Market & Economic Commentary

Tech fundamentals still favor Hardware over Software

While the Technology sector has been less dominant in terms of returns this year than it was last year, it remains the largest sector in the US market by value and the focus of much investor attention.

Our view within the Technology sector for some time now has been to favor hardware-related industries over software-related or services areas, and the latest update of both bottom-up and top-down indicators continues to support this view.

The table below shows some of the key bottom-up fundamental metrics we track for all sectors and industries, and focuses on the six US Technology sector industries (using the GICS industry classifications) within our broad 2300-stock US universe.

The revisions breadth measures shown in the table are based on the proportion of analysts covering each stock who have raised their earnings estimates over the last three months net of those who have lowered earnings estimates. That is, the number of upward revisions to estimates minus the number of downward revisions relative to the total number of analysts covering a stock. We use a weighted average of estimates for each company’s current fiscal year (2021 for most companies right now) and next year (2022) to calculate a consistent 12-month forward earnings figure.

Source: Mill Street Research, Factset

The first column shows the average breadth reading for all stocks in each industry on an equal-weighted (“EW”) basis, while the second column shows the same data on a cap-weighted (“CW”) basis. Naturally, the cap-weighted figures give much more weight to the largest stocks in each industry, while the equal-weighted figures will be relatively more tilted toward smaller names. All stocks in our US universe require a minimum market capitalization of $200 million and at least three analysts reporting estimates, among other criteria, so there are no micro-caps or stocks with very few analysts included.

A few key points jump out from the table:

  • Revisions remain net positive in most areas of Technology, in line with the broadly positive revisions activity in US stocks overall.
  • The average revisions breadth readings on a cap-weighted basis are higher in every industry than the equal-weighted readings, and often much higher. The sector-wide average of about 51% far exceeds the equal-weighted average of about 19%. This means the largest Tech stocks have much more positive analyst activity than the average stock in the sector, i.e., a big-cap bias.
  • The strongest industries are those which focus on hardware right now, while software and services industries are substantially weaker.

We see that on an equal-weighted basis, the Technology Hardware, Storage & Peripherals industry has the highest proportion of positive revisions, followed closely by Electronic Equipment, Instruments & Components and then Semiconductors & Semiconductor Equipment. All three of these hardware-related industries also have the highest revisions breadth on a cap-weighted basis.

At the bottom of the list we see the large Software industry, which has marginally negative net revisions breadth on an equal-weighted basis. This means the average Software stock has a roughly equal number of analysts raising versus lowering estimates. However, on a cap-weighted basis, the revisions figure is strongly positive. This means that a few mega-cap names in the industry have strong revisions, while the majority of mid- and smaller-cap names have relatively weak revisions.

A similar but less dramatic picture is seen in IT Services, where revisions are much lower than in the hardware related industries on both equal-weighted and cap-weighted metrics. The cap-weighted figure is still higher than the equal-weighted, as it is for all Tech industries, but by a much smaller margin than in Software.

The overall picture from the bottom-up, stock level analyst revisions data is that hardware makers continue to surprise analysts positively across large and smaller companies alike, while providers of software and tech-related services are much more mixed and dominated by the largest names in those areas.

The second chart below provides some macro, top-down context for the bottom-up fundamentals we see. The top section of the chart plots the year-on-year percent changes in aggregate spending on investment in computer hardware (blue line) and in software (red line) over the last 30 years. The data come from the quarterly GDP data produced by the US Bureau of Economic Analysis. As of the end of 2020, the growth rate of investment in computer hardware had jumped to 16%, the highest reading since the previous recessionary rebound in 2009-10. Growth in software investment spending, by contrast, had only grown 5%, which is near the lower end of its recent historical range.

Source: Mill Street Research, Bureau of Economic Analysis

The bottom section of the chart plots the ratio of software to hardware spending over time. We see that the line has tended to rise, indicating higher growth in software spending than hardware spending on average over the long run. But the latest readings show a drop, reflecting the jump back toward hardware spending that occurred last year and likely is still ongoing. In the longer-term, it seems likely that software spending will again resume its higher growth rate versus hardware, but the preference for hardware is still very visible in current analyst earnings forecast behavior and could last a while longer as the world continues to adapt to the post-COVID landscape.

Labor market improving but still shows plenty of slack

In the longer-run, a key measure of inflation pressure is the amount of labor market slack (unemployed or underemployed people), which heavily influences the ability of workers to demand higher wages.

The standard reported unemployment rate data (i.e., the U-3 measure in the US) is useful in measuring labor market slack, but has limitations due (in part) to its definitions of “unemployed” and the “labor force” in the calculation: “unemployed” people as a percentage of the “labor force”. That is, to be counted as “unemployed”, a working-age person must be considered actively looking for a job (when asked if they have sought employment in the last four weeks in the monthly household surveys done by the Bureau of Labor Statistics, BLS). If they are not currently seeking employment for any reason, they are “not in the labor force” and thus do not count in the standard unemployment rate, even if they consider themselves unemployed.

Another unemployment rate put out by the BLS, known as the U-6 measure, attempts to address this issue to some degree. The U-6 rate is much broader and includes anyone who has been looking for work within the previous 12 months but has been unable to find a job and has not looked for work in the past four weeks. It also includes anyone who has gone back to school, become disabled, and people who are underemployed or working part-time hours and want to work more. The first chart below plots the traditional U-3 rate and the broader U-6 rate since 1994. We can see that they typically follow a very similar pattern, but by construction the U-6 rate is always higher, and likely a more accurate description of slack in the labor market. What is more notable right now is that even after a dramatic recovery in employment from spring of last year (supported by historically large fiscal and monetary stimulus), the current U-6 unemployment rate of 10.7% is still higher than the worst reading of the 2001-02 recession, and far from the December 2019 low of 6.8%. By comparison, the current U-3 rate of 6.0% is likely understated (too optimistic) relative to the pre-COVID (Feb 2020) low of 3.5% due to measurement issues.

However, these metrics still rely on classifying people into various employment categories with somewhat arbitrary conditions.  An even broader and simpler measure of unemployment can help address these issues, and may be a better overall metric of labor market slack: the employment/population ratio (often abbreviated as “EPOP”) among “prime age” people aged 25-54 is simply the proportion of all persons in that age range who are employed, regardless of whether they are actively seeking a job.

The second chart below shows the total EPOP ratio over the last 50 years in the top section, and the bottom section shows the breakdown between male and female EPOP readings. Even after a sharp rebound from last year’s extreme lows and a very strong employment report last week, the overall reading of 76.8% is still far from the recent “full employment” levels in the 80-82% range in recent decades. Note that the true level of “full employment” is unknown and possibly higher than previous peaks in this ratio. This pattern can be seen in the data for both men and women, with men having a downward drift in EPOP over time while women joined the workforce up until about 2000 and have then remained in a range about 10 percentage points below that of men.

Because we are looking at people in the 25-54 age range, when adults are typically working, retirement and schooling should not have much impact on the ratios (as may be the case in the whole adult population). With a population of about 126 million in this age range in the US, the 4% difference in EPOP from current (76.8%) to previous peak levels (~80-81%) suggests five million or more people who are still unemployed potential prime-age workers. The average monthly gain in employment in this age group in 2016-2019 was about 86K/month, so even at an average of 100K jobs per month on a sustained basis it would take roughly four years to return to the previous peak. Further stimulus and a decisive suppression of COVID could accelerate that pace, but there is likely to be slack in the overall labor market for some time. This, in turn, suggests that labor cost-driven inflation is unlikely to accelerate on a sustained basis, beyond the short-term impacts from supply chain disruptions and re-opening.

Inflation is steady on the surface, volatile underneath

Inflation expectations have been a topic of growing interest thanks to the extraordinary fiscal and monetary support in place for much of the last year, most recently the huge $1.9 trillion American Rescue Plan that is currently sending checks out to millions of Americans.

All of this new spending by the federal government, along with the economic recovery permitted by the rollout of COVID-19 vaccines, is provoking more discussion about whether demand for goods and services will outpace the economy’s ability to produce them and push prices higher.

While we have previously discussed why we do not think inflation will be a major problem in the next few years, investors in the Treasury market appear to have raised their forecasts for future inflation, at least in the near-term. This is reflected in the “breakeven rate”, which is the difference between the yield on nominal Treasury bonds and that of the corresponding TIPS (Treasury Inflation Protected Security) bond. TIPS provide a “real” interest rate (currently negative) plus whatever the rate of inflation is over the bond’s duration. The difference between nominal and TIPS yields indicates the level of inflation that would produce the same return to holding either type of bond after accounting for inflation.

The chart below shows the breakeven rates for five-year and 10-year maturities, and we see that the five-year inflation expectations in particular have risen sharply recently, now back to levels around 2.5% seen after the last two recessions. The 10-year breakeven rate has risen less, as investors appear to expect a temporary jump in inflation that will subsequently ease. Both figures are roughly in line with the Fed’s stated inflation target, and thus are unlikely to provoke a tightening response at this point.

Breakevens 5yr 10yr_032521

Source: Mill Street Research, Bloomberg

Reported inflation, as measured by the Personal Consumption Expenditure (PCE) Price Index (the Fed’s preferred measure), has remained low thus far. Year-on-year comparisons will soon be skewed by the price drops around this time last year when the economy buckled under the weight of COVID and the associated limits on activity. Overall, however, there are thus far few signs of significant overall inflation in the reported data.

When we look under the surface of the inflation data, however, we find that there are a lot of significant changes going on among the various components, which are thus far mostly offsetting each other. This is not unusual around recessions, and certainly consistent with the extreme and unusual kind of shock that COVID-19 has caused in the economy.

The Federal Reserve Bank of San Francisco publishes metrics that capture the dispersion and amount of underlying change in the inflation rates of the various categories of goods and services measured in the PCE data. The charts below show the increased levels of “rotation” under the surface of the muted headline PCE inflation measures.

The first chart below shows the last 15 years of data on the PCE headline (total, dark blue line) and core (excluding food and energy, red line) inflation rates along with measures of the dispersion among the 100+ granular subcomponents of the PCE inflation data. It shows the inflation rate for the 90th and 10th percentile subcomponents of the PCE price index and below that the spread between the 90th and 10th percentiles as a measure of the cross-sectional dispersion or variation of inflation rates among products at any given time. We can see that dispersion in inflation rates among the categories of PCE components has widened significantly recently to 6-7%, up from readings closer to 4% for much of the last several years.

Also notable is the fact that even the subcomponents with the highest inflation rates (the 90th percentile, purple line) have price gains of only about 4%, marking a fairly modest upper bound on inflation pressures so far.

PCE Inflation and DispersionSource: Mill Street Research, Federal Reserve Bank of San Francisco

With some prices falling substantially, the current inflation spread (90th vs 10th percentile) is among the widest in the last decade, and it quantifies and corroborates the intuition that the supply and demand impacts of the COVID-driven recession and recovery have led to more divergent outcomes for different industries (some hurt badly, some benefiting strongly). The inflation spread widened even more dramatically around 2008, driven by enormous volatility at that time in energy prices in particular, and there was less direct fiscal stimulus support in that recession than the current one.  This analysis helps make the point that the gap between winners and losers seen in the stock market has a fundamental driver visible in the inflation data.

The final chart below plots another way of looking at the underlying divergences beneath the surface of the headline inflation data. The same San Francisco Fed data set also calculates the percentage of PCE price index subcomponents that have had large changes in their 12-month inflation rates relative to their previous five-year averages (“large” meaning two standard deviations from the five year average). Industries that have seen their inflation rates lurch upward would be captured in the blue line, showing the percentage of all PCE components with large upward movements in inflation, while those facing big downward changes would be captured in the red line.

Proportion of Big Changes in PricesSource: Mill Street Research, Federal Reserve Bank of San Francisco

The grey line below plots the sum of the two series to provide a measure of how many industries have seen major shifts in their respective inflation trends. Here we see that 25-30% of industries have recently had major shifts (up or down) in pricing power relative to their longer-term trends, much higher than the usual 5-15% readings for most of the last decade.

We also see that current readings are at similar levels to those seen around the 2008 recession, though with a slightly different pattern: in 2008, there was initially a spike in price increases, then a spike in price decreases, while this year has seen concurrent but less extreme spikes in both series as demand and supply had to simultaneously adapt to COVID’s impact on activity.

The implication is that some industries that may have had weak pricing power pre-COVID now have stronger price trends, while others that had higher industry-level inflation are now under more pricing pressure. While there are always a few such industries at any given time, there are many more right now.

These data help provide some further fundamental corroboration for the rotation in stock market industry trends and wide gaps between winners and losers, even in an environment of continued low headline inflation rates.

S&P 500 earnings have fully recovered, but with wide differences among sectors

The S&P 500 has reported another strong earnings season for Q4, with 79% of companies beating consensus earnings estimates for the quarter. This would be the third highest such reading in Factset’s data since 2008. The beat rate for top-line sales was similarly high at 77%. Aggregate income for the index is about 4% above year-ago levels, indicating that net income on a quarterly basis has fully recovered pre-COVID levels based on Factset’s data.

However, when we drill down into the earnings trends in the S&P 500 and its component sectors, we see the wide differentials in earnings patterns among sectors.

The charts below use quarterly index operating earnings per share as reported by S&P (S&P’s data differ slightly from Factset and other sources). The grey shaded areas are the current bottom-up consensus forecasts for the four quarters of this year.

S&P 500 Quarterly Sector EPS p1Source: Mill Street Research, S&P Dow Jones Indices

The top section of the first chart above shows us that the overall S&P 500 index is expected to see its quarterly EPS rise steadily over the next few quarters and see quarterly EPS exceed the previous peak of Q2 2019 by Q2 of this year, before reaching a new high of $47.06 by Q4 (which would be up 37% from Q4 2020).  The aggregate index figures, however, hide the variation among the 11 sectors that comprise it.

We see that Consumer Discretionary is expected to see earnings recover but not decisively exceed recent highs. Consumer Staples shows a choppy upward pattern, with Q4 expected to be slightly below Q3 of this year.

The Energy sector is expected to rebound from heavily negative earnings during 2020 to moderately positive EPS this year, but still well below the levels seen in 2018 and early 2019 (though if crude continues to rise, that could change).

Financials are expected to see earnings generally plateau around current levels, with no improvement in EPS from Q4 2020 levels, and still near levels seen in 2018-2019. Low net interest margins on lending have been a heavy headwind, partly offset by profits from stock and bond market activity and mortgage-related fees.

Health Care is expected to see a jump in earnings in Q1 of this year and then hold steady at new highs. As we will see, it is thus one of the few sectors where the consensus sees new highs in earnings occurring this year.

Turning to the second chart below with the remaining sectors, see that Industrials (as a classic cyclical sector) had a big drop in earnings in 2020 (with the Transportation component weighing heavily) but is expected to fully recover by the end of this year. Naturally, Industrials should be among the biggest beneficiaries of both fiscal stimulus and re-opening from COVID limitations.

S&P 500 Quarterly Sector EPS p2

Source: Mill Street Research, S&P Dow Jones Indices

The Technology sector, as one might guess, has been least affected by COVID and almost certainly got a boost in the second half of 2020 due to a surge in spending on IT as workers and companies scrambled to work remotely wherever possible. Consensus calls for earnings to continue growing and reach new further new highs this year.

The Materials sector is seeing a big rebound in earnings from a decline that began well before COVID hit when commodity prices and global growth were already relatively weak. Analysts expect the sector’s earnings to hit a near-term peak in Q2 of this year (matching the 2018 peak) before easing by year-end.

Communication Services has been under earnings pressure for some time, as a mix of some big Tech-related firms along with Telecom, Entertainment and Media firms. Earnings are expected to rise steadily from the current (Q4 2020) lows through the end of this year.

Earnings for the Utilities sector look to remain in a range, with no discernible growth trend visible. Demand for electricity, natural gas, and other utilities has seen little overall growth for years, and regulations in many areas keep revenues and profits relatively stable.

Finally, the Real Estate sector (principally REITs), has seen earnings hit hard by COVID, and the consensus is for only very modest recovery this year as demand for commercial real estate is likely to remain depressed.

Overall, it appears that only the Growth-oriented sectors of Technology and Health Care will see earnings reach true new all-time highs this year. Other sectors may approach or just exceed 2019 levels, while a few have further to go. While fiscal stimulus and re-opening should provide a tailwind for earnings in many sectors, those winds are not blowing at the same speed for all.

Reviewing current stock vs bond sentiment

Despite what you might hear or read some places, investor surveys do not show an extreme level of optimism toward US stocks. Bullishness on stocks has in fact declined somewhat recently and is not far from long-term average readings.

Sentiment toward bonds, by contrast, has moved quite sharply and is now approaching extreme bearishness by the standards of recent years. This is not too surprising, given that long-term Treasury bond yields have recently risen to their highest levels since COVID hit early last year. The result has been that investors in long-term (20+ year) Treasury bonds have lost about 13% since the end of November and about 18% since the end of July.

One of our key measures of survey sentiment for equities is shown in the top section of the chart below. It is an average of several sources, each of which monitors the proportion of market commentators who are bullish or bearish on equities. They include Investors Intelligence, Market Vane, and Consensus Inc.Stock vs Bond Sentiment

Source: Mill Street Research, Investors Intelligence, Market Vane, Consensus Inc.

The average proportion of bulls on stocks right now is about 60%, down from a recent peak in January of 67%.  The average proportion over the last five years has been just over 57%, so the current reading is only slightly above average. The peak in the last five years (and in fact since at least 2003) was at 76% back in January 2018 (when the corporate tax cuts were going into effect), while the lowest point in the last five years was the brief reading around 33% in late March of last year amid the worst of the COVID-related panic. Readings below 50% on this metric are relatively rare outside of panic periods.

These survey readings stand in contrast to other sentiment-related indicators like put/call volume ratios, certain valuation metrics, or anecdotal “indicators” like the popularity of SPACs or the extreme behavior of “meme stocks” with heavy retail trading activity. Other market-based measures of risk appetite (e.g. relative performance of riskier stocks) suggest investors are still broadly in a “risk on” mood.

Sentiment readings that are not extreme in either direction tend to give less information about future returns. But we can certainly see that stocks have often done well when sentiment has been near current levels, as sentiment has been around these levels since August . Extreme bearishness tends to be the strongest signal for stocks, but occurs relatively rarely given the long-term uptrend in US stock prices.

The negative sentiment toward bonds suggests that the recent rise in bond yields may be getting somewhat stretched. If investors continue to assume that the Fed is not changing its current policy guidance and will keep short-term rates near zero for at least the next year or two, then long-term yields may not have too much further to rise.

Taking the next step, if equity investors are growing more concerned recently about risks that higher bond yields may cause regarding the level of stock prices (i.e., a higher discount rate reduces the present value of future earnings), then sentiment toward bonds is worth watching as part of the broader picture facing equities.

Bond market making some noise

The bond market has clearly awoken from what appeared to be a low-volatility Fed-induced slumber for much of last year. Longer-term bond yields in the US and elsewhere have jumped to their highest levels since just before the COVID crisis hit markets early last year (blue line in first chart below). Even after this rise, though, the 10-year Treasury yield remains below even the low points of previous cycles.

Short-term rates (0 to 2 year), meanwhile, have remained anchored near zero due to the Fed’s continued indications that any policy rate hikes are still at least two years away.

US Treasury Yields

There are two main components to Treasury yields (which do not have default risk): real yields (yield after subtracting expected inflation) and inflation expectations. The first component to move was inflation expectations (first chart below), and more recently real yields (second chart below) have also risen notably. However, real yields remain solidly negative and much lower than they were before COVID-19 hit last year.

Breakevens 5yr 10yr

Treasury 10-yr Real Yield

What have been the drivers of the recent move higher in long-term bond yields?

Some of the most prominent reasons include:

  • Additional fiscal stimulus is expected soon, which will potentially boost inflation and growth, and also require the issuance of a large amount of new Treasury bonds.
  • The economy’s recovery from COVID-related weakness is continuing thanks to ongoing vaccinations, which will combine with stimulus to push growth much higher than average this year.
  • Sharply higher prices for oil and other key commodities (copper, lumber, etc.) are raising concerns about inflation already in the pipeline, with further demand potentially driving prices even higher.
  • Selling or hedging activity by investors who trade leveraged positions in bonds, and/or own mortgage-backed securities that now appear riskier. Rising mortgage rates typically reduce pre-payments (due to less housing turnover) and refinancing of home mortgages, which increases the duration, and thus risk, of mortgage-backed bonds.

The jump in market-implied inflation expectations has been quite sharp, though something similar happened after the 2008 crisis period as well. The current inflation expectations reflected in 5-year and 10-year Treasuries (difference between nominal Treasury yields and inflation-protected TIPS yields) are now slightly above the Fed’s 2% inflation target. Indeed the 5-year implied inflation rate (breakeven rate) is at its highest level since 2013, and the 10-year rate touched its highest since 2014. Investors now appear to expect a rebound in inflation, which is likely not considered a problem by the Fed (given their stated inflation goals) as long as expectations do not become excessive. However, the Fed’s own buying of TIPS in the past year may itself have skewed the interpretation of “market expectations”: the Fed now owns well over 20% of the entire TIPS market, potentially influencing their prices (yields) more than usual.

For stock prices, a moderate amount of inflation is not necessarily a bad thing for corporate earnings, as long as it does not provoke Fed tightening. Since equities (via corporate profits) are partly hedged against inflation, real yields are often viewed as the more important rate. Thus the recent rebound in real bond yields has raised concerns about equities losing the tailwind they have had from falling real yields for more than two years. It has also provoked a shift in investor interest from Growth stocks that are attractive when economic growth and inflation are low toward Value (and other riskier) stocks that tend to do better when economic activity and inflation are accelerating.

With short-term yields still pinned near zero by the Fed, the yield curve has steepened sharply recently. This is notionally good for Value-oriented banks and other “spread lenders” (who borrow at short-term rates and lend at long-term rates), though many other factors can affect the profitability of lending, and higher rates can dampen loan demand.

And one of the biggest impacts of higher long-term yields is in fact on mortgage rates and thus the housing market. Housing has been an extremely hot area recently, as demand for single-family homes is very high and supply has been unusually low. The average 30-year mortgage rate recently hit an all-time low of about 2.8% but has now jumped back up to 3.14% in just the last two weeks (and will likely rise somewhat further near-term). While this is still very low by historical standards and may not hamper housing too much, at the margin it may cool demand, and any further increases would put additional pressure on housing demand.

Overall, a moderate rise in long-term yields with well-anchored short-term rates is not necessarily a major cause for concern for stocks, or the economy, in general. It does however mean potentially more rotation among sectors and styles within equities. It will also bring up concerns about whether or when the Fed will decide to alter its current policy trajectory in response, as too much of a rise in yields could cause economic dislocations that the Fed would prefer to avoid.

Recent rally in “junk stocks” is not unusual

Financial headlines have been captivated recently by explosive behavior in certain “meme stocks” that have been the subject of intense speculation by online retail traders as well as some hedge funds. This has been accompanied by a general trend of outperformance by smaller, money-losing, heavily-shorted, and volatile stocks (sometimes referred to as “junk stocks”, similar to risky high-yield “junk bonds”).

Other signs of “froth” include aggressive use of SPACs (Special Purpose Acquisition Company, or “blank check” company that raises money to acquire private companies), historically high trading volumes and activity in short-term call options, and growing margin debt.

This has raised broader questions about why “junk stocks” seem to be rallying much more than “quality stocks” and whether this is historically unusual.

The short answer is: no, this is not historically unusual under these circumstances. The specifics vary, but similar patterns have been seen in the past when markets are recovering from a sharp decline and policy support is very aggressive.

The first chart below plots the recent (past year) returns of the Dow Jones Thematic Market-Neutral Style indices. These are hypothetical long-short indices (i.e., assuming equal dollars invested in offsetting long and short portfolios) based on widely-used factors, using the 1000 largest US stocks, and constructed sector-neutral.

The key points are:

  • Quality and Anti-Beta (low beta) are highly correlated, since quality stocks (defined by Dow Jones as those with high Return on Equity and low Debt/Equity ratios) also tend to be lower beta. Size (small-caps) is often negatively correlated with Quality and Anti-Beta (since small-caps are generally lower quality and higher beta). Risk is the key theme connecting these factors.
  • November 6th (where shaded area begins) is when Pfizer announced its first COVID-19 vaccine results.  This marked the point at which the recent themes really began: outperformance by low-quality, high-beta, small-cap stocks. This initially hurt the price momentum factor since those had not been the leadership areas previously.
  • The Value factor had a bounce in November, but since then has shown no net performance. Thus it is not Value that has been rewarded, but risk, in the period since November 6th.
  • It is also not coincidental that early November was when the US election occurred, and the results (fully decided in January) increased the perceived odds of additional aggressive fiscal stimulus. Such stimulus tends to benefit smaller, weaker (riskier) companies that had been hit hardest by COVID-19.
  • Thus riskier companies have had recent tailwinds from both COVID-19 developments and greater fiscal support.

Dow Jones Thematic Style Indices All

The long-term chart below shows the Quality and Anti-Beta factors since the data begin in 2001. We can see the correlation is clear over the longer-term, including the most recent few months.

Dow Jones Thematic Style Indices Quality AntiBeta

The key point here is that in each of the previous periods of post-recessionary aggressive stimulus (2002-03, 2009-13), higher risk (lower quality) stocks were rewarded as investors sought the biggest “bang for the buck” from the stimulus and recovery. Weaker, riskier stocks tend to get the most benefit from policy support, while stable, higher quality companies do not need it and get relatively less benefit. Thus the current conditions are not unusual, and fully consistent with a risk-on environment, in line with our other indicators that remain bullish for equities on a tactical basis.

Semis vs Software trade now favors Semis

Within the broad Technology sector, there are often significant divergences among the various industries. A key intra-sector industry relationship that many investors use as a touchstone is the relative performance of Semiconductors versus Software.

These two industries capture different parts of the Technology ecosystem. Due to their widespread use in so many devices and products, the Semiconductors and Semiconductor Equipment industry reflects demand for hardware, both within Technology (servers, PCs, phones) and in other sectors (e.g. autos), and thus tends to be much more cyclical. Software tends to be much more stable, with more recurring revenue, and nowadays is closer to a service-type industry. There is much less chance of major “shortages” or “oversupply” of software of the kind that semiconductor makers must often deal with.

So even though software and semiconductors are complementary products (each requires the other), it is not hard to see that they can often have significantly different fundamentals and relative returns on an intermediate-term basis.

Our indicators currently show a growing shift in favor of Semiconductors over Software, both in fundamental earnings trends and relative returns. This is a reversal of the trend seen in the 2017-2019 period, when Semis lagged Software, and much of 2020 when relative performance was mixed.

The chart below shows the strong relationship between relative earnings estimate revisions activity in the two industries and their relative returns. The data are drawn from our broad US stock universe of about 2300 stocks (roughly, all US stocks with at least $200 million market cap and three analysts reporting estimates), and the constituents of each industry are equal-weighted in both the revisions and return series. The return series uses a five-day moving average to show the trends more clearly. Earnings estimate revisions breadth measures the average net proportion of analysts raising versus lowering estimates for each stock. Readings above zero mean more analysts raising estimates than lowering them on average.

US Semiconductors vs Software Revisions and Returns

We see that Semiconductor revisions breadth began losing its relative strength versus Software back in 2017, and continued through early 2019. At that point, Semiconductor revisions started to recover while Software continued a slow deterioration, allowing the relative revisions spread (middle section) to turn up from very negative (i.e., pro-Software) readings. That spread turned positive (favoring Semiconductors) in early 2020, just before COVID-19 hit, and then weakened again as many industries weakened simultaneously in the spring.  Both industries then had a simultaneous sharp rebound, along with most of the rest of the market, through the fall.

The last few months are where we again see a distinct divergence. Software revisions have clearly been losing momentum since September while those of Semis have held up and actually grown somewhat stronger. The spread is now quite wide and at multi-year highs in favor of Semis.

The bottom section of the chart shows the relative returns of the two industries, and we see the clear tendency for relative returns to follow the relative revisions. The relative return series has recently broken out of the range it inhabited for most of 2020, and looks set to follow the relative revisions higher. This suggests that Semiconductors should continue to outperform Software as long as the relative earnings indicators maintain their recent clear bias toward Semis.

US earnings estimate revisions trends remain strong amid Q4 earnings season

While certain heavily shorted stocks are getting much of the attention lately due to retail-driven price surges, the bigger picture news is Q4 earnings reports and analyst behavior.

We track earnings estimates for a broad universe of about 2300 US stocks (market cap of $200 million and up) and construct estimate revisions indicators using two key metrics: breadth and magnitude. Breadth is the net proportion of analysts raising versus lowering estimates for a stock, which is -100% if all analysts are cutting their earnings estimates and +100% if all are raising estimates (0 indicates a balance between positive and negative revisions, or no activity at all). We look at this proportion based on revisions that occurred over the last 100 calendar days (about one quarterly reporting cycle).

Magnitude is the size of the changes, measured as the percent change in consensus mean earnings (EPS) estimates over the past month. It will thus be more sensitive but also more volatile.

The first chart below shows the average daily readings of those two indicators for all US stocks. The red line is the average revisions breadth and the blue bars are the average revisions magnitude. We can see that revisions breadth is holding at very high levels (the long-run average is actually slightly negative because analysts tend to start off with high estimates and trim them as time goes on). This means that a solid majority of stocks have more analysts raising than cutting their estimates for earnings over the next 12 months, and this has been the case consistently since July.

United States_AbsERS_Daily_20210126

The blue bars are now starting to rise again, and we can clearly see the quarterly reporting cycle in the data. The earnings season for Q2 2020 earnings that started last July provoked a big upswing in revisions magnitudes (due to a high proportion of earnings reports beating consensus estimates), and then the reports for Q3 2020 earnings three months later also provoked a similar jump in estimates.

Right now, we see what looks like a third consecutive acceleration in estimate revisions developing as Q4 2020 earnings are now being reported, and are mostly coming in better than consensus expectations. So even after months of analysts raising estimates, they are still being surprised positively by the actual earnings reports.

Where are revisions strongest? The table below shows the average revisions breadth readings for the 11 GICS sectors in the US (using the same broad universe of stocks). We see that Financials is at the top, with a very high reading of over 50%. While Financials have had strong revisions for a while now, the latest jump is likely because Financials are among the first to report earnings in a given quarter and most have reported positive surprises so far: 30 of the 34 Financials in the S&P 500 which have reported so far have beaten consensus estimates for Q4. Analysts often then respond to “earnings beats” by raising estimates for future quarters.

US Sector Abs Rev Breadth tableBeyond Financials, it is still mostly cyclical areas that have the strongest revisions activity, including Industrials, Consumer Discretionary, Technology, and Materials. And while all sectors have net positive revisions breadth, the weakest by a considerable margin are Real Estate, Utilities, and Health Care.

So the message from analysts continues to be strongly favorable for future earnings expectations, even after two consecutive quarters when earnings beat expectations substantially. The macro influences of fiscal and monetary policy on corporate earnings are now well established and likely being embedded in analyst forecasts. This is clear from the relative strength in the cyclical sector revisions indicators.

While equity markets have jumped sharply over the last three months and potentially priced in a lot of good news, the positive trend in earnings estimates from analysts that has supported equity prices thus far looks to be intact for now.

Still a risk-on environment, but option traders remain nervous

Markets globally continue to show strong risk-seeking behavior, a continuation of the broader trend in place for much of the time since late March 2020. That was the point at which monetary and fiscal policy activity surged to produce enormous stimulus in the US and globally.

Recent US legislation that included a total of about $900 billion in new fiscal support is now starting to be felt, and recent political developments have increased the odds of further fiscal support this year. Alongside this persistent fiscal support to counteract the severe economic impacts of COVID-19, monetary policy remains extremely accommodative. Near-zero policy rates and heavy bond buying programs are expected to be maintained for many months if not years, putting both monetary and fiscal policy firmly in the “highly stimulative” category at the same time.

This backdrop has allowed the strong demand for risky assets to continue, as reflected in many measure of market prices. Our chart below shows four such measures:Global Risk Appetite Measures

Top section: The MSCI All-Country World Index (ACWI) is a broad global equity index, and it has been outperforming the total returns generated by the ICE/BofA Merrill Lynch (ML) 10+ Year Treasury Index (measuring returns to Treasury bonds with maturities of 10 years or more). This stock/bond relative return series has recently moved above its pre-COVID peak as bond returns have been weak and stock returns have been very strong.

Second section: Here we plot our own custom index of global high volatility stocks (top decile of global stocks above USD$200 million market cap, ranked by trailing two-year historical return volatility). This index of risky stocks is a useful measure of investor risk appetite. It has posted powerful gains since the March low in equity prices, and continues to make new highs.

Third section: This shows the relative returns of the S&P 500 High Beta index versus the S&P 500 Low Volatility index. The High Beta index reflects the 100 stocks in the S&P 500 with the highest market beta (sensitivity to stock market movements) and is a measure of high-risk stock activity among US large-cap stocks. The Low Volatility index captures the 100 stocks in the S&P 500 with the lowest historical return volatility (both indices are rebalanced quarterly). Their relative return is another measure of risk appetite among investors based on the relative riskiness of stocks within the major US benchmark index. It has been rising sharply again after a pause over the summer and is also making new cycle highs.

Fourth section: Turning to debt markets, this plots the average credit spread on high yield (junk) bonds in the US. The credit spread measures the additional yield investors require over and above the yield on a US Treasury bond of the same maturity to hold the debt of a high-risk borrower (i.e., companies with weaker financial conditions and thus higher default risk). That spread surged in the immediate aftermath of the COVID crisis in March/April of last year, and then has been steadily declining thanks to the Fed’s aggressive support of the corporate bond market. Recently it has continued to make new lows (reflecting greater risk appetite among investors), and is now back to pre-COVID levels despite the ongoing economic turbulence.

So we can confidently say that investors are content to take on greater risk than usual with the expectation that government support for markets and the economy will continue. We also note that the volatility of stock prices recently has dropped back down to very low levels, another condition typically found when risk appetite is high and a bullish trend is well established.

Under these conditions, we would normally expect options traders to react to the low market volatility and favorable backdrop by reducing their expectations of short-term future volatility. This would typically be visible in the CBOE VIX index, which measures the expected level of market volatility over the next month embedded in S&P 500 index options prices.

But right now, we see that the VIX has held at relatively high readings, and allowed a wide gap to open up between implied future volatility and recent realized volatility. We can see in the chart below that normally the VIX and realized volatility move together and are closer than they are now.VIX vs Realized Vol

It appears that options traders do not expect the current stability in equity markets to continue, and are pricing in a significant rebound in volatility (which is typically associated with falling stock prices). Our analysis indicates that this tends to be a favorable contrarian sentiment indicator: when options traders are especially nervous about rising volatility (relative to actual volatility), it suggests that some investors remain unconvinced and underinvested, which can support further near-term gains.

So while some measures of market sentiment are clearly pointing to high optimism among investors (a worrisome sign from a contrarian sentiment standpoint), the VIX is currently providing a supportive sentiment reading in our view. With the market’s trend still strong and the policy backdrop supportive, risk assets could continue to rise at least a little while longer.