I wanted to go with “The Most Mind-Blowing Study In Investing,” which, at least from my perspective, would’ve been true. But it would’ve sounded too clickbaity.
This looked very promising in the beginning, because I too believe that risk=volatility is oversimplified model. However, it turned out to be very disappointing due to misuse of maths. If you know something for sure this is not a random variable anymore therefore volatility doesn't make sense (i.e. it's 0).
One of the core points of the piece is precisely that reducing something as multifaceted as “risk” to a single mathematical quantity, something we can compute “objectively”, is a category error.
If we take “risk = volatility” as an axiom, then measuring volatility cannot establish that the axiom is correct; it just operationalizes the assumption. In that sense, you can’t refute or validate the axiom from within the same framework, you’ve defined the conclusion into the premise.
For those two reasons, I didn’t use, and couldn’t use, the standard mathematical tools that assume risk equals volatility.
That’s why I used a reductio ad absurdum: syllogisms and basic logic to show that the identification “risk = volatility” leads to contradictions or unintuitive implications in certain edge cases.
Also, even if I know volatility will occur with certainty, that doesn’t mean it ceases to be uncertain in the relevant sense: I may still not know when it will materialize or how large the move will be. The uncertainty is about timing and magnitude, not about whether price variation exists at all.
You can certainly challenge my interpretation of what “risk” should mean, because that part is, unavoidably, partly philosophical. But I don’t think your objection undermines the method I’m using to argue that “risk = volatility” is an inadequate definition.
Practice and theory is a large gap. The human brain is not designed for volitity. Fear/flight is embedded in our psychology. To master that is to master investing.
I have worked with effective people in normal times who collapse in panic with life and death threats. The time spent assuaging your fear is enough to kill you, sometimes. This especially applies in war situations, i.e. in theater.
I would’ve agreed with you 10 years ago, but much less so today.
I’d even say that dealing with noise volatility is a relatively easy problem to solve. Time teaches that lesson quickly, and very explicitly.
Speaking from experience: I’m a highly concentrated investor, mostly in sub-$500M market caps, sometimes even below $10M. I’ve already watched my portfolio drop 20% in a single day without it bothering me. Noise volatility stopped being an issue a long time ago, but it felt very different early on.
What still hurts performance are other, harder problems: distinguishing noise volatility from signal volatility (i.e. the business actually deteriorating), position sizing, timing exits, estimating opportunity cost, and so on.
Clearly, mastering volatility is just a small step toward mastering investing, in my opinion.
Hey, great read as alaways. That line about applied mathematics producing equations that stay close to reality really hit home. So true for many fields, not just finance.
I think the most surprising example I know (at least one that’s somewhat “rigorous”) is the early 20th-century physiologists and psychologists who tried to find an equation for motivation and performance.
They were using variables like heart rate, blood pressure, and so on. At the very least, they were imaginative.
If you have any truly outlandish examples, I’m all ears.
You could do the same at the roulette table. Use a martingale system. Play red or black. Double the bet when you lose, and start again at 1 when you win. For most people it is a winning system, except for the one who lose their whole capital, by doubling too often.
I really enjoyed that! Great insight and food for thought. Thanks for sharing
I’m glad you liked it, I enjoyed writing it too. Thanks for your feedback!
Buy and hold , hold , hold Great companies …. That is the force that keeps volatility at bay .
This looked very promising in the beginning, because I too believe that risk=volatility is oversimplified model. However, it turned out to be very disappointing due to misuse of maths. If you know something for sure this is not a random variable anymore therefore volatility doesn't make sense (i.e. it's 0).
One of the core points of the piece is precisely that reducing something as multifaceted as “risk” to a single mathematical quantity, something we can compute “objectively”, is a category error.
If we take “risk = volatility” as an axiom, then measuring volatility cannot establish that the axiom is correct; it just operationalizes the assumption. In that sense, you can’t refute or validate the axiom from within the same framework, you’ve defined the conclusion into the premise.
For those two reasons, I didn’t use, and couldn’t use, the standard mathematical tools that assume risk equals volatility.
That’s why I used a reductio ad absurdum: syllogisms and basic logic to show that the identification “risk = volatility” leads to contradictions or unintuitive implications in certain edge cases.
Also, even if I know volatility will occur with certainty, that doesn’t mean it ceases to be uncertain in the relevant sense: I may still not know when it will materialize or how large the move will be. The uncertainty is about timing and magnitude, not about whether price variation exists at all.
You can certainly challenge my interpretation of what “risk” should mean, because that part is, unavoidably, partly philosophical. But I don’t think your objection undermines the method I’m using to argue that “risk = volatility” is an inadequate definition.
Practice and theory is a large gap. The human brain is not designed for volitity. Fear/flight is embedded in our psychology. To master that is to master investing.
To master that is to master life.
I have worked with effective people in normal times who collapse in panic with life and death threats. The time spent assuaging your fear is enough to kill you, sometimes. This especially applies in war situations, i.e. in theater.
I would’ve agreed with you 10 years ago, but much less so today.
I’d even say that dealing with noise volatility is a relatively easy problem to solve. Time teaches that lesson quickly, and very explicitly.
Speaking from experience: I’m a highly concentrated investor, mostly in sub-$500M market caps, sometimes even below $10M. I’ve already watched my portfolio drop 20% in a single day without it bothering me. Noise volatility stopped being an issue a long time ago, but it felt very different early on.
What still hurts performance are other, harder problems: distinguishing noise volatility from signal volatility (i.e. the business actually deteriorating), position sizing, timing exits, estimating opportunity cost, and so on.
Clearly, mastering volatility is just a small step toward mastering investing, in my opinion.
Hey, great read as alaways. That line about applied mathematics producing equations that stay close to reality really hit home. So true for many fields, not just finance.
Thanks for your feedback!
I think the most surprising example I know (at least one that’s somewhat “rigorous”) is the early 20th-century physiologists and psychologists who tried to find an equation for motivation and performance.
They were using variables like heart rate, blood pressure, and so on. At the very least, they were imaginative.
If you have any truly outlandish examples, I’m all ears.
You could do the same at the roulette table. Use a martingale system. Play red or black. Double the bet when you lose, and start again at 1 when you win. For most people it is a winning system, except for the one who lose their whole capital, by doubling too often.
I honestly don’t see the connection between anything in my post and a martingale. A bit more detail would be appreciated.