On April 15, the SP500 and the Nasdaq Composite Index moved to new all-time highs, and added to those records on April 16.  The NYSE's A-D Line is still 1018 net advances away from equaling its own all-time high.

Some might see it as a bearish divergence to have the SP500 make a new all-time high while the A-D Line has not yet confirmed.  I do not see it that way, in part because the NYSE Composite Index is still 2.4% away from its own all-time high.  So in that sense, the A-D Line is actually doing better than prices.  It is just that the SP500 is doing even better than that.

And it is further worth noting that the NYSE breadth data have been averaging 738 net advances in the two weeks since the March 30 price low.  It is really hard to criticize that as being not strong enough.  It is a very steep rise in the A-D Line, which conveys the statement that liquidity is plentiful.

Divergences between the A-D Line and prices are a big deal for me.  And I should emphasize that bearish divergences are much more valid and important than bullish ones.  Sometimes the A-D Line can lag just a bit at turning up from an oversold bottom.

The fun thing about the A-D Line is that every stock gets an equal vote.  Some see this as a flaw, asserting that tiny little companies which do not matter much should not get the same vote as big stocks which drive the cap-weighted indices.  But this supposed flaw is actually a strength.

When liquidity starts to dry up, it hits the most vulnerable stocks first.  So if one looks only at the healthiest of stocks, one can miss the message that liquidity is starting to be a problem.  This is why I do not pay much attention to the A-D Line for the stocks which make up the SP500.  Those stocks are all on the varsity team, and they are not as vulnerable to liquidity problems as the more marginal companies' stocks.

I have also found that the NYSE's A-D Line works better at giving these messages than other A-D data.  The Nasdaq's A-D Line, for example, has a profound bearish bias, and always has.  It has never made a new high in its entire history.  It started going downward from the beginning of the data in 1972, and has kept going down.  This is because the Nasdaq exchange has looser listing standards, and so a company that is going to IPO then go broke is more likely to do that on the Nasdaq.  And every day it spends declining from its IPO price to zero will contribute to the Declines column.

I also find that the daily A-D Line for high yield corporate bonds can serve as an excellent indication of liquidity problems, or lack of problems.  Those corporate bonds are marginal investments, and they draw from the same pool of liquidity that the stock market does.  So when the HY A-D Line starts diverging, it is a great warning of trouble.  Right now, there is no sign of that trouble from that indicator.

I feature the NYSE's A-D Line in every issue of our twice monthly McClellan Market Report.  And I show the HY Bond A-D Line periodically there and in my Daily Edition when it has something useful to say.  If it as been a while since you were a subscriber, or if you are curious about learning more, check out our web site, www.mcoscillator.com.

Several analysts I respect have noted that the price structure in 2026 is looking a lot like that of 2025.  This week's chart highlights that point, but I had to do a little bit of tweaking to get the best pattern fit. 

Whenever I employ price pattern analogs, I strive to find the best overall fit of even the minor price wiggles.  That helps to validate (or not) that I have a good pattern comparison.  To get the best fit in comparing 2026 to 2025, I had to do a little bit of time shifting, so that there is not a perfect calendar alignment.  Doing this better aligns the lesser movements in the left hand of the chart.  The plots are shifted 15 trading days apart from a strict calendar alignment in order to get the better pattern match.

To help illustrate this point, here is the same chart with the two plots arrayed with a strict calendar year alignment in the chart:
We can still see a general similarity of the chart structures, but not as tight of a match of the smaller dance steps. 

I prefer to use a comparison with the best alignment of structures that I can get, even if that goes against strictly following calendar seasonality.  The presumption of analyzing any chart structure is that price structures are a manifestation of the unfolding of human emotions as they get applied to price movements.  Similar emotional scenarios result in similar price structures, or so goes the theory.  There is no perfect way to test that hypothesis. 

Anyone employing chart pattern analogs should also be aware that all of them will eventually break correlation.  In my experience, the moment when they break correlation is usually the moment when one is counting on the relationship most to continue working.  So I never give them my full confidence because of that inherent fickleness. 

Turning our attention back to the top chart, if the current year's pattern continues to match that of 2025, then we can expect a nice uptrend lasting through the summer of 2026.  One problem with that expectation is that the stock market typically moves sideways to lower from May to October, and especially in the second year of a presidential term.  So we will have to see which factor is stronger, i.e. the feeling of relief after the Iran War cease fire matching the relief after the April 2025 tariff crash, or the normal seasonal tendencies.  For the moment, the market is still matching the 2025 time-shifted pattern, and we are still in the bullish phase of normal annual seasonality.  The conflict does not arrive until May gets here.

When my parents wrote Patterns For Profit in 1970 to introduce the McClellan Oscillator and Summation Index to the world, they emphasized the point that the patterns in the structure of the indicators mattered more than the numerical levels.  One of the patterns that they highlighted was seeing a 3rd bottom in the Oscillator, higher than the prior two.  We just had one of these, conveying a big bullish message for the stock market.

The McClellan Oscillator measures acceleration in the Advance-Decline data.  Negative readings mean that there has been downward acceleration.  The observation that there are subsequent higher negative readings after the lowest one means that the downward acceleration is slowing.  That is a precursor to a change of price trend.  That is the setup, but not a signal by itself.

The confirmation this time came first with the Oscillator breaking its own declining tops line.  Then more confirmation came with the Oscillator going up above the zero line, signaling a switch to upward acceleration.  That does not necessarily mean upward movement for the A-D Line, since a change from downward to sideways constitutes upward acceleration in physics terms. 

The Oscillator can next give us additional confirmation of a bullish change by zooming up to a really high positive reading.  Very low negative readings are usually conclusive in their nature.  But a very high positive reading is a sign of strong initiation of an uptrend.  We have not yet gotten that piece of confirmation.  It will be something to look for in the days ahead.

We feature a chart of the McClellan Oscillator in every issue of our twice monthly McClellan Market Report, and frequently in our Daily Edition.  You can see a copy of the chart above every day at the "Breadth Data" page at our web site.  And you can read more free articles about the McClellan Oscillator here: https://www.mcoscillator.com/learning_center/kb/mcclellan_oscillator/

There is a fun magic trick which the McClellan Summation Index does when it crosses through its neutral level, which is the topic of this week's chart.  The moment of crossing down through neutral tends to mark at least a temporary bottom for the price decline which brought about that crossing.  This also happens crossing back up through zero to mark tops, but to a lesser extent.

The Summation Index chart shown above is the "classic" version, first created by my parents Sherman and Marian McClellan back in 1969.  It is different from the Ratio-Adjusted Summation Index (RASI) which we use for some other applications in that first, it does not adjust for the changing numbers of issues traded like the RASI does.

The classic version is also different in that its neutral level is at +1000, and there is a brief story about this.  When my parents first introduced the McClellan Oscillator and McClellan Summation Index to the world, there were no computers outside of large universities and the Pentagon.  So anyone wanting to use these tools had to do all of the math by hand.  The Summation Index changes each day by the value of the McClellan Oscillator, and some users would get confused about having to "add" a negative Oscillator reading to a negative Summation Index value.  So to help avoid this computational confusion, they artificially boosted the neutral level to +1000.  At that time in the early 1970s, the Summation Index had a total amplitude from highs to lows of only about 2000 points, so boosting the neutral level to +1000 meant that it would be very rare (and thus special) to see a negative Summation Index reading.

We thankfully have computers now to do our calculations for us, and the computers are not bothered nor confused by arithmetic operations.  But we have kept the +1000 neutral level for the classic version of the Summation Index out of custom, and also to prevent confusion for anyone who has been using it for years.  In reality, we could have the neutral level be any number we want and it would not make any difference.  But the principle of there being a neutral level is important for this week's lesson.

Crossing down through zero offers us this fun magic trick of marking a bottom for prices.  It may not be a permanent bottom, but it is a noticeable one.  This is not new; it has been working this way for decades, and it is just one of the special features of the Summation Index, and also of the McClellan Price Oscillator for price-based indices.  In fact, the Summation Index is mathematically like a Price Oscillator for the daily A-D Line.  The Price Oscillator is calculated as the difference between a 10% Trend and a 5% Trend of closing prices.  The Summation Index is calculated by summing McClellan Oscillator values, but it also can be arrived at by finding the difference between a 10% Trend and 5% Trend of daily A-D Line values.

This magic trick of marking price bottoms when crossing down through neutral is similar to the topic of a "rainbow convergence" of moving averages that I have written about before.  See the prior article linked below.  I cannot explain why this magic trick works, but it is a phenomenon with enough history to demonstrate that it does work even if one cannot explain it.

I wrote here in February about how the Investors Intelligence bull-bear spread had gone to an extremely high level.  It has since come back down again, as the war with Iran has stock market analysts rethinking their optimism.

The Investors Intelligence survey of investment advisors and newsletter writers (including me) comes out every week.  Like most sentiment surveys, it responds to what prices are doing.  There is nothing like an uptrend to get people excited, and selloffs tend to make people turn bearish.  That is not true for all survey respondents, obviously, and some of us work to trade against what the crowd is doing. 

The remarkable point about the Investors Intelligence survey data is just how precisely it matches the price action, most of the time.  The chart above shows the SP500 on a detrended plot, meaning it is a comparison of where the index value is versus its 200-day simple moving average.  Making this simple adjustment results in both plots staying close together most of the time.

Occasionally, though, the sentiment data overshoot what prices have done.  I call that a manifestation of "pure" sentiment as opposed to price-induced sentiment.  When we see these sentiment overshoots, the message is that the crowd has gone too far in either its enthusiasm or its pessimism, and the stock market usually responds by moving away from that overshoot.  That movement tends to continue until sentiment oversteers to get back in step with what prices are doing, and we have seen that happen just now. 

Three weeks ago, the bull-bear spread was at +40.8 percentage points.  The latest data show that it is down to +18.5, which is a really big reappraisal of the market's prospects.  A war breaking out can do that.  When sentiment lurches like this, it is usually a great opportunity to bet against the crowd.

On a separate note, I recently did an interview with Lars Von Thienen of the Foundation for the Study of Cycles, https://cycles.org.  We discussed the sunspot cycle and its impacts on the financial markets, a topic I addressed here back on Feb. 26, 2026.  You can find a link for that 46-minute interview at our Home page, https://www.mcoscillator.com/.

The war against Iran has pulled down the major US indices, and it has hit some overseas markets even harder.  One encouraging sign, though, is that there is no bearish divergence apparent yet between EEM and the SP500.

EEM is the "emerging markets" ETF sponsored by iShares.  It supposedly invests in stocks in new markets that are just getting going, although its two largest holdings are Taiwan Semiconductor (TSMC) and Samsumg.  One could argue that both Taiwan and South Korea are already past the "emerging" stage.  TSMC alone accounts for a 13% weighting in the fund.

What I find interesting about EEM is that it pretty reliably shows us a bearish divergence versus the SP500 at important price tops.  It is not showing us one right now.  The chart above shows us that there were big divergences at each of what I would call the major price tops of the last 5 years.  And that includes just before the 2020 Covid Crash at the left end of the chart. 

Divergences are important, although one big problem is that they can persist for a long time before they finally decide to matter.  A divergence is "a condition, not a signal".  It will not tell us when it is going to matter.  And divergences can sometimes get "rehabilitated".  That is possible.

EEM shows divergences, much like the NYSE A-D Line does, when liquidity starts to get tight.  Emerging markets stocks are arguably of lower quality than the big "blue chip" stocks which make up the major averages.  If there is plenty of money to go around, then even the less deserving ones can get some.  When liquidity starts to dry up, the weak get hurt first.

We do not have a divergence now, and that is perhaps even more important of a message than if we did have a divergence.  The lack of a divergence carries the message that the recent price top is likely not the end point for the uptrend.  There can be stumbles along the way, and the start of a war which shuts down shipping from the Persian Gulf is arguably a big reason for a stumble.  But the message is that liquidity was strong going into that event, and so prices will likely recover.  Whether the EEM can recover to a new high remains to be seen, and so we could be seeing the commencement of building a divergence but we do not have it yet.

The shutdown of shipping through the Strait of Hormuz into the Persian Gulf has understandably brought a big spike in the price of the near month crude oil futures contract.  The contract for April 2026 delivery is now above $90.  But if you go out 11 months to the March 2027 contract, the price is still at $66.50.

The condition of having the near month contract price above the far month contracts is known as "backwardation".  The opposite condition is called "contango".  Financial futures like T-Bonds and SP500 futures almost always trade in contango, with the more distant contracts at a higher price, thanks to something called the "time value of money".  With the right portfolio engineering, a trader could go long the distant month and short the near month, thereby having a neutral position relative to the market, but collecting "interest" on the difference in contract premiums.

In crude oil futures, we have seen persistent backwardation ever since the 2020 Covid Crash.  Anyone with some available supply of crude oil therefore has a big incentive to sell it now and collect the higher price, versus holding onto it for future delivery.  Years ago, there were several instances when oil futures went into contango, and so oil producers had an incentive to buy storage tanks to hold their current production.  When contango has gotten really extreme, some traders have even rented crude oil tanker ships to act as floating storage in order to take advantage of the difference in pricing in the futures market. 

There are several messages to take from the current condition of backwardation.  The first is that crude oil consumers like oil refineries are desperate to secure any oil which can be delivered, so that they can keep operating.  With the unknown outcome of Iran's announced closure of the Strait of Hormuz, buyers are in a panic. 

The big spread to the distant month contract prices also tells us that crude oil futures traders do not see the current panicked condition as being permanent.  The distant month contracts have come up a little bit since the US-led invasion of Iran began, but that rise is not nearly as big as the near month. 

This creates the big spread you see in the chart above, and these episodes of very large backwardation are great markers of tops for oil prices.  Normally a spread of about $7/barrel is enough to mark a top, although it obviously can get to a much bigger spread like what we are seeing today. 

The high backwardation spread we are seeing now is a topping condition, but it is not a "signal" to say that a top is in.  Oversold or overbought conditions always have the potential get even more extended.  But this current spread is an interesting bit of history, and a sign that this big spike in near month crude oil prices should not last very long.

Every president wants to have improving jobs numbers, and they all do what they think is necessary and appropriate to achieve that. This includes President Trump, but he is fighting against a more powerful force with a long track record.

It turns out that the sunspot cycle has a very strong correlation to the U.S. unemployment rate (U-3), after one adjustment.  This week's chart compares those two sets of data, with the plot of sunspot numbers shifted forward by 3 years.  The bottom of each sunspot cycle coincides nicely with a bottom for the unemployment rate 3 years later.  And peaks in unemployment tend to echo peaks in the sunspot cycle, with that same 3-year lag time.

The peak month for this current sunspot cycle was in August 2024, so if we count forward exactly 3 years from that we get August 2027 as a projected top for the unemployment rate.  It does not always work out exactly to the month, but that is a pretty good rule for planning purposes.

It is also important to understand that sometimes outside events come along which disrupt this nice correlation.  Covid was an obvious one, and we cannot really blame this sunspot model for not predicting the 2020 spike in unemployment.  There was also an exogenous spike in 1954, after the end of the Korean War brought a slowdown in government defense spending and a rise in unemployment.

Perhaps the biggest example of an exogenous event was when the Fed in the mid-2000s kept interest rates too low for too long, fueling the housing bubble and its eventual collapse.  That led to the "Great Financial Crisis (GFC)" in 2008, which did not fit the timing suggested by the sunspot data.  But by the late 2010s, the two data plots were back into correlation again.

Whenever I show a comparison of data like this, I always get asked what factor could explain the relationship.  Wanting to know that is a natural human tendency.  We all want to know the "why".  It is not always necessary, though, to get after the "why" if the "is" can be established well enough.  We have good data on unemployment rates going back to 1947.  Over that period, it is a well-established correlation, except for that handful of exogenous events I mentioned above.  It is pretty clear that something is going on here, even if we cannot explain what it is.

Some analysts have hypothesized that sunspots affect the weather, which affects agriculture and thus somehow flows through to unemployment.  But the data on sunspots and agricultural production do not match up as well as these data.  Another theory is that the charged particles emitted during higher sunspot numbers affect the wiring in human brains, causing us to collectively change our moods.  That is an interesting hypothesis, but I know of now way to construct a satisfactory experiment to test that one.

I have personally seen enough evidence of this relationship working for long enough that I can accept its validity even if I cannot explain it.  Others may need more evidence.  I invite you to ask yourself, for how much more time would it need to keep "working" before you could accept that it is valid?

The last sunspot cycle bottom was 2018-2020, and the period is about 11 years.  So we can figure on the next sunspot minimum being due 2029-31, and thus the low for the unemployment rate 3 years later in 2032-35.  We do not have the full data for February 2026 yet, but there are already several days in February with zero sunspots.  It can be argued that this cycle is quieting down faster than normal.  If so, that could matter for improvements in jobs data, but not until the 3-year lag time goes by.

The Federal Reserve is now doing QE5, although we are not supposed to officially call it that yet.  All four previous rounds of quantitative easing (QE) have been unquestionably bullish for the stock market.  But the same cannot be said for T-Bond prices.

During all 4 previous QE episodes, T-Bond prices have seen a dramatic drop, which also means a rise for long term yields.  So if QE5 is going to unfold in the same way, then we can look forward to higher long term yields on T-Bonds, and presumably also on home mortgages and other long term debt.

One factor which is different this time is that bond prices have not just seen a big rally leading up to the start of QE5.  All four previous episodes saw QE starting as bond prices were at a spike top.  So there was a lot of room each prior time for bond prices to give back the big gains they had just made.  This time there has only been a small rise in T-Bond prices.

Why would QE be bad for bonds?  This does not make intuitive sense.  After all, if the Fed is going to step in as a new incremental buyer of Treasury debt, then that additional demand should mean upward pressure on prices, and yet we see it works the opposite way.

Part of the answer is that the Fed's purchases of Treasury debt during prior rounds of QE have tended to be in shorter maturity instruments, T-Bills and T-Notes.  So they are not adding very much direct additional buying pressure at the long end of the yield curve.

QE also acts as an economic stimulus, which in theory drives up demand for longer term credit from businesses looking to finance expansion.  That puts upward pressure on longer term rates. 

That is all great in theory, but what is still unknown is if it can work this same way for a 5th time without having the big run up first in bond prices. 

Recent data from the Investors Intelligence weekly survey of investment advisors and newsletter writers showed a very high bull-bear spread.  That spread is simply the numerical difference between the percentage of respondents classified as bullish versus those who are bearish.  High readings show extreme confidence, which every card-carrying contrarian knows is a sign of a top for stock prices.

But before you go placing any sell orders just based on this one indication, a few caveats are important to keep in mind.  The first is that any overbought reading on any indicator constitutes just a "condition, not a signal".  Sometimes an overbought condition can go on to get even more overbought.  It is also worth noting that in many cases, the stock market has been able to continue trending higher in spite of such a reading, especially in a strong bull market. 

That point is worth pausing to reflect upon.  If the stock market can ignore an overbought condition and keep trending higher, that is a sign you are in a strong trend.  And that is really useful information to find out.  Very low readings are much more reliable in terms of marking focused bottoming events.

A more concrete indication that we are seeing right now is the lack of a divergence versus prices.  This week's chart looks back 10 years, and there have been a few really noteworthy price tops over that period, plus a whole lot of lesser tops which did not matter much.  The really big price tops saw a divergent lower top on this bull-bear spread versus prices.  The one big exception to that "rule" was in 2020, when Covid took everyone by surprise.  So to see no divergence now means that we can have pretty high confidence that the market now is NOT at a really important top.  It may still be making a lesser top, but not a major one.

One point about these data from Investors Intelligence is that they seem to track with prices more precisely than other sentiment survey data that I have researched.  I noticed this point years ago, and sought a way to track that even better.  What I came up with was using a detrended plot of the SP500 instead of the raw price data.  To do that, I calculated how far the SP500 was away from its 200-day simple moving average.  This chart shows that comparison:

This chart uses a shorter lookback period, and compares that same bull-bear spread to that detrended plot of the SP500.  With a little bit of scaling adjustment, we see that the two plots are almost identical most of the time.  In other words, sentiment responds to whatever prices are doing.  A rising market gets people more bullish, and vice versa.  Occasionally, though, we see a big disagreement when the bull-bear spread seems to overshoot what prices have been doing.  In other words, survey respondents are getting more fearful or more confident than prices say that they should have done.  That usually marks a turning point for prices.

In the current moment, that turning point has taken the form of having the SP500 lagging behind what other parts of the market are doing, causing the detrended price plot to fall.  Sentiment should soon catch up (i.e. down) to what prices have been doing.

One last point to notice in that lower chart is that the zero levels on the two Y-axes are offset.  This was done in order to get the best fit of the two plots, and it reveals something.  There is about a 15 percentage point bullish bias in the Investors Intelligence survey data versus how prices behave.  I would argue that this bullish bias is appropriate, because in the long run the stock market does tend to go up.  It is just interesting to quantify what that bias amounts to in these data.

The NYSE's daily A-D Line just made a new all-time high on Feb. 4, 2026, which is a statement that liquidity is plentiful.  But just a day later, we have gotten the 3rd Hindenburg Omen within 6 trading days.  This is a message that for all of that supposedly plentiful liquidity, the market has some serious problems.

The late Jim Miekka created the Hindenburg Omen signal back in 1995.  He intended it as an improvement on the late Gerald Appel's "Split Market Sell Signal", which occurred any day that saw both New Highs and New Lows on the NYSE exceed 45 issues.  Miekka saw the problem of not adjusting that for the increased number of issues traded.  And he wanted to add some other filtering rules to get better signals.  An important one is that the market has to be in an uptrend to give a signal.  Miekka thought it was not very useful to get such a warning once stock prices are already in a downtrend.  The criteria for a Hindenburg Omen signal are listed in the chart above. 

If you do an Internet search, you will likely find other sets of criteria at some technical analysis web sites, which is unfortunate.  And because Miekka has passed away, we cannot get him to correct the record, so that task is left to others.  The criteria I use are those which Miekka personally told to Greg Morris, who recorded them in his 2006 book, "The Complete Guide To Market Breadth Indicators". 

The basic idea for the Hindenburg Omen signal is that during a normal uptrend, there should be more stocks making New Highs than making New Lows.  That is the normal condition.  If you get a condition where the uptrend is still underway, but the numbers of New Lows start perking up, then that is a sign of trouble.  What constitutes "perking up"?  That's a matter for opinion, and perhaps back-testing, but Miekka set his threshold at both NH and NL being greater than 2.8% of Advances plus Declines on the same day.  Other analysts might choose a different criterion, which people are perfectly allowed to do.  But for the sake of consistency, and so as to avoid confusion, I stick with Miekka's criteria.

A single signal is interesting, but the message gets more compelling when we see clusters of multiple signals in a short time frame.  We had a grouping of 5 signals from Oct. 29 to Nov. 13, 2025, but the market shrugged.  Now we have 3 more (so far) and would have had a 4th on Feb. 4, 2026 except that the NYSE's McClellan A-D Oscillator was just barely positive that day.

I have found that using a 6-month lookback period to count cumulative Hindenburg Omen signals is useful.  On that basis, we are now up to 8 signals, which is a pretty high reading.  Some noteworthy market tops have come from big readings like this.  But we must also note that there have been other times when we got a bunch of H.O. signals and nothing much happened.  That is possible.  A Hindenburg Omen signal, or a bunch of them, is a warning but not a guarantee of trouble.  It says "pay extra attention".

The last such cluster appeared at the end of 2024, right after the presidential election.  It did not tell us exactly what trouble was brewing, but it did appear just ahead of the stock market's violent drop on tariff worries courtesy of President Trump.  A lesser cluster appeared in early 2022, ahead of that year's bear market. 

It is noteworthy that there was a cluster of 10 signals in 2013, and the uptrend just powered on through.  It is important to remember that the Fed back then was doing QE3, and QE can paper over lots of problems.  The Fed now is doing yet another round, QE5, although not as vigorously as some past QE episodes.  So it is possible that the Fed will paper over the trouble again this time.

Now that the Fed has cut short term rates several times, we are seeing a further steepening of the yield curve.  It is tough to portray the entirety of changes in the whole yield curve over time, and so I am summarizing it in this week's chart by showing just the spread between 10-year and 3-month Treasury yields. 

The 10y-3m spread does a really cool trick, which this week's chart illustrates.  Changes in that 10y-3m spread draw us a roadmap for what small cap outperformance or underperformance is going to look like.

The green plot in this chart is the relative strength ratio of the Russell 2000 vs. the Russell 1000.  It is calculated by simply taking the numerical value of the Russell 2000 Index, and dividing it by the Russell 1000.  The line goes up when small caps are outperforming on a relative basis, and it goes downward when large caps are doing better.  And the cool part of this trick is that the green plot makes those movements corresponding to what the 10y-3m spread was doing 15 months prior.  We are getting the answers ahead of time.

They are not perfect answers, though.  The nice predictive relationship can break down when the Fed is putting a thumb too heavily on the scale with actions other than interest rate policy.  QE3 in 2013 caused a temporary inversion of the relationship.  And in 2020 the Fed started QE4 in response to the Covid shutdowns, which also disrupted the nice correlation for a while.

The Fed is doing QE5 now, although (shhhh!) we are not supposed to call it that yet.  But the magnitude of the Fed's recent purchases is a lot smaller than what we saw in prior rounds of QE, so the potential for skewing the leading indication is likely much less now.

The Russell 2000/1000 relative strength line bottomed in July 2025, and has been rising since then as small caps have started outpeforming again after a really long period of underperformance.  Seeing what the 10y-3m spread has been doing, its message is that we should expect small caps to continue outperforming for at least the next 15 months.  We do not yet know the end point of that projected small cap outperformance, because we have not seen a topping out of the 10y-3m spread. 

When technical analysts learn about volume, they are taught that it is useful for helping to confirm (or not) what prices are doing.  This includes hopefully seeing expanding volume to confirm a price breakout.  And a head and shoulders structure should ideally have the heaviest volume on the left shoulder or the head.

For big ETFs like QQQ, it works differently.  As a gross generalization, QQQ volume works as a fairly pure inverse sentiment indication.  High volume is a sign of a bottoming condition, while a low volume day is a marker of a top.

Low volume days can be problematic, though, because sometimes volume is low due to holiday-light trading.  So one must employ at least a mental filter when evaluating low volume readings.

This week we saw a pair of high volume days, brought about due to the market's reaction to President Trump's announcement about imposing tariffs on European countries who won't go along with plans for the US to annex Greenland.  That news understandably got traders excited, although it was pretty quickly walked back when President Trump announced in Davos that he had arrived at a "framework of a deal".  Prices rebounded on the news.

But the sentiment message had already been posted.  The Jan. 20 selloff brought a big volume spike in QQQ, high enough to be a decent bottom marker, although clearly not the highest volume ever.

This phenomenon "works" because during selloffs, some traders turn to QQQ versus individual stocks for its greater trading liquidity.  It also serves as a shorting vehicle for those wishing to hedge overall portfolio risk but without turning to the futures market.  Similarly, when everyone is feeling happy and complacent, they don't trade QQQ as much and so a low volume day can be a marker of a price top. 

Getting an indication like this week's pair of high volume days does not tell us much about how far prices will move on a rebound.  That can vary a lot.  It just says that a bottom-worthy sentiment indication has announced itself.

We have just seen a new all-time high in the NYSE's daily Advance-Decline (A-D) Line.  It confirms the new highs in the major indices, and that is a really good thing.

Years ago, I undertook a study to see what it means to have a new high in the A-D Line.  In order to increase my sample size, I specified that it had to be just a new 3-year high instead of all time, and then I looked at what the max drawdown was in the SP500 over the succeeding 3 months.  The recent decades' results are shown in this week's lead chart. 

The short version is that if you see a new A-D Line high, you have pretty good assurance that the biggest drawdown you are likely to see over the next 3 months is limited to about 10%.  But the big caveat is that you can throw this rule out the window if the Federal Reserve or Congress puts a thumb on the scale. 

After the bottom of the Great Financial Crisis (GFC) in March 2009, the Fed decided to throw money at the banking system with its first ever round of "Quantitative Easing" or QE1.  They ended that suddenly in April 2010, and what followed came to be known as the "Flash Crash" on May 6-7, 2010, when liquidity dried up all at once and bids just disappeared.  Some blue chip stocks traded for pennies, and those trades had to get wiped out by the stock exchanges.

The Fed honchos saw that they had not fully fixed the liquidity problems with QE1, and so they started QE2 in August 2010, and everything was great.  Or at least it was great until the Fed once again ended QE2 very suddenly in June 2011, and we saw a 19% drop. 

The FOMC learned its lesson, and when they decided to end QE3 in late 2014, they wisely "tapered" their slowdown of purchases of Treasury and mortgage debt.  That allowed the banking system and the financial markets to adjust more slowly to the withdrawal symptoms.  We still saw a market correction in 2015 because of ending QE3, but it was more muted.

We also had a big exception to the rule about new A-D Line highs back in 2020, when the arrival of Covid into the US led to a government shutdown.  Remember "2 weeks to flatten the curve"?  That brought a big drawdown in April 2020, which I named the "Covid Crash" and others took up that label.  That was a genuine exception about the supposed assurance of limited drawdowns from a new A-D Line high.

This principle has also worked further back in time.  Here are a couple more charts looking back further in history, so that we can see that the chances of a big drawdown are pretty limited for at least 3 months after a new A-D Line high. Note that the big time gaps between the red drawdown bars reflect periods when there were not any new 3-year A-D Line highs.

There was one notable exception in October 1978, when the SP500 saw a 13.5% drawdown.  There was a dollar crisis then, thanks in part to rising inflation rates.  It all came to a climax on Oct. 24, 1978, when President Carter announced a tougher anti-inflation program to stabilize prices and the currency.  The SP500 was at 97.49 that day, and continued to fall further to a closing low of 92.49 on Nov. 14, 1978 before starting to rise again. 

The key point to all of this historical analysis is that seeing a new A-D Line high is bullish news, and it offers us "some" assurance that we won't see a big ugly bear market for a while.  The handful of exceptions help to illustrate how there are no guarantees in the financial markets, especially when folks in Washington, DC decide to try to "help".

We are still in the "best 6 months of the year", due to last until early May 2026, and so the current uptrend ought to continue.  But we should also expect a meaningful dip this month, based on the DJIA's Annual Seasonal Pattern (ASP) shown in this week's chart.

I created this ASP by chopping up the daily data into 1-year chunks, restating their value for each year to a starting value of 1.00, then averaging them together as the percentage change from that starting value rather than the numerical value of the index.  Doing that revaluation allows for more accurate averaging than using the raw numerical values, because with raw values the later years with higher index numbers would have a bigger weight. It puts each year on an equal footing.

I also leave out the entire year of 2020, because the Covid Crash was such an abnormal event and a very large one, such that it skews the data.  The point of creating such an average is to depict what "normal" looks like, and the market's response to the Covid shutdowns and then the Fed's monstrous QE was definitely abnormal.  Throwing it out is like discarding the highest and lowest judges' scores in platform diving or figure skating competitions.

One big factor affecting the use of the ASP this year is that there have been several big news events which have pushed the stock market around in ways not reflected in the ASP.  We have not had one of those events for a while, and the market is behaving itself pretty well in tracking the ASP.  But that could change at any moment.  One might argue that the stock market was a lot more sensitive to news events early in President Trump's current term, but stock traders are getting more accustomed to tumultuous news out of Washington DC, and thus they are less reactive to it now.

The month of January typically sees a mid-month dip, with a top ideally due Jan. 10, and then a bottom ideally due Jan. 23.  After that bottom, the market on average gets back to trending higher.  And it could get a boost from the QE5 which the Fed has now restarted, although they are not calling it that yet.  Since the last FOMC meeting, the Fed's Treasury holdings are up by $46 billion.  They are still rolling off mortgage backed securities (MBS), but the net effect of both factors is still a $32 billion rise in the Fed's balance sheet.  That is a bullish tailwind for the stock market.

Whether that QE can paper over the normal seasonal tendency for a January dip is what remains to be seen.

The Annual Seasonal Pattern is one of the indicators I feature regularly in our twice monthly McClellan Market Report and our Daily Edition. https://www.mcoscillator.com/market_reports/

The University of Michigan has been conducting its "Survey Of Consumers" since 1955. The recent data have been among the lowest of their published readings, meaning that survey respondents are not feeling all that great about the supposed 4.3% rate of US GDP growth.  Perhaps people are more attuned to indications like manufacturing employment being in a decline since May 2024.  And thus far, the low gasoline prices have not gotten any traction in the hearts of consumers.

Lows in consumer sentiment measures tend to be bad for whoever is in the White House, and to some extent this applies to Congress as well.  The UMich survey data reached what was then an all-time low in 1980, which doomed Jimmy Carter's reelection chances and led to Ronald Reagan's victory.  A similar low reading in 2008 saw a change from Republican control under Bush 43 to President Obama in a decisive popular vote and electoral college victory.  There was another very low reading in 2022, which led to a change in Congress, and eventually to Donald Trump winning another term in 2024, even though the survey numbers had recovered some by the time of that election.

So the Republicans currently in control of the White House and both houses of Congress will want to see these consumer sentiment numbers start to rebound.  That is the point for politicians to worry about.

The point for investors to worry about is that as consumer confidence numbers start to rebound from very low levels like this, it tends to be extremely bullish for the stock market.  Usually that rebound occurs from a simultaneous low in stock prices along with the consumer sentiment data.  It is a rather unusual condition to see extremely low survey readings like this happening with stock prices at new all-time highs.

Part of the reason why low consumer sentiment are bullish is that such readings usually arise from a condition of seeing a bad economy, which the Federal Reserve then steps in to do something about.  We have had 3 rate cuts in 2025, and now the Fed has started up QE5 (although they are not calling it that yet).  Those are bullish conditions for both the stock market and the actual economy.  It should lead to a rebound in the consumer confidence data, and that should help keep the bull market going.

Back in September I reported on how the data on US trucking from Cass Information Systems was not looking good for the stock market.  Since then the message has gotten a little bit worse, as seen in this week's chart.

Cass tracks trucking data in a lot of different ways, and publishes their own indices.  This week's chart shows the 12-month percentage changes in their Shipments and Expenditures indices.  Both measure trucking activity, but in different ways.  And what is important for our purposes is that these trucking data are well correlated to the stock market.

So it is NOT good news for the stock market to see that both of these indices are down year-over-year.  That is a condition reliably associated with bear markets for stock prices.  A couple of points are worth noting, though.

The first point is that Covid really screwed up the trucking industry, first by sending everyone home for "2 weeks to flatten the curve".  Then while everyone was home, they all decided to order a bunch of stuff online, resulting in big delays at US ports getting container ships in, and getting trucks to haul off those containers.  It was quite the bust-boom-bust cycle for truckers, and arguably the Cass Shipments Index (red line) still has not recovered.  The green Expenditures Index growth rate did go up above the zero level, but it is back down to below zero, showing shrinkage versus a year ago.  Having both of these at or below zero is not a good condition for the stock market.

EXCEPT!!  Point 2 is that when the Fed is doing QE, as they just started up again in December, the stock market can ignore that condition.  We saw in 2012-14 in the middle of the chart that during QE3 both of these indices were showing zero growth, and the SP500 just kept on trending higher.  It turns out that Fed money printing smooths over a lot of problems, for the stock market at least.

We know from how things turned out with QE1 through QE4 that while QE is happening, it is very bullish for stock prices irrespective of what the actual economy might be doing.  So earnings matter much less, and trucking data too.  We also know that shutting off the QE fountain tends to lead to bear markets, but that is a problem for another day.

Gold prices are making a repeating stair-step pattern of movements as gold trends higher.  Each part of this sequence sees a multi-month up move after breaking out to higher highs, then another multi-month consolidation of those gains. Right now gold is in a consolidation phase.

This week's chart shows our Proportional Price Oscillator, which is a variation on the classic McClellan Price Oscillator.  The Price Oscillator which my parents developed back in 1969 is similar to the McClellan A-D Oscillator, which measures the difference between two EMAs (10% Trend and 5% Trend) of the daily A-D difference.  The math is the same for the Price Oscillator, but using closing prices in place of that A-D difference.

Sherman and Marian McClellan were the first to do this mathematical trick of finding the difference between two moving averages, as opposed to just looking at each moving average on its own.  In 1977, the late Gerald Appel adapted this technique to create what he called Moving Average Convergence and Divergence, or MACD.

The Proportional Price Oscillator (PPO) goes one step further, dividing the Price Oscillator by the closing price (and then multiplying by a constant to get to normal sized values).  Doing this helps to normalize what would otherwise be expanding amplitudes of Price Oscillator values owing to higher price levels over time.  The PPO is thus better for longer term chart evaluations, especially if there has been a big change in price levels.  I was the one who innovated this change to the Price Oscillator back in the 1990s, and since then platforms like StockCharts.com have added PPO to their arsenals of indicators you can use.  By adjusting the Price Oscillator for higher price levels, the PPO is therefore equivalent to the Ratio-Adjusted Summation Index (RASI) for A-D data.

I am including the PPO for gold futures in this week's chart in order to make an important point about gold's stair-step pattern of surges and consolidations.  What we are seeing during the consolidation phases is that the PPO works its way back down to near the zero neutral level, which helps reset the gold market to a nice equilibrium state, the better to support the launch of the next ascending phase.

That is important right now because gold's PPO has only made it partway down to neutral, which implies that there is more consolidative work to do.  And this sideways period has only been underway for 2 months, since the Oct. 20, 2025 all-time price high.  Prior consolidation phases have lasted 3-5 months.  There is no mandate that it has to happen exactly the same way this time, but this pattern seems to be repeating nicely so it would be strange if we got a different behavior this time.

Along the way, it is quite possible that we can see gold prices make an incrementally higher price high, as it tries to convince everyone that the next breakout is starting.  Then after a few months, when traders finally give up hoping for a legitimate breakout move, the real one can start.

Years ending in 5 are up years almost without exception through the entire history of the DJIA.  The two exceptions were 2005, when the DJIA fell 0.6%, and 2015 with a 2.2% drop.  Thus far in 2025, the stock market is back to its normal year 5 behavior, with a 12.5% gain through Dec. 4, 2025.  It would have to be a really bad rest of the month to spoil this year 5's record.

 This week's chart shows the Decennial Pattern for the DJIA, created by chopping the price history up into 10-year chunks of time, and averaging them together on a percentage gain basis.  It is similar in that respect to the Annual Seasonal Pattern and the 4-year Presidential Cycle Pattern.  Putting the data together this way allows us to see what typically happens over the course of each decade.

Coming up is the more problematic year 6 of the decade, which is more flat on average.  But that flat part does not start for a while, and we still have more of the uptrend seen in year 5s that continues into year 6.

This next chart shows the same comparison, but zoomed in to see the data better.  I have also adjusted the scaling so that we can get more of each of the plots on the same chart. 

The year 5 bullish effect was interrupted earlier this year when the stock market had a bit of indigestion after hearing of President Trump's tariff plans.  Investors eventually got over that, and the patterns have matched up nicely since about May 2025.  The Decennial Pattern shows that this uptrend should continue all the way to a top due ideally April 6, 2026.  That is when the sideways period of the year 6 is supposed to start.

Real life approximates the average pattern, but never duplicates it exactly.  There is no logical reason why years of the decade should matter and manifest similar behaviors, but this is something which has been going on for decades.  So there must be something to it, even if it does not make logical sense.

 

Analysts are watching closely to see if we are going to get another Zweig Breadth Thrust Signal within 2025.  Created by the late Martin Zweig, the ZBT triggers when a 10-day EMA of Advances divided by Advances plus Declines goes from below 0.40 to above 0.615 within 10 trading days.  The numbers of historical instances are pretty low, which is intentional.  Zweig wanted to find those rare times when breadth data switched suddenly from bad to really good.

Breadth data had been bad earlier in November and that resulted in achieving the first step, which is to get that EMA down below 0.40.  It got to 0.393 on Nov. 20, 2025.  Once it started rising above that 0.40 threshold, that started the clock to see if we can get the other criterion for this signal within the 10 trading day time window.

Back in 2015, I wrote an an analysis of all ZBT signals triggered from 1928 through 2015, showing that there were many great ones, some so-so, and some real losers.  In recent years, this signal has been working better than it did decades ago.  You can read that at https://www.mcoscillator.com/learning_center/weekly_chart/zweig_breadth_thrust_signal/.

Here is what the last 3 decades look like for this signal, and all of these signals were followed by nice uptrends.  In 3 of these cases, though, one had to wait through a retest of the prior lows before one got to enjoy the strength that the signal promised.

As I write this on Nov. 28, 2025, we are only 5 days into the 10-day window, and the 10EMA is already up to 0.595.  It only has a little bit more to go to get up to the 0.615 threshold.  We need to keep seeing more strong breadth days to get there, and one big down day could be a setback which would scuttle the possibility this time if it happens.  There are a whole lot of episodes of potential ZBT signals, but only a few that succeeded.

You can keep track of this very easily for yourself in any spreadsheet program, as long as you have access to data on Advances and Declines.  For final calculations, I use data from the Wall Street Journal's web site.  https://www.wsj.com/market-data/stocks/marketsdiary

You can get preliminary data throughout the trading day at https://www.wsj.com/market-data/stocks/us.  I have used those preliminary data for this article, as the final data come out later each day.  You can also fetch the A-D numbers from my web site's Breadth Data page.  https://www.mcoscillator.com/market_breadth_data/

Here is a screenshot of what a simple spreadsheet looks like for calculating the Zweig Breadth Thrust signal:

The hardest part of this (and it is not all that hard) is doing the math for the 10-day Exponential Moving Average (EMA).  The math of EMAs was only invented in the 1950s, and they are different from simple moving averages (SMAs) because the most recent data are weighted more heavily.  Many analysts, including Zweig, refer to EMAs with a time duration such as 10 days.  I have long preferred the originalist terminology coined by the late Pete Haurlan, who first introduced the use of EMAs for tracking stock prices in the 1960s. 

Haurlan referred to EMAs by their "smoothing constants", which refers to how much weight is given to the latest datum.  Haurlan knew that EMAs never really forget the old data like an SMA does.  In an EMA, the older data just become decreasingly important. So to Haurlan (and to me), the smoothing constant is the important factor, more than some number of prior periods.

To convert a time period to a smoothing constant, one uses the formula 2/(n+1), where n is the number of periods.  So for a 10-day EMA, n in that formula is 10, so the equation is then 2/11, or 0.18.  So in Haurlan's original terminology, this would be an 18% Trend.

What that means is that each day's EMA value moves by 18% of the distance between yesterday's EMA value and today's new datum.  So in that spreadsheet screenshot above, we see that the Nov. 26 EMA value was 0.5811, and the new datum for A/(A+D) is 0.6570.  The difference between those is 0.0758, and so the EMA gets moved by 0.18 x 0.0758, or 0.01366.

The formula bar in the spreadsheet screenshot shows a simplified version of the math to calculate the EMA for cell F21.  The same formula can be copied upward and downward within that column.

The column with the counter in that spreadsheet screenshot shows that we have until Dec. 5, 2025 to accomplish the task of getting this EMA up above 0.615, starting from day 0 which was when that EMA was last below 0.40.  If you build this simple spreadsheet calculation for yourself, you can enter hypothetical or intraday values for Advances and Declines to see what it would take to accomplish the task of moving the EMA up high enough. But for the final calculations, you will need the final breadth numbers each day.

So what happens if we get to that 0.615 number, but on day 11?  Great question.  The top chart shows several instances of seeing this 10EMA get up above the 0.615 threshold but after the 10-day period.  Generally speaking, the uptrend continued higher in those instances, although the one in late 2021 that took 11 trading days was an exhaustive up move and the downtrend resumed.  I have not done an exhaustive study to show whether Zweig's 10-day specified period really is the ideal one, or whether his EMA thresholds of 0.40 and 0.615 are the best.  One can do an infinite number of permutations of varying these numbers to try to optimize a signal.  That can sometimes lead to interesting insights.  It can also lead to "overfitting" of past data.  Just about any trading system, or signal, is going to have bad signals.  That is the world we live in.

The general point one should take away from this is that Gobs Of Breadth Is A Good Thing.  There are lots of ways to quantify that, and there are other breadth thrust signals which other analysts have developed since Zweig introduced his.  If you are inclined to tinker with these ideas, I encourage you to do so.  You may not find a way to build a better mousetrap, but you will still probably learn some things along the way.

The VIX Index was invented in 1989, in a series of papers written by Menachem Brenner and Dan Galai.  The CBOE introduced it as an index in 1993, initially using SP100 (OEX) options, but then changing to SP500 options in 2003.  See https://cdn.cboe.com/resources/indices/Volatility_Index_Methodology_Cboe_Volatility_Index.pdf for more information on the history of the VIX, and its current formulation.

The CBOE then introduced the first futures contracts based on the VIX in 2004, but those contracts really did not take off and become popular until 2014.  The cool thing about having futures contracts on the VIX is that we can use their pricing data as a way to normalize the value of the VIX Index, and that is what this week's chart is all about.

Each VIX futures contract gets settled for cash, since the VIX is not really "deliverable", and this takes place usually on the 3rd Wednesday of each month.  VIX futures contracts that expire far into the future are usually priced much higher, because the traders of those contracts have to factor in potential changes in risk levels over a long period of time.  Because of that, the most distant VIX futures contract is usually the highest priced contract.  As time goes by, and each contract gets closer to its expiration, that price premium will decay and see the futures contract price work its way closer to where the VIX Index is.

Most of the time, the VIX Index is below the prices of all of its futures contracts.  That condition results in a positive reading for the indicator in this week's chart, which measures the spread from whichever VIX futures contract has the highest price, vs. the VIX Index itself.  Sometimes this indicator gets up to a really high positive value, meaning that the VIX Index is down really far below all of its futures contracts.  That condition can be a topping sign for prices, but it is a hard condition to read reliably.

A more reliable condition occurs when the VIX rises up above the prices of all its futures contracts, which results in a negative reading for this spread indicator.  We have such a condition now, and these negative readings are great indicators of a bottoming condition for prices.  But it is important to note that a "bottoming condition" is not necessarily the same thing as the exact bottom moment.

What this indicator does is to evaluate the current VIX Index reading compared to the baseline of what its futures contracts are doing.  Traders of those contracts have to make long term assessments of what risk and volatility are going to look like going out several months.  The VIX Index can gyrate around more wildly given worries of the moment, and so making this comparison allows us to quantify where the VIX Index is compared to the assessments by its futures contracts' traders opinions about the future.

At the April 2025 tariff crash low, we saw this indicator get all the way to -30%.  The current drop below zero is thus far only to -11%, but that is still a decent oversold condition.  It is saying that the rise of the VIX (to 26.42 as of Nov. 20, 2025) has gone on a lot further than the VIX futures traders think is appropriate.  This should mark a bottoming condition for the SP500 (eventually).

There was some excitement in the world of technical analysis the past two weeks as we saw 5 separate signals fire for something called the Hindenburg Omen.  This is a warning signal of trouble, but trouble does not always come.  What is fair to say is that Hindenburg Omen signals have appeared at every major stock market top going back several decades.  But they have also appeared at other times.

The creator of this signal was the late James Miekka, who died tragically in 2014.  Miekka was a blind mathematician and stock market analyst who had a great way to see numbers in his head, even though he could no longer see them with his eyes.  His father helped him with publication of his newsletter, The Sudbury Bull and Bear Report.

Miekka created this signal as an attempt to improve on the late Gerald Appel's "Split Market Sell Signal", which triggered on any day that the NYSE saw more than 45 New Highs (NH) and New Lows (NL) on the same day.  That signal was developed when there were fewer issues traded, and so the first adjustment was to allow for more issues, and not use a fixed number.  Miekka also wanted to add additional filtering criteria, insisting for example that the market be in an uptrend.  He figured there was no use for a warning signal when you are already in a downtrend.

Over the years, Miekka tinkered with the criteria, and that has created some confusion in the world of technical analysis.  The criteria for the signal listed in the chart above are those which Miekka told to Greg Morris for his 2006 book, The Complete Guide To Market Breadth Indicators.

The name for the Hindenburg Omen came from the late Kennedy Gammage, who wrote The Richland Report newsletter and who was a big fan of using the McClellan Oscillator.  Ken was a frequent guest on FNN, which was a cable business news predecessor before CNBC.  Miekka introduced this signal to Ken, who had a background in marketing and knew that it needed a catchy name.  Ken knew of a signal created by Bill Ohama called the Titanic Syndrome, which happens when NL exceeds NH within 7 trading days of a new 1-year high in the SP500, so he proposed the Hindenburg Omen which Miekka adopted.

Generally speaking, Hindenburg Omen signals tend to matter more when you see a big cluster of them in a short space of time.  Here is one way of looking at that, using a 6-month lookback.

The current count of 5 signals is not as big as some other clusters.  But we got 4 signals in a cluster at the end of 2021, ahead of the 2022 bear market.  So 4 is enough, if the market is inclined to live up to this warning. And 2 signals were enough back in December 2024 and March 2025 to tell us about the trouble in the market which unfolded in the April 2025 tariff reaction minicrash.  But 5 is better.

Calamity does not always happen, especially in cases like 2013 when the Fed was doing QE3 and throwing a lot of money at the banking system.  Fed QE can paper over lots of ordinary types of problems.  And if we get QE5 in the next few weeks as some are speculating, that lesson from 2013 would be an important one to remember to help put these recent Hindenburg Omen signals into context.

Some analysts are dismissive of the Hindenburg Omen because of how there have been several instances of failed signals.  Miekka acknowledged that in the rules he crafted, something which these dismissive analysts fail to take into account.  He insisted that the signal was only valid for the next 30 trading days, and only on days when the McClellan Oscillator is below zero.  If the McClellan Oscillator goes above zero during that 30 trading day forward look, the signal remains valid but not in effect as long as the Oscillator is positive.  You can see the McClellan Oscillator value every day on our web site's Market Breadth Data page, https://www.mcoscillator.com/market_breadth_data/.

These recent signals should not be viewed as a guarantee of trouble.  They are like your check engine light, which could mean you are out of engine oil (really bad!!), or it could just be a loose gas cap.  Use this information in concert with other indicators of trend direction, and as a warning that something is going a little bit unusually in the market, which may be worth keeping in mind.

The Challenger, Gray, & Christmas report on corporate layoffs just posted at 153,000, the worst October since 2003.  Economists are floating numerous explanations for this, including the government shutdown, tariffs, and other "usual suspects".  But I am going to put the blame right at the feet of the Federal Reserve, for having kept interest rates too high since 2023.

My definition for "too high" is the 2-year T-Note yield, shown in this week's chart.  I first wrote about that here in 2009, and have been writing about it for longer than that in our twice monthly McClellan Market Report newsletter.  The 2-year yield knows better than the 400 PhD economists working at the Fed what the FOMC ought to do with its target rate.  The FOMC makes big mistakes when they think that they know better than the silly old bond market. 

For the past 3 decades that the FOMC has been using the Fed Funds target rate as its monetary policy instrument, the FOMC has almost always been being the message of the 2-year.  They are either too slow to hike rates in good times, or too slow to cut them.  The 2-year always seems to know.  By maintaining either a positive or negative spread between the 2-year and the FF target, the Fed fuels bubbles and recessions.  If I had my way, the FOMC should just outsource the task of setting the FF target to the 2-year, and that way they could save a bunch of money flying in all of the district presidents and other members of the FOMC for the 8 meetings they hold per year.  And we would get better results.

As a side note, before the early 1990s the Fed used to target the Discount Rate for their monetary policy, something which almost no one ever even thinks about these days.  So extending this comparison back further than what this chart shows would not be a valid comparison given that policy change.

The FOMC is finally getting around to cutting rates now, but their rate of cutting has been too slow and they have been maintaining this negative spread we still see today.  Think of that negative spread as having the Fed's foot on the economy's brake pedal.  We are now seeing the results of all this built-up braking force over the past 2 years.  Other agencies and causes may get blamed in the media for the economic slowdown, but it is the Fed's fault.

I wrote here back in September 2025 about how the total amount of Reverse Repurchase (RRP) agreements at the Federal Reserve was bottoming out, and how they were thus ceasing to be an issue for the stock market.  That thesis needs a review, given the past few days' data.

To review, a regular Overnight Repurchase Agreement (or Overnight Repo for short) is a transaction between the Fed and a member bank in which the Fed effectively lends money to a bank.  The process involves the sale of Treasury debt with an agreement to repurchase it later at a defined price, set to match the Fed Funds target rate. 

A Reverse Repo or RRP is the same transaction but done in the opposite direction.  In a RRP, the Fed effectively borrows money from a bank, which has the effect of reducing liquidity in the banking system.  That matters to the stock market because changes in RRPs tend to have an effect on stock prices about 5 trading days (TD) later, as illustrated in this week's chart.  In that chart, I have inverted the scaling on the total amount of RRPs just to help us see the relationship with a positive correlation. 

When RRPs increase (blue plot going down in the chart), that takes away liquidity, and the stock market tends to suffer.  That effect helps to explain why we had a bear market in 2022 (not shown), because the Fed was trying to undo the effects of QE4 and so it ramped up RRPs to a high of $2.5 trillion. 

As they have been unwinding that, and shrinking the total size of their RRPs, liquidity effectively comes back out of the Fed and into the banking system, thereby making it available to do things like help lift stock prices.  But with RRPs down to almost zero, there is no fuel left in that tank and so the stock market is going to have to find liquidity (or not) in other places.

That should have a net neutral effect on stock prices, except that for some reason RRPs are starting to rise again (blue inverted chart plot going down) over the past few days.  RRPs got down to just $2.4 billion on Oct. 24, but now they are back up again to $19.2 billion.  That is not a whole lot of money in the scale of Fed operations, but it has a negative effect on liquidity. 

Overnight Repos and RRPs are not the same thing as Quantitative Easing (QE) or Quantitative Tightening (QT), which is where the Fed buys or sells Treasuries on the open market.  But repos are like QE because the Fed is renting Treasuries, either in or out, and thus having the same type of effect on liquidity.

Now, as RRPs have been getting down close to zero, the Fed is suddenly becoming more active doing Overnight Repos.  The sizes are still small, but they are not nothing.

On Oct. 29, the Fed did $10.3 billion in Overnight Repos, and this comes as part of an awakening of that activity since the Fed started cutting rates again in September.  Many times these Overnight Repos are done as part of an effort to get the overnight trading of deposits among member banks to match the FOMC's target rate.  Doing an Overnight Repo adds liquidity, but it also conveys a statement that there seems to be a need for liquidity in the banking system.  That jump up to $10.3 billion of Overnight Repos on Oct. 29 matched a jump higher for the SP500 to a top that day.  And then as Overnight Repos backed off to just $6.2 billion on Oct. 30, we saw the SP500 pull back.

I don't have any inside information on what the Fed is going to do next with its repos activity.  But I do know that their activity in RRPs tends to work with about a 5TD lag, and that should mean a dip for stock prices, assuming things work as they have been.

You can track data yourself on RRPs and Overnight Repos at these links:
https://fred.stlouisfed.org/data/RRPONTSYD
https://fred.stlouisfed.org/data/RPONTTLD