The S&P 500 is tracking 2 standard deviations above the norm right now.
The purpose of this post is to inform - it is not to predict, not to scare, not to embellish - it is to inform.
So, quick reference:
When I refer to the market, I am talking about the S&P 500.
The charts in this post are of the SPY ETF - The most popular ETF that tracks the S&P 500.
The research is my own. I have studied and tracked the market for well over 2 decades, and this is my way of making sense of the environment we find ourselves in.
This is a statistical approach based on the bell curve. So, when I refer to market extensions, I'm referring to the number of standard deviations that price is extended for the mean (average).
We start this study in January 1993 - the origin of SPY, taking it right from the beginning up to today. Looking at the market environment at the major turning points - at least the major turning point in my mind. (Feel free to differ)
1994 - 2000 - Bull market to the Dotcom crash
2000 - 2002 - Bear market bottom
2002 - 2007 - Bull market to the GFC (Global Financial Crisis)
2007 - 2009 - Bear market bottom
2009 - 2020 - Bull market - (The age of monetary policy - Central Banks)
2020 - 2020 - Bear market - (Covid)
2020 - 2022 - Bull market - (Enter Fiscal policy)
2022 - 2022 - Bear market
2022 - today - Bull market - (The AI bubble)
The descriptions in the brackets are my own but are also commonplace in popular financial discourse, but if you would like to describe it in any other way, knock yourself out.
Methodology:
Allow me to quickly explain my methodology.
Let's look at the 1st period in question: Jan ‘93 - March 2000, our 1st Bull run.
Take all the closing prices during this period and find the mean (average). Use this mean to build your bell curve (standard deviations, sequence and distribution numbers) and from that you are able to gain context about where prices found themselves during the period.
It looks like this: Bell curve capturing the price action during this period.
Line graph representation of the price action captured by the bell curve.
Different time periods:
When we look at all the other time periods mentioned above, we see the following:
(Side note - Important to note is the average price during the period and the 2 standard deviation price levels).
March 2000 - Oct 2002: Dot com crash and market bottom
Oct 2002 - Oct 2007 - Sub Prime Housing Bubble
Oct 2007 - March 2009 - GFC
March 2009 - Feb 2020: Monetary policy
Feb 2020 - March 2020: Covid (1st time we did not reach the 2-sigma price level)
March 2020 - Jan 2022: Fiscal policy
Jan 2022 - Oct 2022: ‘22 Bear Market
Oct 2022 - Today: The AI Bubble
This is all the data available since the inception of the SPY ETF. What do we learn from this?
The important level in both bull and bear markets seems to be the 2 standard deviation (2 sigma) price level. When price reaches that level, it usually signals a turn or maybe a pause in the market. The 2 instances that price did not reach the 2-sigma level (the pandemic and right after) are interesting. I suppose price exhaustion might have been caused by the speed of the market movement, but I’m not sure about that.
Also important to understand is that this method of looking at the market environment is not predictive and can only be determined in hindsight or in the moment - mainly because it is not possible to predict the average price of the market during either a bull, or a bear run.
However, for the current environment we do know that we are trading above the 2 standard deviation price level. This argues well for re-evaluating allocations to different asset classes and maybe considering adjusting the exposure.
Thank you for reading, much appreciated.
Hendrik
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