Breadth is liquidity
Interview with Sherman and Tom McClellan
Notes from my conversation with Tom and Sherman McClellan, recorded for the Foundation for the Study of Cycles interview series.
A price index can rise while most of its stocks fall. The McClellan Oscillator was built in 1969 to expose exactly that condition, and for this episode of the FSC interview series both generations behind it joined me: Sherman McClellan, who created the Oscillator and Summation Index with his late wife Marian, a mathematician, and their son Tom McClellan, who edits The McClellan Market Report and still works on it with Sherman daily. The conversation covered an origin story that is better than most people know, and the claim that gives this article its title.
Rocket science and hand-drawn charts
In the summer of 1969 every data point was computed by hand. Marian McClellan calculated the values, Sherman posted them to charts, and the mathematical machinery came from an unlikely source: P.N. “Pete” Haurlan, a genuine rocket scientist at the Jet Propulsion Laboratory who had used exponential smoothing for missile and satellite tracking and applied the same technique to market data. Haurlan’s terminology survives inside the Oscillator to this day. His “10% Trend” and “5% Trend” are exponential moving averages with smoothing constants of 0.10 and 0.05, which correspond to lengths of 19 and 39 days (the EMA multiplier is 2 divided by length plus 1). Gene Morgan, host of the “Charting The Market” television show in Los Angeles, put the new indicator on air in 1969 and attached the family’s name to it, and Haurlan’s Trade Levels firm published the McClellans’ book “Patterns for Profit” in 1970.
The construction itself is compact. Take the NYSE’s daily net advances (advancing issues minus declining issues), compute the 19-day and 39-day EMAs of that series, and subtract the slow from the fast: that difference is the McClellan Oscillator. The running total of the Oscillator is the Summation Index, the slower gauge for the larger swings.
What breadth sees that price hides
Cap-weighted indexes hide participation. A handful of mega-caps can carry an index higher while the average stock rolls over, and today’s concentration makes the effect stronger than at any point in the indicator’s history. Breadth counts every issue equally, and as a result it measures something closer to the availability of money than to the opinion of the index. When liquidity is abundant, the buying reaches even the weakest issues and breadth is broad. When liquidity drains, money concentrates in the largest names first, the advance-decline statistics deteriorate before the headline index does, and the divergence appears at major tops with remarkable consistency.
In terms of this interview series, the McClellans complete a measurement chain that Michael Howell opened in episode one: Howell measures liquidity at its source, the balance-sheet capacity of the financial system, while breadth measures its arrival at the level of the individual stock.
A band-pass filter before the term was fashionable
From an analytical perspective, subtracting a slow EMA from a fast EMA is a band-pass filter. The fast average removes the day-to-day noise, the subtracted slow average removes the trend, and what remains is the vibration between the two smoothing horizons, roughly the swings that play out over several weeks to a few months. The Oscillator was therefore a cycle instrument from birth, tuned by its fixed 19/39 pair. That fixed pair is the same design decision John Bollinger made with his fixed 20-period bands, and the same adaptation applies: measure the dominant cycle first, then set the EMA pair relative to it, so the passband stays centered as the market’s rhythm morphs. In practice, breadth data rewards this treatment more than price data does, because removing the mega-cap distortion leaves a cleaner carrier. Running dominant-cycle detection on the cumulative advance-decline line regularly produces sharper spectra than the cap-weighted index itself.
Repetition as a family business
The other thread through six decades of McClellan work is repetition. Tom’s research lives on lead-lag relationships and recurring patterns:
commercial traders’ net positions in eurodollar futures as a roughly one-year leading indication for the S&P 500 (a relationship he introduced publicly in 2011, and one he is candid about),
gold leading interest rates by about 20.5 months, and an 8-year cycle in gold itself.
Sherman has watched enough complete market cycles. Even the founding dataset was framed this way: before publishing in 1970, the McClellans assembled advance-decline data covering two full 4-year market cycles, because one cycle proves nothing.
The full conversation is on the FSC channel:
The McClellan Oscillator: Two Generations of Market Timing
McClellan Financial Publications: https://www.mcoscillator.com
Foundation for the Study of Cycles: https://cycles.org