Direct answer
A worked example of revenge trading is a step-by-step scenario that shows how a person might react to a loss by entering another trade (often larger or faster) with the goal of “getting back” money. The example should separate what is stable about the behavior—loss-driven escalation—from what is variable—market movement, execution, spreads, and fees.
Mechanism and definition
Revenge trading is a behavioral pattern: after experiencing an undesired outcome (commonly a loss), the trader feels pressure to undo it and continues trading in a way that is driven more by emotion than by the original plan. A “worked example” makes that behavior observable by documenting:
- The starting point (trade result and remaining account state).
- The new decision rule (for instance, “increase size to recover quickly”).
- The explicit assumptions used to calculate profit and loss (P&L).
To keep the mechanics general, this article uses a simplified model. In real trading, forex P&L depends on instrument contract details, price movements, leverage, margin requirements, and trading costs. Those elements can be treated as variables in the scenario.
Evidence or example (worked numerical scenario)
Below is one transparent scenario using clear assumptions. It is not a prediction.
Assumptions (state all inputs)
- Account equity at the start: $1,000.
- Each trade uses a fixed “position value per pip” simplification: $1 P&L per 1 pip move, per trade size unit.
- Trade 1 uses size unit S=10, so $10 P&L per pip.
- Trade 1 entry price is followed by a move of +15 pips against the position, producing a loss of 15 pips.
- Trading costs for both trades are ignored in the calculation (set to $0) to isolate the behavior mechanics.
- After Trade 1, the trader feels compelled to recover the loss and increases size to S=14 for Trade 2.
- Trade 2 experiences a move of +5 pips against the position (still losing), showing a plausible failure mode.
Step-by-step
Trade 1
- Loss pips: 15 (against the position)
- P&L per pip: $10 (because S=10)
- Loss = 15 pips × $10/pip = -$150
- New equity (ignoring costs) = $1,000 − $150 = $850
Revenge-driven decision
- The behavior change is the size increase from S=10 to S=14.
- The implicit goal is “recover the prior loss faster,” which increases exposure.
Trade 2
- Loss pips: 5 (against the position)
- P&L per pip: $14 (because S=14)
- Loss = 5 pips × $14/pip = -$70
- New equity = $850 − $70 = $780
What this example demonstrates
- The stable “worked example” takeaway is behavioral escalation: the second trade is larger because the trader is trying to fix an emotional outcome, not because a plan was improved.
- The variable part is market movement: even if Trade 2 is “less bad” in pips, larger size can still produce continued losses.
Limitations and risks
A worked example can clarify mechanics, but it does not guarantee or forecast outcomes. Material limitations include:
- Costs and execution are omitted or simplified. Real spreads, commissions, slippage, and swap/financing can materially change P&L.
- Market conditions are variable. A move that is small in pips can still be large in account impact if leverage or contract sizing differs.
- Compounding loss is a failure mode. Revenge trading often increases exposure after a loss; if losses continue, equity can decline quickly.
- Behavior can distort decision rules. Even if a person believes they are “correcting” a trade, the emotional driver can lead to overriding pre-set risk limits.
Independent verification should focus on facts the reader can check: the actual trade timestamps, entry/exit prices, position sizing, and documented costs from a trade ledger. Historical patterns do not establish future results.
Verification and next question
To verify the concept using your own data, compare your pre-loss plan to your post-loss actions. Look for evidence of escalation (larger size, faster re-entry, abandoning the original criteria) after a loss.
If you want, a next worked example can be created using your preferred assumptions (for example, include a fixed cost per trade, a realistic pip-value model, or a margin constraint).