The Big Picture
Graphic Novel Edition
I was recently reminded that I need to summarize every now and again for those who haven’t been keeping up with my writing and are coming in cold. I need to spell out what I’m doing and why, so that readers can make sense - and hopefully, use - of what I present.
The quick & the dirty
Why?
35 years of portfolio management experience have taught me that the institutional approach to understanding economics and financial markets is fundamentally flawed. This has led to an accepted mediocrity as industry “best practice” because the orthodox approach misses the mark by a significant order of magnitude.
Because of these failings, I set out on my own to find a better way.
My process
The economy and financial markets are cyclical. At various points in the business & investment cycle there are varying degrees of investment risk. Additionally, there are fairly consistent patterns of consumer & investor behavior. Cause and effect are observable. The problem is, that there is a lot of data and a lot of noise around the data (i.e. everyone has an opinion, but few do the research … and fewer still can interpret information well).
In a nutshell, what I do on this website is:
identify our current position within the cycle (this is the majority of my content, especially the free stuff). It’s an ongoing process.
given our current location in the cycle, I can identify an asset or asset class that has more favorable asymmetry of risk than other assets & asset classes (i.e. biggest bang for the buck on a risk-adjusted basis).
I also have a trading algorithm that I wrote, which has proven remarkably accurate at identifying market turns. This helps identify market timing. The model identifies asymmetry in market positioning relative to economic conditions.
I focus on the big picture. This includes identifying the larger economic cycles (the tide) of which the business & market cycles I mention above are but a subset (the waves). I also choose to employ my trading model in pursuit of the big picture (i.e. preferring to identify medium-term outcomes), though it is scalable enough to use for short-term trading purposes.
Research & curiosity
Everything I do is research-based and designed with a disciplined approach. I aim for robust and repeatable processes.
I’ve always had an analytical ability - the one benefit of an autistic mind. I have always been able to quickly and accurately interpret patterns & relationships in data and information. My mind also has a curiosity that wants to understand things. In recent years, I broke away from institutional demands & control and let my mind have its way with the data. Here’s some of the unique insights that I developed:
quantifying the systematic nature of risk-on and risk-off behavior in markets
identifying asymmetry of risk enables taking greater market “risk” with no harm (i.e. greater returns with lower drawdowns)
identifying superior assets & asset classes at various points in the investment cycle (superior in terms of consistency of behavior and performance)
The nature of the economy; what drives business & market cycles; and why “soft landings” occur (which is very rare)
a new way to assess the yield curve, which is especially valuable in a low rate environment as old models lose their efficacy
I developed my trading algorithm with a specific objective in mind (no optimization required, it was insight-based. I built it and it worked first time, so never went back to try and tweak it)
… and lastly, what I consider the jewel in the crown of my research. Based on my personal understanding of the economy from my research, I figured that there should be an observable relationship between a certain structural element of the economy and market risk, so I went looking for this specific element and found it:
the amount of debt in the economy has a direct relationship to market fragility
These may not sound like much, written here as they are, but they are industry leading insights. I guess you’d have to be fairly experienced to appreciate them, so you’ll just have to take my word …. or not.
Incidentally, I uncovered a brand new insight this week, which we’ll look at a little later in this article. I keep wondering when I’ll stop finding new stuff, but I keep surprising myself after all these years.
Graphic novel
I introduced this article as a graphic novel, so I better start with the pictures.
In my last post, I mentioned how people in the U.S. who are living on their credit card are getting no relief from a lower Fed Funds rate. In addition to that, mortgage interest rates will have to fall a long way yet to be of any marginal benefit for U.S. households and the broader economy.
I think we can leave it until well into 2025 before we start counting our chickens on the interest rate relief front.
Average U.S. household credit quality has started to turn down. Last time that happened was during the GFC.
I found a couple of different sources for FICO data, so I took the more official version plus applied some of my own calculations to FICO’s available data (making some assumptions) to validate the findings.
I got into the FICO 8 scores after reading that a significant portion of U.S. households have maxed out their credit cards.
It’s true that the above could’ve only been temporary at any point over the last 2-years (especially with all the tech layoffs in 2022/23), but chances are, for a good portion of the 37% (“maxed out” or “near maxed out”) in the above chart (and probably a good portion of the 6% “prefer not to say” bunch), that they are more likely at or near maxed out now, with credit card interest rates at 23% and an economy that is slower and unemployment higher.
The new insight
As I poke around economic data, I notice differences in patterns and I wonder why.