The house money effect is the tendency to take more risk after a gain, as if profit you have just made is not really yours. Richard Thaler and Eric Johnson documented it in 1990. In trading it shows up as bigger size and looser setups after a strong start, which is how a green morning becomes a red afternoon.
The name comes from the casino: money won at the table feels like the house's money, so losing it does not hurt in the same way. Your broker does not see it that way. A dollar of today's profit is exactly as much yours as a dollar of your deposit.
What did Thaler and Johnson find?
In a series of experiments on risky choice, they found that prior outcomes change how much risk people take next (Thaler and Johnson, 1990). They described two effects:
| After | Effect | What it looks like in trading |
|---|---|---|
| A gain | House money effect: more willing to take risk | Doubling size after two winners, taking B-setups because you are up |
| A loss | Break-even effect: options that offer a way back to zero look especially attractive | Revenge trading to get back to flat |
Together they explain why both green and red days can end in overtrading. The break-even side is covered in revenge trading and thesunk cost fallacy.
What does the house money effect look like in trading?
- Raising size after two or three winners, "because the risk is covered by today's profit".
- Taking setups outside your plan because you can afford to lose on them.
- Widening a stop on a trade you would normally cut.
- Trading the session you usually skip, simply because you are in the green.
- Giving back the whole day, then trading on to recover it. This is the green-day giveback in how to stop overtrading.
The pattern is described from the inside inovertrading after a win.
Is it the same as the hot-hand fallacy?
They often travel together but are different. The hot-hand fallacy is a belief: a winning streak means you have found something and the next trade is more likely to win. The house money effect is about risk: losing profit feels cheaper than losing capital, so you are willing to bet more of it. The hot-hand fallacy is covered ingambling fallacies in trading.
How do you protect a winning day?
- Keep the same risk per trade all day. Size does not go up because the day is green.
- Count trades on green days too. A daily trade limit caps a winning day exactly as it caps a losing one.
- Decide your stopping point after a win in advance, for example stop after reaching 2R, and write it down before the session.
- Make the cap automatic. EmotionLock counts your real MT5 trades and blocks your trading apps when you reach your limit, whether you are up or down.
The house money effect is one of the biases in our guide totrading psychology, alongside thedisposition effect.
Sources
- Thaler, R. H. and Johnson, E. J. (1990). Gambling with the House Money and Trying to Break Even: The Effects of Prior Outcomes on Risky Choice. Management Science, 36(6).
- Kahneman, D. and Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2).
Frequently asked questions
What is the house money effect?
The house money effect is the tendency to take more risk after a gain, because recently won money feels less like your own. Richard Thaler and Eric Johnson described it in 1990. Its mirror image is the break-even effect: after a loss, options that offer a way back to zero look especially attractive.
What is an example of the house money effect in trading?
A trader is up 3R by mid-morning, doubles their position size because the risk feels covered by the day’s profit, takes two setups outside their plan and finishes the day red.
Is the house money effect the same as overconfidence?
Not quite. Overconfidence is believing your skill or information is better than it is. The house money effect is about treating recent gains as cheaper to lose. They often show up together after a winning streak.
How do I stop overtrading after a winning day?
Keep the same risk per trade all day, decide in advance where you stop after a win, and use a daily trade limit that applies to green days as well as red ones, ideally enforced by software rather than willpower.