Safar Choriev - Life & Econ

Let’s say you are offered a choice. To take 50$ as granted or to risk it and gamble for heads/tails with one being 100$ and the other 0$. A risk-averse person would choose the first option, but what does it tell us?

In economic terms, risk aversion is the preference for a certain, lower-payoff outcome over an uncertain, higher-payoff outcome.

The concept here is of diminishing marginal utility. Say, you are given 100 chocolates to EAT in one day. With each chocolate you eat, the next one will be less tasty and less wanted. The same logic applies here. Each additional dollar you may potentially get from gambling adds only a little value. At the same time, the risk of not getting that FIRST chocolate, the one that brings with itself the highest value, or in our case 50$ that are guaranteed, is not worth it for the majority of people.

Risk aversion ≠ loss aversion

Risk aversion is about preferring certainty to variance, while loss aversion is about weighing losses more than equal-sized gains (losing 100$ feels more painful than is feeling of happiness when one gets 100$)

Economists regard people as rational creatures, and risk aversion is one of the concepts that supports that idea of rationalism and here is why:

Ruin beats return. If a downside can trigger irreversible damage (expulsion, debt spiral, reputational or health ruin), the expected value is secondary. First apply a ruin filter (eliminate options with non-negligible ruin), then optimize among the survivors.
Sequencing and bankroll constraints. You don’t live in expected values — you live through paths. A small positive-edge bet repeated many times is attractive; the same edge in a one-shot, all-or-nothing decision is not. If you can’t survive early losses, you never reach the favorable long run. Size risks so that a losing streak doesn’t knock you out of the game.
Ambiguity and model error. When odds are uncertain (new markets, unfamiliar strategies), it’s rational to demand a margin of safety or buy information first (pilot tests, small trials). You’re not “afraid of risk”; you’re pricing unknowns and estimation errors that expected value alone ignores.

I first came to this term, while having a podcast with a Williams Professor in the field of Behavioral Economics and we were going over the “inconsistent choices” and what they tell us. In the study we discussed, people made multiple switches between safer and riskier options, something that risk aversion models say should not happen.

Brief description:

Normally, a risk-averse person will make one switch from choosing the risky option to the safe one as the lotteries get worse (for example, moving from gamble to sure thing). But if someone first switches to the safe choice and then later switches back to a riskier choice, the pattern is inconsistent with standard theories (like expected utility — satisfaction or benefit you can anticipate from a choice when the outcome is uncertain) because it implies the same person both prefers a safer lottery over an intermediate one and a riskier lottery over that same intermediate option. In the experiment, each subject answered a sequence of paired lottery questions (first all gains then losses), and a coin flip determined one payoff for payment. If a subject chose “safe” in one question and then later chose “risky” in another, that was counted as an inconsistent choice or mistake. Peoples’ risk decisions are not only about preferences but also about mistakes.

My suggestions to be more risk-averse would be to:

Never risk ruin
If a choice has any real chance of irreversible harm (health/legal/expulsion/financial ruin), kill it. Only then pick the highest-EV option among the safe ones.
Say it in human terms.
Turn every probability into a frequency (“5%” → “1 in 20”) and read it in both frames (“gains” and “losses”). If your preference flips, you’re reacting to wording — rethink.

Risk aversion is not a bug in human judgment, it is a feature that keeps us alive. But left on autopilot, it can also make us turn down good opportunities just because they feel fuzzy or are framed to scare us. The fix isn’t to “love risk.” It is to choose uncertainty on your terms: avoid outcomes that can end your game, size bets so you survive the path (not just the average), and buy information when the odds are unclear.