded liquidity as a driver above. This is not because liquidity is not a meaningful driver of macro markets but rather because its application to markets is significantly more nuanced and much more amenable to the relative value of credit spreads, yield curves, and macro asset differentials than betting on assets like stocks, bonds, commodities, and gold.

Returning to our Macro Regime Regime monitors— markets price these permutations of changes in growth and inflation with varying degrees of conviction on any given day. Typically, we can see these regimes in the relative price movement of assets. Each regime mechanically benefits specific assets:

• (+) G (-) I: Stocks & Credit

• (+) G (+) I: Commodities

• (-) G (-) I: Treasuries

• (-) G (+) I: TIPs

Thus, examining the relative performance of these assets allows us to estimate today’s regime. For instance, if stocks fall, commodities fall even more, while treasuries rally more significantly than TIPs— we are more confident that markets are moving in a manner consistent with (-) G (-) I than other alternative scenarios. As macro investors, we largely want to be able to invest in a manner consistent with tomorrow’s macro regime. Knowing today’s regime is relatively straightforward, but the question is whether today’s regime can persist into tomorrow.

To do this, we need to apply bottom-up forecasts for each asset primary asset class and compare those forecasts relative to each other to understand what is likely to dominate price action. This approach is dramatically different from our original programs (circa 2020) and what we see used by practitioners today. Most popular models today essentially leverage the persistence of price trends to predict and trade macro regimes. However, this leaves the success of one’s prediction conditional upon whether trends persist, which often is simply not the case. We recently documented an example of trend following can be a poor predictor of forward returns:

We think a combination of macro trends, macro mean reversion, expected returns, and fundamental economic conditions will likely offer a much better solution for estimating the probable outcome of markets. Using our proprietary tools, we can add up these fundamental and market-based tools to estimate the probability we see for tomorrow’s economic regime. We visualize this below:

Above, we show the evolution of our Macro Regime Probabilities over time in the area chart and their recent readings in the table on the right-hand side. The readings range from 0 to 100% across all regimes. The higher the reading, the more conviction we have that tomorrow’s regime will be consistent with our expectations. Given that these regimes account for an extremely wide array of factors, they offer significant insight into investment decisions. We show how using these regimes to enter and exit stocks, bonds, and commodities can be highly beneficial to long-term performance.

We begin with stocks:

Next, we show bonds:

Finally, we turn to commodities:

As we can see above, these regimes can be additive to long-term, long-only performance. They can help long-term performance by generating investable signals and helping investors contextualize the current macro environment by creating regime analogs. We define an analogous regime as one where the distribution of macro regime probabilities closely resembles those we see today. Using these regime probabilities, we can look at history to understand how asset markets acted when our regime expectations were similar to today's. Recall that this is how markets responded relative to our expectations for the future, not simply how they responded contemporaneously. We call these our Regime Expected Returns. We visualize the most recent readings below:

In the above visual, our systems look for instances where the distribution of regime probabilities resembles those of today's and look at how asset markets performed when we had similar expectations. Specifically, when our Macro Regimes Probabilities of (+) G (-) I, (+) G (+) I, (-) G (-) I, (-) G (+) I were around 40%, 20%, 20%, and 20%, respectively; we find that stocks, bonds, and commodities had Sharpe Ratios of 0.51, 0.29 and 0.22. More simply, stocks outperformed when we last expected this regime mix.

These visualizations (Macro Regime Probabilities and Regime Expected Returns) encapsulate hundreds of economic activity and price data measures concisely and in a manner that we leverage as investors. Given this approach's comprehensiveness and its application's simplicity, this will become the primary tool we use to manage our Prometheus ETF Portfolio. We visualize this simulated portfolio below relative to its underlying beta:

These improved and streamlined tools will boost performance while significantly increasing the ease of understanding. We look forward to sharing updated positioning based on these tools with our ETF Portfolio members.

Consistent with this idea, we present our Macro Mechanics, a series of notes that describe our mechanical understanding of how the economy and markets work. These mechanics form the principles that guide the construction of our systematic investment strategies. We hope sharing these provides a deeper understanding of our approach and ongoing macro conditions.

Subscribe now

Thus far in our Macro Mechanics series, we have provided our understanding of the following subjects:

• Growth

• Inflation

• Liquidity

• Integrating Growth, Inflation, & Liquidity

• What is Beta?

• What is Alpha?

• Where Do Recessions Come From?

• What’s Priced In? The Bridge Between Beta & Alpha

• What Drives Bond Markets?

• What Drives Stock Markets?

• What Drives Commodities?

• What Is A Market Regime?

• How Do Valuations Impact Stock Markets?

• How Do You Beat The Stock Market?

We highly recommend reading these previous notes if you are unfamiliar with our approach. Today, we turn to a subject that many macro-market investors are concerned about: tariffs.

Since the U.S. presidential election replaced the previous administration, tariffs have become a primary focus for markets, with incremental news flow driving price action. The durability of price trends will depend on whether economic data comply with price moves to create a robust macro trend. To that end, we offer our understanding of how tariffs may impact the economic picture.

We expect tariffs to have a minimal impact on nominal GDP conditions, a marginally higher impact on profits, and a potentially moderate impact on inflation. We dive into the mechanics of these outcomes. Before we look at the specifics of each prospective impact, we want to begin with a high-level conceptual description of how tariffs flow through the economy.

A tariff is a tax imposed by a government on imported goods and services to make imports less attractive than domestic production. The objective of tariffs is to improve the trade balance in favor of the domestic economy, either by increasing domestic business profits or by reducing the government deficit. As such, tariffs operate by changing the composition of nominal spending rather than directly impacting the total amount of nominal spending. This dampens the direct effects of tariffs on nominal GDP and biases their effects toward profits and inflation. We explain each channel.

Read more

Consistent with this idea, we present our Macro Mechanics, a series of notes that describe our mechanical understanding of how the economy and markets work. These mechanics form the principles that guide the construction of our systematic investment strategies. We hope sharing these provides a deeper understanding of our approach and ongoing macro conditions.

Subscribe now

Thus far in our Macro Mechanics series, we have provided our understanding of the following subjects:

• Growth

• Inflation

• Liquidity

• Integrating Growth, Inflation, & Liquidity

• What is Beta?

• What is Alpha?

• Where Do Recessions Come From?

• What’s Priced In? The Bridge Between Beta & Alpha

• What Drives Bond Markets?

• What Drives Stock Markets?

• What Drives Commodities?

• What Is A Market Regime?

• How Do Valuations Impact Stock Markets?

We highly recommend reading these previous notes if you are unfamiliar with our approach. Today, we discuss a complex and challenging subject: How Do You Beat The Stock Market?

The US equity market has far outperformed its peers globally and significantly outperformed most active managers domestically. Since 2010, the S&P 500 has provided investors with a return-to-risk profile consistent with those of a sophisticated asset manager, generating 13.3% annualized returns over cash at 17.2% volatility, i.e., a Sharpe Ratio of 0.78. Given the conservative nature of most institutional investors, even if they have matched or somewhat outperformed this risk-adjusted return, they were unlikely to have maintained such a high volatility profile, leading to underperformance. Combining these risk-adjusted and absolute return characteristics with the proliferation of low-cost ETFs— the S&P 500 has become the primary benchmark against which most investors measure success.

We think it is unlikely that equities can continue to perform at this pace over the long term. Over a very long history, beginning in the 1900s, the equity market has had a Sharpe Ratio closer to 0.35, i.e., about half of what we have seen since 2010. That is our long-term expectation. However, how that long-term expectation comes to fruition is a question whose answer extends beyond the capabilities of reasonable quantitative investing. We may have another two decades of exceptional equity returns followed by a lost decade, a re-run of the technology bubble followed by an exceptional bust, or any one of the infinite number of permutations of the future. Those long-term future paths are unknowable, and any strategy that seeks to bet on those paths is much closer to a coin flip than durable alpha in its odds of success.

Thus, given the centrality of US equity markets today, we think it is our role as active investors to seek to add value to this core component of investor portfolios. If most investors seek equity-like exposure, we think it’s our job to add an edge to that exposure. We believe that with reliable, durable, and uncorrelated alpha, it is possible to outperform the equity market significantly over a full investing cycle. In this note, we share our thoughts on the levers that we think we can pull to create these outcomes.

We think there are four big levers that we can pull to create durable outperformance versus the S&P 500:

• Sector Selection

• Beta Timing

• Dynamic Risk Control

• Strategy Overlays

We think pulling these levers can create a portfolio that seeks to maintain significant or leveraged upside capture to bull markets and limited or short exposure to bear markets while maintaining a much more moderate drawdown profile versus the benchmark. As ever, our approach is driven by a macro-based edge leveraged via quantitative implementation. Macro alpha signals operate at mid-frequency, i.e., big changes occur over months, not days. As such, we do not think it is reasonable to expect a strategy to outperform equities at every rolling junction. Rather, we seek to engineer strategies that outperform over a full investment cycle. We define a full investment cycle as one where markets have experienced bull and bear markets with a generalized upward drift. With these characteristics explained, let’s turn to our levers.

Sector Selection

As we begin our process of adding alpha to the benchmark, we must start by understanding the benchmark. The S&P 500 (our chosen benchmark for US equities) is an index that tracks the performance of 500 of the largest publicly traded companies in the United States. For a stock to be included in the S&P 500, it must show positive profitability and maintain a sizable market capitalization. The constituents of the index itself are weighted by their outstanding market capitalization. The larger the market capitalization of a company, the greater the share it occupies. The dominant driver of market capitalization over time is price rather than shares outstanding. As such, the S&P 500 has a very large bias toward medium-term price momentum for the largest, profitable companies in the stock market.

Now, momentum in itself is not a bad thing, in fact it is a valuable tool in the toolkit for investor. However, it is just one factor which can be predictive of asset market performance. We think adding factors to this mix can add some modest edge to the S&P 500. Said differently, we think the first step to generating alpha is to make beta better.

Given our expertise is in macro, we leverage our systematic macro process to achieve this. Particularly, our macro process lends itself well to sector selection. At the index level, the most dominant driver of changes to the equity market are changes in growth expectations, which flow through to earnings expectations, which flow through to the index, and various sectors. We find that responsiveness to big growth-induced moves is fairly uniform in terms of their price impact on sectors. As such, only very modest incremental alpha is achieved by playing big moves like recessions, economic booms, etc., via sector tilts. However, we find that there is considerably more information available in the distribution of profits in the economy. Thus, for a given level of growth, we can search for the biggest winners or losers in the cross-section. For instance, during an investment boom, we would prefer technology equities as our primary long exposure. Alternatively, during an inflationary surge, we would prefer energy stocks. We can map these relationships for every sector. Effectively, we seek to align the portfolio with cross-sectional macro trends rather than just price trends. Accounting for such macro factors adds an additional layer of protection and return to a standard S&P 500 portfolio.

There are a wide variety of alternative implementations possible here, but we use macro implementations to stay with our primary expertise. The purpose of this approach is to add a modest amount of sector selection alpha to S&P 500 exposure. By itself, this is nothing to write home about, but when combined with our other levers, it can be quite powerful.

Beta Timing

Choosing sectors that look more attractive during a given macroeconomic backdrop offers us additional returns versus the index and better downside protection. While it may offer a better beta, it is still exposed to all the risks embedded in equity beta. The primary risk that all equities are exposed to is the risk of a persistent and pervasive economic contraction, i.e., a recession. Secondarily, equities are often at risk of more minor corrections when they have become rich versus bonds, commodities, and cash in a manner inconsistent with their fundamental economic drivers. Our systematic macro process consistently evaluates the probability of these outcomes to trade equities long and short— we call this beta timing.

Crucially, this process is mechanically and empirically uncorrelated to the underlying market and depends entirely on whether our systems can anticipate what’s likely to transpire. We can use these signals to achieve higher confidence in whether equity markets will likely outperform or underperform. We can take these quantitative estimates of over/underperformance to estimate potential returns and use them to lever up or scale down our equity exposure. When equities are cheap and in an economic expansion, these signals dial-up portfolio exposure. Conversely, when equities are expensive and the economy is at risk of a recession, this component may take equity exposure to zero or even enter a net-short position. We find that adding this layer of beta timing to our sector selection process is extremely accretive to total portfolio performance. If the drivers of the returns streams are adequately differentiated, the benefits of adding sector tilts in addition to beta timing can improve the gross portfolio Sharpe Ratio 1.5-2x.

Dynamic Risk Control

Thus far, we have largely discussed generating better signals, which primarily increase total returns. However, we cannot simply seek to generate returns without direct consideration of measures of risk. Equity markets are extremely episodic in their risk— their volatility profile remains stable for long periods only to shoot upwards during times of crisis. Significant and persistent drawdowns usually accompany these volatility spikes.

Now, while our signals may provide outsized returns during these periods of high volatility, they run the risk of running high leverage at locally elevated volatility levels. In the event that these bets are offside, as they will often be, we run the risk of significant losses. As such, we think capping the total amount of risk, regardless of the amount of signal generated, is a prudent decision to boost investors’ staying power in an investment strategy. From our experience, most investors look for conformable equity-like risks with drawdowns of approximately 20%. We can cap our risk-taking to avoid exceeding a pre-specified drawdown threshold like this one. The further we are from this drawdown threshold, the more unconstrained our portfolio risk-taking; the closer we get, the more we dial down risk. We want to take the most risk when we have the most signal, but we want to do that within reason. This dynamic process is different from traditional volatility targeting, which imposes a constant level of portfolio risk regardless of signal strength.

We find this dynamic version of risk-taking significantly additive to portfolio performance. While dynamic risk control doesn’t directly enhance returns, it mitigates drawdowns and facilitates better risk-adjusted returns. Overall, dynamic risk control allows us to press our edge when we feel strongly but tempers our bets so that we take risks consistent with investors' risk tolerance.

Strategy Overlays

Combining sector selection, beta timing, and dynamic risk control creates a return stream that consistently changes its gross exposure to equities. When there is a lot of signal, there is a lot of exposure. When there is little signal, the systems maintain very modest exposures. We cannot know how these signals will be distributed over the next few months or even years. Often, our signals may dial down their exposure, taking significantly less volatility than the S&P 500. Traditionally, this decrease in exposure would increase cash positions. However, we can further enhance portfolio returns by taking that cash and investing actively in bonds and commodities at an extremely low volatility. Maintaining a very low volatility for these exposures allows us to make sure we do not have excessive drift from the benchmark but can also reliably add returns above cash to the portfolio, further boosting the potential for long-term outperformance. We find these overlays to be extremely additive when our strategies have begun to reduce exposures, but equity markets may continue to power ahead. During these periods, the additional excess returns generated through these overlays help bolster the portfolio’s returns, allowing total returns to maintain pace with the benchmark without loading on the increasing risks embedded in the market.

Conclusions

Thus, while beating the equity market is a challenging and complex objective, we think it is attainable.

We believe an integrated approach to sector selection, beta timing, dynamic risk control, and active overlays can engineer a portfolio that durably and significantly outperforms the equity market over a full investing cycle.

We visualize the outcome of applying the principles we have described here in the readout below:

Coming soon for clients. Stay tuned.

Until next time.

Consistent with this idea, we present our Macro Mechanics, a series of notes that describe our mechanical understanding of how the economy and markets work. These mechanics form the principles that guide the construction of our systematic investment strategies. We hope sharing these provides a deeper understanding of our approach and ongoing macro conditions.

Subscribe now

Thus far in our Macro Mechanics series, we have provided our understanding of the following subjects:

• Growth

• Inflation

• Liquidity

• Integrating Growth, Inflation, & Liquidity

• What is Beta?

• What is Alpha?

• Where Do Recessions Come From?

• What’s Priced In? The Bridge Between Beta & Alpha

• What Drives Bond Markets?

• What Drives Stock Markets?

• What Drives Commodities?

• What Is A Market Regime?

If you are unfamiliar with our market approach, we highly recommend reading these previous notes. Today, we turn to a topical and often discussed subject: Stock Market Valuations. Market valuations are often discussed in financial media as a harbinger of things to come. Amongst market practitioners, their usefulness and quantification are frequently a polarizing subject. This polarization has been primarily driven by the underperformance of value-based approaches over the past few decades. This underperformance has led many investors to forgo all value-based measures in their investment process and some to look for alternative definitions of value. At Prometheus, we think valuations are an integral part of understanding expected equity market returns, which can provide significant insight for macro alpha generation.

Let us begin by defining equity valuations in the conventional wisdom. Equity valuations are a measure that reflects how much investors are willing to pay for stocks based on the expected future return the business can return to shareholders. This measure can be defined in an extremely wide variety of ways, usually in the form of price ratios— price to earnings, price to book, price to intangible investment, etc. While these measures are all modestly different, their core premise is the same— they seek to depict a relationship between price and the stock's underlying value. Often, these price ratio measures are compared against their history to understand whether equity markets are cheap or expensive. Essentially, these measures use the fundamental value of the business as an anchor for price and seek to predict stock prices based on whether stock markets are cheap or expensive. This was a successful approach for many decades, but in the modern investment era, this type of approach has been less successful.

At Prometheus, we approach valuations differently from most investors. We use valuations not to predict prices but to estimate the pace of shareholder yield. This distinction is simple but extremely powerful. For further clarity, we decompose equity market returns:

Stock Returns = Dividends + Buybacks + Price Appreciation

It is well documented that most of the variation in stock returns comes from price changes. However, it is less well documented that most of the trend in long-term returns for equities comes from dividends & buybacks, also called shareholder yield. In fact, the majority of long-term equity returns can be attributed to shareholder yields. Thus, we think a comprehensive approach to investing requires a significant focus on understanding the dominant drivers of shareholder yield. In particular, earnings yields are the dominant driver of shareholder yields.

This is because the ongoing pace of earnings relative to the equity price determines how much the stock can return relative to the cost of its shares. Said differently, a company's earnings yield potentiates its stock's prospective dividends and buybacks. The higher the earnings, the greater the potential for dividends and buybacks. Even if these earnings are not returned to shareholders directly and reinvested, they potentiate future dividends and buybacks. Thus, the higher the earnings yield on an equity, the better the expected outcome for an environment where the price does not change. This return type, generated independent of price movement, is often called carry. Thus, we believe valuations, in the form of earnings yields, are highly informative of the carry for holding equities.

All else being equal, we want to own assets with a high carry level and avoid assets with negative carry characteristics. Now, while it is clear that positive carry is a good thing and negative carry is not, it is less clear what carry levels are attractive. Like all macro assets, we think the value of carry is determined not just relative to the asset's history but relative to the carry of other assets like cash, bonds, and commodities.

Our systematic study of history has shown that a cross asset evaluation of the carry available in equities relative to other assets, offers a signficant edge over the traditional valuation approach. We think this gap exists due to the positives of the approach we have outlined, but also due to inherent flaws in how valuations are conventionally used. The most common use of valuations is to take various valuation ratios (price/earnings, price/book etc) for a given security, and compare today’s valautions to those seen over history. In this common approach, the higher the valuation versus the historical average, the more negative the outlook for the stock, with the expectation that valuations will mean-revert to historical averages. We belive that this method has several issues:

• Carry. While equities prices may be high relative to history, their earnings may well be positive, creating a stable undercurrent for dividends and buybacks, which in turn support total returns. Shorting or avoid an asset that has a positive carry is unlikely to yield positive outcomes.

• Momentum. One of the most persistent and pervasive phenomenon across markets and time is momentum. Macro cycles are self-reinforcing dynamics, and traditional valuation techniques by their construction find themselves reducing or shorting equities just as momentum rises. This effectively creates a bet against one of the most perisstent and pervasive phenomenon in all of investing.

• Mean reversion. Traditional valuation measures are largely suboptimal mean reversion bets. This suboptimal nature is due to the extremely large variance of stocks prices relative to their earnings, along with significantantly higher price appreciation of stocks over time relative to earnings. These varying charcateristics make tradtional valuation ratios a bet on mean reversion between a large and volatilie item (prices) and a small and stable item (book value, earnings, sales etc.). This makes the price component of the equation a very large overweight, essentially creating a counter-trend indicator. Mean reversion exists in every market, including equities, however, traditional valuation dynamics capture these poorly.

Reflecting these factors, our work has shown that the subtle shift from traditional valuation measures like price to earnings, price to sales etc relative to their history; to our preferred approach of estimating equity carry relative to other macro assets yields creates a much more effective lense for evaluating the relative attractviness of equities over time. We think this nuanced approach is an integral part of understanding one component of expected equity market returns, which can provide significant insight for macro alpha generation.Of course, there is a significant amount of work that needs to be done other than accounting for equity value when trading stocks, but this mechanical understanding forms an integral pillar of our understand.

If you want to see this understanding in action, we recommend checking out our systematic strategies, which invest based upon the codification of our Macro Mechanics. You can check out our ETF Portfolio:

Or our Asset Allocation program:

Until next time.

Consistent with this idea, we present our Macro Mechanics, a series of notes that describe our mechanical understanding of how the economy and markets work. These mechanics form the principles that guide the construction of our systematic investment strategies. We hope sharing these provides a deeper understanding of our approach and ongoing macro conditions.

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Thus far in our Macro Mechanics series, we have provided our understanding of the following subjects:

• Growth

• Inflation

• Liquidity

• Integrating Growth, Inflation, & Liquidity

• What is Beta?

• What is Alpha?

• Where Do Recessions Come From?

• What’s Priced In? The Bridge Between Beta & Alpha

• What Drives Bond Markets?

• What Drives Stock Markets?

• What Drives Commodities?

Our Macro Mechanics have dealt with markets in isolation thus far. Today, we describe how to view markets in unison through market regime probabilities. Market regime probabilities were the first tools we built to help navigate markets starting in 2020. As such, we have a significantly differentiated perspective on understanding and leveraging them as investors.

Before diving into trading markets, let’s define market regimes. As described in our Macro Mechanics notes, markets price in incremental changes in growth, inflation, and liquidity expectations over time. Said differently, growth, inflation, and liquidity are the principal drivers of asset markets. Importantly, these principle drivers largely operate cyclically, with self-reinforcing cycles upwards and downwards. These cycles drive significant, consistent, and parallel moves across macro markets. As such, macro markets often move in unison over long periods to reflect the most significant growth, inflation, and liquidity changes. Adding up these features into a single definition:

Market regimes are significant, consistent, and parallel movements of macro markets, which reflect the dominant impulses of growth, inflation, and liquidity.

At Prometheus, we think that a rigorous and consistent tracking of these regimes is extremely additive to traditional macro investing. This is because the true state of the macroeconomy is largely unobservable in real time. For all the macro data we use, we are just trying to achieve a high degree of probabilistic understanding of where we are in the economic cycle. To get the best probabilistic understanding of where we are today— we need as much new data as possible, and this is where the macro markets are invaluable. Macro assets offer a high-frequency look into what’s marginally occurring in the economy in terms of growth, inflation, and liquidity. Using quantitative techniques, we can use the information from the combined price action of these markets to estimate the probability of whether the economy is experiencing:

• Rising/Falling Growth

• Rising/Falling Inflation

• Rising/Falling Liquidity

Every regime has its hallmarks. For instance, if we expect equity markets to rise modestly, bond markets to fall significantly, and commodities markets to rally strongly— there is an increased likelihood that we are experiencing a rising inflationary growth environment. Alternatively, if we expect stocks and commodities to fall significantly but bonds to rally strongly, we will likely experience a falling growth environment. If assets rise versus cash and notes, outperform bonds, we are likely in a rising liquidity environment. There are many permutations and combinations of asset market performance, which are too exhaustive to list in this note. Still, the intuition is straightforward: we find more signal strength when a host of markets act like we are in a certain macro environment than if only one does.

Estimating today’s macro regime helps us add significant refinement to our economic nowcasting process and significantly improves overall portfolio performance. However, it is crucial to recognize that every regime probability, when used to guide investors, is an implicit forecast of the future. We cannot trade today’s regime, only tomorrow’s regime. This means that simply extrapolating today’s regime forward is inadequate, as it biases one towards trend following. Trend following is an excellent strategy for most investors to consider. However, excess bias toward trend-following can lead to large periods of mediocre performance as trend factors get crowded. Therefore, knowing today’s regime can be a part of a system’s signal generation— but it should not depend on it. Every position you take in markets is an effective bet on what the market regime will be tomorrow; you shouldn't bet it all on it just like yesterday.

We apply this nuanced understanding of market regimes to our systematic portfolio strategies. You can leverage them for your investment process using our ETF Portfolio, which has been systematically using this understanding since 2023:

Until next time.