In the experiments behind prospect theory, people consistently refused gambles where they could win more than they could lose — the psychological weight of a loss is roughly double that of an equal gain. Your P&L column is not read by a calculator; it is read by that asymmetry. A ₹5,000 open loss feels like a ₹10,000 event, and closing it converts painful-but-hopeful into painful-and-final. The brain will bend a lot of rules to avoid that conversion.
- Held losers. “It will come back” is loss aversion speaking — holding keeps the loss unreal.
- Widened or deleted stops. The stop exists to cap the loss; moving it postpones the pain of finality.
- Averaging down. Adding to a loser lowers the price at which the pain would end — while doubling the risk.
- Winners cut short. An open profit is something that can now be “lost,” so the bias pushes you to lock it instantly — the disposition effect (see the companion guide).
- Post-loss paralysis or revenge. A realised loss demands relief — either freezing on the next valid setup or firing a revenge trade to erase it.
Stop placed with the order, never widened. The decision about the loss is made before the pain exists to argue with it.
Reframe the stop as a business cost. A capped, planned loss is the premium paid to test a setup — taking it calmly is execution, not failure.
Size so the loss is bearable. Loss aversion scales with the size of the potential loss; a position small enough to lose calmly is a position you can manage rationally.
Ban averaging into losers, in writing. One sentence in your plan removes the bias’s favourite move.
Review in R-multiples, not rupees. Measuring outcomes as risk-units (−1R, +2R) strips the emotional weight the rupee figures carry.
The staged process for when a big loss has already happened is covered in recovering after a big loss, and the original deep-dive lives in the loss aversion blog guide.