#writing **July 17, 2023** We experience mean reversion a lot in everyday life. Take the "Sports Illustrated jinx" as an example. The theory is that the player that appears on the cover is doomed to underperform the following season. Overconfidence and pressure to perform are often offered as explanations, but a simpler explanation is that the player just got lucky the prior season and it was inevitable that they would see regression the following season. We like to assign causal explanations for mean reversion, but they are wrong because mean reversion has an explanation but does not have a cause.[^1] Because we frequently experience mean reversion in life, we assume it happens in the markets and we assign causal explanations to why it should happen. The commonly held belief is that extremes in valuations, the yield curve, interest rates, speculation, etc. cannot last. The "rich" will fall in price and the "cheap" will rise in price. Depending on the topic, mean reversion can work over the long term when there is significant correlation, but often the causal explanations we develop around them are inaccurate. The chart below shows that the yield curve (as measured by the 30-year UST minus the 2-year UST) tends to revert to the mean over time. It also tends to invert prior to recessions. Because of these properties the yield curve is accepted as a leading indicator of recessions. _When it gets too steep the market is telling the central bank that it needs to tighten which slows economic growth, and when it is too inverted the market is telling the central bank that it needs to lower rates which is supportive for economic growth._ ![[Pasted image 20230716135207.png]] Consider the statement that **an inverted yield curve predicts a recession**. We know that the yield curve is the difference between short rates and long rates. We also know that short rates are influenced by monetary policy and long rates are influenced by market expectations. Further we know that the direction of short rates is negatively correlated to economic growth because of the impact on leveraged enterprises and the cost of money. As we go through this exercise the causal narrative of how the yield curve predicts a recession is growing stronger, however we can also say that **the correlation between short rates and long rates is less than perfect,** and that statement is roughly equivalent to the first statement because of the interplay between market expectations and monetary policy in determining the slope of the yield curve. The difference is the second statement is far less evocative than the first. It is not that the yield curve does not convey important information, it is that we tend to overestimate the causal influence of it due to our tendency towards causal explanations and lack of interest in "mere statistics." The graph below shows the 76 unique yield curve inversions we have seen since February 1977 along with recessions shown as the shaded areas. Clearly the longer short rates and long rates diverge the more likely it is we will see a recession, and this is where we can start to draw some insight from the yield curve: from understanding why the Fed and the market are going in such different directions. ![[Pasted image 20230716135300.png]] The Fed feels that it must keep tightening as the risk markets stay buoyant, mainly due to optics. The monetary policy transmission mechanism continues to lose efficacy as the housing market stays strong and the shadow banking sector continues to grow in size and influence. Strong risk markets also keep the cost of capital affordable for companies and puts a support under the economy. However, the breadth in the risk markets is narrow as the trend for inflation and growth is lower. The breakout in treasury yields from the secular down trend has been unable to find meaningful acceptance above 4% on the 10-year and the market is oversold which increases the risk of a countertrend rally. This emboldens the treasury bulls who have been calling for a recession and have been disappointed so far. The ability to lock in all-in yields that we have not seen since before the GFC also brings buyers out of the woodwork. The net result is that we have the third longest stretch of inversion since the late 1970s when the modern era of central banking began at the same time that we have very “high valuations” for the equity market. ![[Pasted image 20230717093141.png]] The chart below shows Shiller CAPE for the S&P 500.  Valuations are often thought of as synonymous with risk: there is more risk in highly valued stocks, and less risk in lowly valued stocks. Once again, we see the tendency to assign a causal explanation of mean reversion. This is a "superficial process [that] doesn't distinguish between a value stock and a value trap"[^1] . ![[Pasted image 20230716140417.png]] Let’s think about how a high valuation like NVDA’s  200+ PE could come about. PE is price divided by earnings, so a high ratio could come about from an average price on a low earnings number, a high price on average earnings, sky high price on high earnings, and so on. The price the market is willing to pay for earnings today or expected earnings in the future is based on current interest rates and investor utility. We already explained how the short term utility in the market is all about covering shorts or underweights after this surprising rally, we know what the Fed is doing with short rates, and we know what the market thinks about the future path of interest rates; and in this we have a perfect example of how we tend to see how value investors are often frustrated by rich stocks that just get richer and value stocks that never seem to catch the eye of the market.  The correlation between price and profits is surprisingly much better than the correlation between short rates and long rates. This seems counterintuitive except for when you consider the efficiency of greed in the market as well as the self-fulfilling nature that a lower cost of capital can have for a company. The markets are very efficient at pricing and distributing risk to the highest bidder for that risk and the emotional cycles of fear and greed tend to determine who the marginal buyer of risk is at any moment in time. Price drives narrative in the markets and whether it is real profits or expected profits, in the absence of fear, investors tend to clamor for the shiniest thing at any given moment and financial commentary is more than happy to throw gasoline on the fire. This is Newton's first law at work.  Knowing who is setting the marginal prices of risk in the market is so important. If you sit down at a poker table and you can't spot the fish, you are the fish. The same holds true in the markets. Just because something looks rich or cheap doesn't necessarily mean it is because you may not be seeing the whole picture. If it is just [retail tourists selling REITs and CMBS due to fear](https://cedarshillgroup.substack.com/p/chg-issue-112-anatomy-of-a-cmbs-downturn), then the odds that they are "cheap" options increases. But if the illiquidity in CRE is delaying the price discovery process because there is a supply-demand imbalance then today's "cheap" options could become overpriced tomorrow as the private market catches up with the public market. Any simplistic strategy dependent on mean reversion doesn't work in isolation. Mean reversion is a real force in the markets, but you need to understand how it works and guard against our tendency to accept flawed causal explanations. Dig deeper and understand that regression and correlation are "different perspectives on the same concept".[^3] Understand how the machine that is the market works and how risk is priced and transferred. Finally, appreciate the importance of who is making the current prices and their capacity for holding that risk. [^1]: Daniel Kahneman, Thinking Fast and Slow, p.182 [^2]: [Measurement Not Prediction](https://moontowermeta.com/measurement-not-prediction/) [^3]: Daniel Kahneman, Thinking Fast and Slow, p.181