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Brainstorms: Timeless Principles Expressed In Quantitative Metrics
A long time ago when I was studying hermeneutics, linguistics, discourse analysis and advanced grammar, a friend of mine engrained into me, “You need to prove your work.”
From the very beginning of my learning journey, I assumed that I couldn’t just throw ideas out there without actually showing WHY I held a specific view. Ironically, this is something we are born with but it’s typically beaten out of us as we get older.
Just think about how many WHY questions young kids ask. Then as we get older, we stop asking questions.
When I approach life, there are several principles I always keep in mind. However, when I approach any domain, I always quantify those principles with the specific language, data, and variables from that specific domain. In this article, I will lay out some of this process as it connects to markets but you need to realize that this is the TYPE of thinking and proof that can be (and should be) applied to any domain. Being multidisciplinary in this way is what allows you to be extemporaneous.
When operating under uncertainty, you want to match your patience with others’ impatience. (a principle I originally learned from the DAO of Capital)
Always have a different time preference and/or risk tolerance than the market. (a principle I originally learned from VitruviusCurve)
Quantifying Fundamental Principles:
Something I have learned over the years is that people will always speak in generalities but never quantify their fundamental views with quantitive metrics.
For example, “The market always moves between greed and fear.” While this might be true in theory and it is descriptive, you still need to prove it.
When I think about these principles of having a different risk tolerance or patience, there is a high degree of subjectivity to this. For example, what is impatience in the market? VIX at 20? VIX at 30?
This is similar to the whole value investing dilemma. Value guys will say they want to buy undervalued companies but how do you define value? PE? PB? Are you sure that will work?
Risk Premiums: Top Down/Bottom Up
When I think about markets, I break things into risk premiums. What is a risk premium? It is functionally what you get paid above the risk-free rate. We could write endless articles on the different types of risk premiums, how to quantify them, and why they function the way that they do.
Part of quantifying risk premiums is connecting them with growth, inflation, and liquidity. I talked extensively about this in the FX primer which can be found here:
I also touched on HOW you want to frame these various risk premiums in terms of GIP here:
The bottom line is that you want to quantify the fundamental principles I noted above with a robust quantitive process that allows you to account for how market cycles change.
The key qualification I should make here is that just because you can quantify fundamental principles with quantitive metrics, doesn’t mean the future becomes more predictable, it simply means you can express views with more precision. Why does this matter? Because defining risk-reward correctly is HOW you are able to manage your trading statistics (see risk management article on this: link).
Pulling It All Together:
When I think about all of the ideas I have laid out above, my goal is to have a clear connection between the fundamental principles I believe in, the quantitive expression of those, and how those specifically connect with my scenario analysis and risk management.
For example, if I have a specific way of quantifying a specific R:R setup, it will clearly connect to my scenario analysis with confirmation and falsification. From here, I will have a clearer picture of how I want to size the specific position.
I am currently in the process of writing the next comprehensive macro report for paid subscribers and I will be specifically focusing on showing this entire process for our current situation as we move into the end of the year and beginning of 2024. (If you want to see the previous macro reports, here they are: link and link)
Thanks for reading!