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One of the most underrated aspects of investing is understanding risk and the degree of risk you’re taking to achieve a given return.

I think many of us would like to think that we know what level of risk we’re taking in our efforts to generate alpha. Still, in reality, we allow ourselves to be clouded by our own ego (ex, the company will continue to grow at x% and re-rate), confirmation bias (ex, focusing on just the positives and downplay the negatives), and a successful track record (“hot-hand fallacy” = I’ve been doing so well the last few times that the next one will be great).

Risk gets downplayed during good times because when a rising tide lifts all boats, how can you lose? There have been a few periods over recent years where we’ve seen this trend: 2020 → Q2’21, 2024 → 2025. You could throw darts at a dartboard while blindfolded and hit something that would return money.

Hell, even Dave Portnoy at one point was picking stocks purely based on the Scrabble letters he pulled out of a bag.

Despite these recent euphoric times, it’s become very apparent that with the drawdown we’re experiencing in risk-on assets, generally tied to anything AI-related and a new war in the Middle East, we’re slowly coming to see who’s been swimming naked (i.e., nothing but beta).

Now, more than ever, it’s paramount to understand risk as all of us navigate uncharted waters with the threat of AI, flip-flopping foreign policy, a new “not a war” war, and an economy where absolutely no one knows where it’s going.

Speaking for myself, I’ve fine-tuned over the years how I analyze risk in an investment, largely through understanding not just myself as an investor but also my conviction in the investments I take positions in. Otherwise, how can we really learn about ourselves/style if we don’t make mistakes?

I’ve been able to sum up my risk tolerance/exposure into one simple fact: I optimize my risk to what allows me to sleep calmly at night.

If I take a position in something and it worries me (prevents me from getting a good night’s sleep), then I know I either don’t know the investment well enough, or I sized it wrong. As my fellow investor, Bill the Starfish (literally) would say, “position sizing is determined by downside.”

Now, there aren’t too many professional investors I try to emulate (think that’s the wrong mentality); however, there is one I’ve followed over the years that I have come to really respect.

Howard Marks did a breakdown the other year on how he interprets risk, and I found it a very interesting listen, full of points I tend to agree with. Below, I’ve broken down many of the principles he highlighted and included real-world examples from my own experience to help explain them.

This should help you understand either similarities with yourself or potentially areas where you might need to consider going forward.

Hope you enjoy.

Risk is not Quantifiable

Risk is the Probability of Loss

Howard Marks: Can’t be anything but an opinion in advance, and you can’t quantify it even after the fact. Was it a safe investment that was sure to 2x, or was it risky and you got lucky?

Risk is unquantifiable, even after the fact (i.e., in advance or in hindsight).

Example:

Not picking on this company either, but you could point to Rocket Lab's (RKLB) early days. Many bulls early on took the risk that early-stage rocket launches would succeed and prove the company was on track to launch more.

However, while the company would need to implement intense safety measures to ensure the rocket was stable (since there wasn’t an infinite amount of cash to keep making mistakes), that doesn’t mean it was perfect or near-perfect.

In hindsight, some rockets worked, and the stock rose. Some took that same logic on the long side only to have the rocket explode. So, was it a safe investment that developed into a good return? Or was it a risky investment that got lucky depending on when you first started buying?

Howard Marks: The risk of not taking enough risk. He really labels this as more of a “selling at the bottom” and a missed chance of recovery. By having near-term volatility shake you out, you believe you’re minimizing your portfolio risk by cutting your losses; however, for good companies, they tend to eventually bounce back and make higher highs. The issue is that you traded your way out of a situation where you should have been an investor, which meant you missed out on the eventual recovery.

My commentary: While it’s obviously not always the case, cutting your losses might seem like a good idea at the time since you don’t truly know where the bottom is, but having the pain threshold to endure a corrective drawdown, or even a prolonged one, could have you miss out on amazing recoveries.

Costco (COST), for example, experienced an >33% drawdown during the GFC. It is now up >2,200% since the bottom if you sold to “protect” yourself from more pain.

Howard Marks: We have ignorance, to some degree, about what the future holds. If we knew what was going to happen in the future, then there would be no risk.

We don’t have an appreciation for the things that are highly unlikely to happen. 96% of financial history has occurred within two standard deviations, but everything interesting has happened outside of 2 STDs.

Even though we might know what will likely happen, we don’t give enough thought to what is unlikely to happen → i.e, tail events.

Recent example: We know that Trump campaigned on no regime changes and being a peace-time president. However, we already saw him change country (Venezuela) and is actively bombing another (Iran), sending oil prices up ~24% in just ~10 days, and causing investors to become risk-off.

Again, what was once considered an unlikely outcome, but is now one that surprised everyone.

Howard Marks: The future should not be a fixed point but a range of outcomes, which translates into a probability. Even if you know the probabilities, it doesn’t mean it’s going to happen.

We can determine this by using a pair of dice. Based on the number of outcomes, we can, with certainty, know what the range of outcomes is (6 sides x 2 dice = 36 possible outcomes).

Even when you know the probabilities, it does not eliminate uncertainty.

“We live in the sample, not the universe.” → 36 possibilities, but only one outcome.

Howard Marks: The probability weighted average of possible outcomes could be irrelevant. Sometimes, the expected value isn’t even an option.

Ex: A course of action that has four possible outcomes: 2, 4, 6, and 8. An equal likelihood.

The weighted average of possibilities = 5. But 5 can’t happen because it’s not in the list of possibilities.

Additionally, some aspects that contribute to the outcome of #2 might not fall in the same outcome as #6. Thus, making one possibly more risky than the other.

Example:

Investing in special situations is a hard thing to do. Each situation is inherently different, even if the return profile is the same. Take, for example, comparing two M&A arb trades that are in different universes, but still yield the same return performance. Spread is 10% from the take-out price, and the close date is the same.

Which do you go with? You have to dig into the nitty-gritty to understand if the expected value is indeed an option that you’re looking for, and the risk meets that expected value.

Howard Marks: He gives two examples of this, which I think are great for explaining this point.

1) In Drachten, Holland, they removed traffic lights, signs, and road markings. Because of this, accident fatalities actually went down. How could that be? Well, traffic accidents went down because with no more aids to help them, people were more aware and attentive, which led to fewer accidents.

2) Counterintuitively, rock climbing is another good example. At its core, rock climbing is dangerous, but new gear consistently comes out to make it less dangerous for the climber. However, even though new advancements in gear slowly decrease the risk of injury or catastrophic outcomes, climbers take this as a reason to push the risk further. I.e, taking more risk.

“The risk of an activity doesn’t just lie in the activity in itself, but in how the participants approach it.”

Howard Marks: It’s only in times of testing, where investors’ strategies are tested with the amount of risk they’ve held.

Example:

Using California housing as the scenario. There might be a flaw in the design structure of the house that can live there unabated if nothing bad occurs. It’s only when an earthquake comes that the flaw is exposed and the house comes crumbling down.

Said another way, in the mid-2000’s, underwriting subprime mortgages was easy because nothing wrong was happening with late payments. It’s only after all the derivatives started blowing up, once a few percentage points of total MBS were defaulting, that everything came crashing down.

And one last recent example, with Silicon Valley Bank (SVB). They could still issue loans at very cheap LT loans while rates were low, and nothing bad would happen. It’s only when the FED started raising rates aggressively that they found themselves quickly underwater, and the bank went under.

It could look like a winner or safe for a long time, even though it isn’t.

Howard Marks: There’s a belief that high-quality assets are safe, and low-quality assets are risky. A high-quality asset can be priced so high that it ends up being risky.

Example:

Investing in the “nifty-fifty.” Investors bid up the top 50 companies in 1969 because they were of such high quality that the likelihood of anything happening to them was thought to be low. However, if you bought them in September 1969 (when Howard started on Wall Street) and held them for the next five years, you lost more than 90% of your money.

The prices you paid were just too high to be sustainable. The quality alone, or the perceived quality, did not make them any less risky than they actually were.

On the other hand, a low-quality asset could be cheap enough to be safe because the market has already left it for dead.

Howard Marks: Investment success doesn’t come from buying good things, but buying good things well.

There are no assets that are so “good” that they can be bid up to any price and become less dangerous. There are very few assets that are so bad that they can’t be cheap enough to become attractive.

Howard Marks: The common misconception is that riskier assets = a higher return. If it were true, then they wouldn’t actually be risky, because then everyone would only buy them.

The real take here is that investments that are perceived to be risky have to be perceived as offering higher returns to induce people to make those investments. The problem here is that they don’t have to deliver on it.

It’s from the possibility that the projected returns will not be delivered that the risk ensues.

Positive correlation between risk and return is a mirage → the range of possibilities (tails) becomes wider.

Howard Marks: While we like to be aware of the level of risk that we’re taking, we need to understand that the probabilities of them occurring will make it so that we either forego a permanent loss of capital or give up the option of a higher return due to our evaluation of risk-taking.

Just because certain outcomes don’t materialize does not mean that you made the wrong choice in the level of risk you took.

Example:

By law, every driver on the road needs to have auto insurance. You pay for it every year, and it gives you peace of mind that if anything did happen, you would be (presumably) covered. At the end of the year, you don’t get upset and wish that you had never spent money on the policy to begin with because you never had an accident.

Howard Marks: Risk is best handled on the basis of accurate, subjective judgments made by experienced expert investors who emphasize risk consciousness.

Outstanding investors are outstanding for the simple reason that they have a superior sense for the probability distribution that governs future events, and whether the potential return compensates for the risks that lurk in the distribution’s left-hand tail.

As always, we appreciate your support of our work. If you have any questions, please message or comment below. If you think others would benefit from the research/commentary we release, we would greatly appreciate your sharing.

Until next time,

Paul Cerro | Cedar Grove Capital Management

Personal Twitter: @paulcerro

Fund Twitter: @cedargrovecm

Fund Website

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