Prospect Theory - Why Losing Hurts More Than Winning Feels Good
You know that feeling when you lose a $20 bill on the street? It ruins your whole afternoon. But finding $20 on the street? Nice, sure. You smile for maybe five minutes and forget about it.
That asymmetry is not a character flaw. It is how human brains are wired. And two psychologists, Daniel Kahneman and Amos Tversky, built an entire theory around it back in 1979.
Chapter 9 of Burton and Shah’s book breaks down this theory. It is called prospect theory, and it changes how we think about risk, money, and investing.
Everything Starts With a Reference Point
Traditional economics assumes you make decisions based on your total wealth. Like, you have $150,000 in savings, and every financial choice you make is calculated against that number.
Here’s the thing. Most people cannot even tell you their total net worth within a reasonable margin. You might have a rough idea, but you are not running precise calculations in your head before deciding whether to buy that coffee.
So if people don’t think in terms of total wealth, what do they think about?
Gains and losses. From wherever they are right now. That “wherever they are right now” is the reference point.
Kahneman demonstrated this with a clever experiment. He gave people two sets of choices that look different but are actually identical in outcome.
Set 1: You get $1,000 for free. Now pick: take another $500 for sure, or flip a coin for a chance at another $1,000 (or nothing).
Set 2: You get $2,000 for free. Now pick: lose $500 for sure, or flip a coin where you might lose $1,000 (or lose nothing).
Both sets give you the same final amounts. You either end up with $1,500 for sure, or you take a 50/50 shot at $1,000 or $2,000. The math is identical.
But people chose differently. In Set 1, most people took the safe $500 gain. In Set 2, most people gambled to avoid the sure loss.
Why? Because the reference point changed. In Set 1, your brain sees gains and plays it safe. In Set 2, your brain sees losses and suddenly becomes a risk taker.
This is a big deal. Traditional economics says your risk preference should stay the same regardless of how the question is framed. But it doesn’t.
The S-Curve
Kahneman and Tversky mapped out how people actually feel about gains and losses. The result is an S-shaped curve.
On the gains side, the curve bends like a hill. You feel good about your first $100 gain, but the next $100 doesn’t feel quite as sweet. Going from $900 to $1,000 doesn’t feel as different as going from $0 to $100. The curve flattens out. Economists call this concave. It means you are risk averse when dealing with gains. You prefer a sure thing over a gamble with the same expected value.
On the losses side, the curve flips. It bends the other way. Losing the first $100 stings, but going from $900 lost to $1,000 lost doesn’t feel that much worse. You are already hurting. So when you face potential losses, you become a gambler. You take risks trying to avoid or recover from losses. Economists call this convex, and it means risk-seeking behavior.
Here is a quick example. Pick one:
- Get $900 for sure, or
- 90% chance of getting $1,000
Most people take the sure $900. Now flip it:
- Lose $900 for sure, or
- 90% chance of losing $1,000
Now most people take the gamble. Same math, different feelings. When facing losses, we become risk lovers hoping to dodge the bullet.
Loss Aversion: Losses Hit About Twice as Hard
But the S-curve has another important feature. The loss side is steeper than the gain side. Meaning a $100 loss hurts more than a $100 gain feels good.
How much more? Research suggests roughly 1.5 to 2.5 times more. So you need to win about $200 to make up for the pain of losing $100.
Here is the classic test: would you take a coin flip where you win $150 or lose $100? The expected value is positive ($25 on average). A purely rational person should take it. But most people say no. The potential loss of $100 scares them more than the potential $150 gain excites them.
Mathematician Matthew Rabin showed that traditional utility theory cannot explain this properly. If you use the old models and assume someone rejects that small gamble, you end up with absurd predictions. Like that same person should also reject a 50/50 bet between losing $600 and winning literally any amount of money, no matter how large. Billions, trillions, doesn’t matter. The old model says they’d still say no.
Nobody actually behaves like that. So the old model breaks down. Loss aversion is real, and you need prospect theory to explain it without getting ridiculous results.
The Path Matters
Loss aversion creates another problem for traditional economics. It makes your happiness path dependent.
Say you gain $500 on Monday. Nice. Then you lose $500 on Friday. Traditional economics says you are back where you started, no change in happiness. Net zero.
But prospect theory says that is wrong. You felt good about the $500 gain on Monday. Then you reset your reference point. Now on Friday, you lose $500 from your new reference point. And because losses hit harder than gains, the pain of Friday’s loss outweighs Monday’s joy.
You end up feeling worse than when you started, even though your net financial position is unchanged.
This is why checking your stock portfolio every day is emotionally brutal. Every little dip hurts more than every little rise feels good. The more often you look, the more pain you accumulate, even if the overall trend is positive.
And this has real consequences for markets. Burton and Shah point out that how frequently investors check their portfolios can affect their investment decisions and even contribute to market premiums that traditional risk models cannot explain.
Where Prospect Theory Falls Short
The book is honest about the limits. Prospect theory is better than the old models, but it doesn’t explain everything.
Problem 1: Disappointment. Consider three scenarios:
- 1 in 1,000 chance to win $1 million, and you win nothing.
- 90% chance to win $10, and you win nothing.
- 90% chance to win $1 million, and you win nothing.
Winning nothing technically has the same “value” in all three cases under prospect theory. But emotionally? The third one is devastating. You were already planning what to do with that money. Prospect theory cannot capture that level of disappointment properly.
Problem 2: Regret. Imagine you choose a 90% gamble for $1 million over a sure $10, and you lose. Annoying, but okay, you only missed out on $10. Now imagine you chose that same gamble over a sure $100,000, and you lose. That is crushing. You gave up a guaranteed $100,000 for nothing.
Prospect theory assigns the same value to “getting nothing” in both cases. But the regret is completely different. The theory has no way to account for that.
What This Means for Your Investing
Even with its flaws, prospect theory explains a lot of real investor behavior.
It explains why people hold losing stocks too long. You are in “loss territory” on the S-curve, so you become a risk seeker, gambling that the stock will recover instead of cutting your losses.
It explains why people sell winning stocks too early. You are in “gain territory,” so you become risk averse. You lock in the profit because a bird in hand feels safer.
It explains why checking your portfolio daily makes you miserable and leads to worse decisions. Every small drop triggers loss aversion. Over time, that emotional weight pushes you toward overly conservative choices.
And it explains why market crashes feel so much worse than market rallies feel good. A 30% drop in your portfolio is not simply the mirror image of a 30% gain. The drop feels roughly twice as painful.
So here is the practical takeaway. Your brain is not built for calm, rational investing. Knowing about loss aversion won’t make it disappear. But at least you can recognize it when it is driving your decisions. And maybe, just maybe, you can pause before selling that dip or chasing that recovery gamble.
That awareness is worth more than most trading strategies.
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