On October 31, 2023, the S&P500 closed at 4193.80. The index closed at 5137.08 on March 1, 2024. This represents a price return of 22.49%, not inclusive of dividends.
In addition to the astonishing feat of putting up two to three years of positive returns in three calendar months, the above was accomplished with a collapse in realized volatility, with few negative return days and even fewer negative return weeks.
Meanwhile, cuts in the Fed’s policy rate have been delayed by three months, the yield curve remains inverted, and bottomless wells of digital ink continue to be spilled over esoteric shiny toy models that cannot be monetized into additive PNL.
This juxtaposition of contradictions reveals a truism in market-macroeconomic analysis that confuses academics and practitioners alike:
The hardest part of macro analysis is not mistaking the epiphenomenon of indicators that coincided with past events as being causal factors.
This mistake has turned much of the practice of macroeconomic analysis into a dogmatic cult not dissimilar from technical analysis.
A macro model based on linear X then Y (rates rise => stocks fall => demand slows => earnings decline => job market weakens => wage growth slows => inflation falls) events crowds out the nuance of every business cycle.
In this cycle, things have happened that were not supposed to happen.
The inverted yield curve did not cause a recession (any day now).
Demand has not slowed as consumer spending remains bussin and income driven.
The labor market is the best it’s been since before I was born (the stone ages).
Inflation is falling without throwing a generation of people out of work as a formative life experience.
The contras to the above can be mildly intellectually defensible with the long and variable lags associated with broken clocks. This makes them academically satisfying but economically unfulfilling to traders and investors.
What is not sus, however, is the hard reality of cash flows and PNL’s.
Take for example, the idea that Treasury yields matter for actionable, tradeable equity valuations. The cultish answer is that a rise in long yields will depress valuations (and prices) and a fall in long yields will raise valuations (and prices).
Decades of data tell a different story, starting with the most recent cycle.
The U.S. 10-year note ended 2019 at 1.92%. Meanwhile, the S&P500 was trading at 19x forward earnings.
The 10-year closed on March 1 at 4.19%, and the S&P500 is trading at 20.4x forward earnings.
In the 1960’s, we can see that equity valuations were high (21x Schiller PE average throughout the decade) despite 10-year yields rising constantly though the entire decade.
The 1970’s and 1980’s demonstrated that stock valuations do not respond to yields themselves, but rather to interest rate volatility, which is driven by inflation volatility.
The causal chain is inflation volatility leads to policy uncertainty, which leads to interest rate volatility, which leads to depressed valuations.
There is a logical intuition to this. A firm budgets capital based on hurdle rates far in excess of wholesale funding markets. Cyclical ebbs and flows do not change their long-term plans. They adjust when they must, like all economic agents.
Their ability to make timely adjustments is impaired when inflation becomes unpredictable and distorts the decision-making process, and thus impairs the value of an income generating asset.