Managing Risk

John Doe
5 min readDec 6, 2022
The Three Sides of Risk, Morgan Housel

I’ve only heard the term “risk management” in the context of financial markets or business operations. In these two cases, the scope of risk management is limited to preventing financial losses and increasing financial gains. In everyday life, risk management has a much broader scope.

When you’re gambling in the stock market or running a business, you are playing a game with a simple objective — minimize losses and maximize gains. In life, you have to worry about that in addition to everything else that a person is responsible for. The game becomes much less simple because now not only do you need to minimize losses and maximize gains, you also need to determine the relative value of different outcomes and you can only do this by acting and gathering experience.

Risk management in the context of money is a survival and optimization game, in that order. Risk management in the context of life is a survival, valuation, and optimization game, in that order. People already have enough trouble with the first game, so it should come as no surprise that people have even more trouble with the second game.

The first thing you need to understand is that these two games are not the same. I say this because some people largely see the game of life as the game of money. If anything, the game of life is better seen as the game of time. The difference between two games is the valuation component. In the game of money, more money is better and less money is worse, case closed. In the game of life, you have to do the valuation yourself. Yes, all things held equal, more money is better, but there are so many other dimensions to consider.

For the sake of simplicity, we can treat the survival, valuation, and optimization games as independent. Texas Hold ’Em Poker is a good approximation for the optimization game but not for the survival game since it is missing the tail risk component. The multi-armed bandit problem is a good description of the valuation game:

The multi-armed bandit problem is a problem in which a fixed limited set of resources must be allocated between competing (alternative) choices in a way that maximizes their expected gain, when each choice’s properties are only partially known at the time of allocation, and may become better understood as time passes or by allocating resources to the choice.

There aren’t any good approximations for the survival game besides life itself. That’s part of what makes it so tricky to get good at.

In both games, emotions are best utilized as a data source instead of a decision maker when making decisions. Emotions signal value in the valuation game and danger in the survival game.

The most fundamental game here is the survival game, followed by valuation and then optimization. When I say A is more fundamental than B, I mean that any success you attain at B only matters if you aren’t failing A, with the converse not being true. If you fail to survive, it doesn’t matter how good you are at valuation or optimization because you’re dead. If you fail to value outcomes properly, it doesn’t matter how good you are at optimization because you’ll be optimizing for the wrong thing.

A good example of optimizing before valuing is the story of the man who works long nights and weekends to make more money for his family, justifying the extra time away from his family as “providing for them” and “making sure that they never grow up like I did”. Eventually, his wife divorces him and he realizes he doesn’t really know his kids. Ultimately, the man always regrets working the long hours he did and says something like “I would give it all back just to do it over again”. He skipped the valuation component and went straight to optimization, and in the end, all his optimizing was for nought.


The key to the survival game is not losing. When it comes to survival, there are many ways to lose and there is no way to win. Losing removes you forever, “winning” just means that you survive to see another day. If the key to the survival game is not losing, then the logical next step is avoiding terminal risks. Taleb has done a lot to outline what this strategy looks like in his books, so I won’t go into too much detail about it here.

What I will say is that the people who survive the longest in any domain or in life have a very conservative approach to these terminal risks and they listen to their gut when it comes to danger. Your gut isn’t always right about what is or isn’t dangerous, but it’s better to follow your danger instincts and miss out on something lucrative than it is to go against your danger instincts and get terminated. Again, I’m not saying listen to your gut all the time, I’m saying listen to your gut when it’s saying something is dangerous. If you do override the danger alarm, it better be for a very good reason. You will never really understand how this unconscious danger-detection system works, but it is foolish to ignore this system that was passed down to you through billions of years of evolution.


The key to the valuation game is to have a rough balance between exploration and exploitation (i.e. double-observing) and using your emotions as signal for value. It’s not important to find the mathematically optimal way to do this. In the long run, if you have a balance between exploration and exploitation, you’ll end up doing as well as anyone can reasonably ask for.


The key to the optimization game is divorcing decision quality from outcome quality. Conflating the two is called “resulting”, a term coined by Annie Duke. Resulting works fine when there is little to no randomness involved, but in life, the most important decisions are almost always made under significant uncertainty. People like certainty, and when the results come out, it is much more emotionally satisfying to come up with a reasonable explanation for the result post-hoc than admit you still don’t really understand what’s going on. The more uncertainty involved in a decision, the more randomness will play a role in the outcome. As uncertainty and randomness increase, the less reflective the result quality will be of the decision quality. The only way to overcome the randomness in these situations is through volume.

That’s a short summary of the optimization game. Professional poker players seem to have the best understanding of probabilistic decision making out of all the groups out there, most likely because Texas Hold ’Em poker is a game that involves decision making under significant levels of uncertainty.


In life, survival, valuation and optimization are not independent pursuits. The important thing is to understand the correct priority to the put them in and how to approach each pursuit most effectively.



John Doe

Processing information, stacking concepts. Writing this down so I don’t keep thinking about the same things over and over again