There's a decision most traders make after the trading is already over. Not during a trade. Not on a chart. It's the one that never shows up in a post-mortem.
It isn't the entry.
It isn't the stop.
It isn't even the size of the position.
It's what happens a few minutes, or a few days, after the account is already down, when a number gets typed into a deposit box.
There's a clinical checklist, used to diagnose a completely different kind of disorder, where this exact behavior is endorsed more often than any other item on the list, by a wide margin.
A 1976 study on business students found people do more of this, not less, under one very specific condition, and most traders meet that condition every single time.
One entire industry now has a dollar figure attached to it, a receipt for the exact same decision, paid out again and again by traders who never once changed what they were doing between attempts.
A simulation built for this report ran the decision 20,000 times. By the second repeat, one specific probability had already crossed 99%.
The clinical research, the 1976 study, the industry receipts, the simulation, and a hypothetical account walked through dollar by dollar are all laid out below, with the page number where each piece lives.
A Trading Habits Report
The Reload
Why redepositing into a losing trading account almost never buys back the loss.
- Length 20 pages, with 9 original charts and a worked hypothetical case study
- Author TradingHabits.com
- Format PDF, delivered as an instant download right after checkout
- Covers The clinical research and psychology behind redepositing after a loss, a 20,000-trader Monte Carlo simulation, real prop-firm rebuy economics, and a written rule to interrupt the pattern
This report breaks down the research, the math, and the numbers on one specific decision.
What's Inside
20 Things This Report Actually Says
- 01The 4 recognizable shapes this habit takes, and the smallest, most frequent one is the easiest to miss in your own account.Page 3
- 02Every drawdown ends at the exact same fork in the road. This report names precisely what separates the two paths from there.Page 4
- 03One behavioral marker shows up in more than 8 out of 10 people who meet the clinical threshold for a very different kind of disorder, and it isn't the one most people would guess.Page 5
- 04A 1984 definition, still used in clinical diagnosis today, pins the entire behavior down to a single motive in one short sentence.Page 5
- 05A 1976 study on business students found people commit more money to a failing decision under one very specific condition, not less.Page 6
- 06A 2023 study tested 5 different ways to spot this exact behavior in raw account data. The winning signal wasn't the size of any single transaction.Page 7
- 07One entire industry hands you a literal dollar receipt every time this pattern repeats. This report puts an exact number on what 3 repeats actually costs.Page 8
- 08There's a specific psychological side effect that shows up by the 3rd or 4th repeat in that same industry, and it isn't overconfidence.Page 8
- 09Roughly 7 out of 10 account failures in one funded-trading industry trace back to a single type of rule, and it isn't the one most traders blame first.Page 9
- 10A hypothetical $5,000 account gets rebuilt 3 separate times, and the percentage lost gets measurably worse with every single cycle.Page 10
- 11Add up everything that actually went into that same account against what was left at the end. The real number comes out more than double the size of the worst single loss along the way.Page 11
- 122 individual redeposits, looked at one at a time, each sound almost reasonable. Stacked together, they tell a completely different story.Page 12
- 13A 2-line chart where one line only ever goes up and the other keeps resetting, and almost no trading platform calculates the gap between them for you.Page 13
- 14A simulation splits 20,000 traders into two groups that differ by exactly one decision, built specifically to settle what one hypothetical case study alone can't prove.Page 14
- 15The median outcome in one simulated group came out more than triple the other, and the shape of the full distribution told an even worse story than the median did.Page 15
- 16By a 2nd reload, one specific probability has already crossed 99%. This report shows exactly where that same probability crosses 50% for the first time.Page 16
- 173 related trading habits usually get lumped into the same conversation, but only 1 of them requires bringing in money from outside the account entirely.Page 17
- 18A 5-part written rule is what actually interrupts this pattern, and the common thread running through all 5 parts has almost nothing to do with willpower.Page 18
- 19A 5-question checklist for the exact moment right before the next redeposit, and 1 of the 5 questions has nothing to do with money at all.Page 19
- 20The sources behind this report span a 1984 gambling book, a 1976 organizational-psychology study, and a 2023 account-tracking paper, and not 1 of the 3 was originally written about trading at all.Page 20
HABITS
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Behind The Report
Loss Chasing And Escalation Of Commitment
Each reload doubles the size of the last one. The math that's supposed to make you whole is the same math that tips the stack over.
The Concept
Chasing losses, in the clinical sense, means returning with more money specifically to win back what's already gone, instead of accepting the loss and stepping back. It's one of the nine criteria the DSM-5 uses to diagnose gambling disorder, and it's endorsed by more people who meet that diagnosis than almost any other single criterion on the list.
Redepositing into a drained trading account, or rebuying a failed prop-firm evaluation, is that same decision wearing different paperwork.
Where It Comes From
Sociologist Henry Lesieur wrote the defining early account of this behavior in his 1984 book The Chase: Career of the Compulsive Gambler, a title that names the pattern outright.
Separately, organizational psychologist Barry Staw ran a classic 1976 study, "Knee-Deep in the Big Muddy," in Organizational Behavior and Human Performance, finding that people commit more resources to a failing course of action specifically when they made the original decision themselves, not less. Corporate-strategy postmortems and analyses of Vietnam-era policy have both cited it since. The reload is that same escalation of commitment, run on a live trading account instead of a boardroom budget.
Each Reload Is Its Own Independent Roll
Illustrative only, built on a hypothetical 40% chance of full recovery per independent attempt, not the report's own modeled figures. The shape is what matters: each reload compounds against the last one, so the odds of still not being even climb fast rather than resetting to even money every time.
Try It: Stack Your Own Reloads
Same hypothetical used in the chart above, just adjustable: at a 40% recovery chance per attempt, the default here reproduces the chart's own four numbers almost exactly (small rounding differences only). Push the recovery odds up or down and watch how fast the odds of still not being even climb anyway. That's the compounding, not a worse trader.
Background only. The report itself runs a 20,000-trader simulation on what repeated reloads actually do to the odds of getting back to even.
Common Questions
Is "chasing losses" a clinical term, not just a trading habit?
Yes. It's one of the nine criteria the DSM-5 uses to diagnose gambling disorder, and it's endorsed by more people who meet that diagnosis than almost any other single criterion on the list.
What did Barry Staw's 1976 study actually find?
That people commit more resources to a failing course of action specifically when they made the original decision themselves, not less. It's been cited in corporate-strategy postmortems and analyses of Vietnam-era policy since, and the reload is that same pattern on a live trading account.
How fast do the odds of "still not being even" climb with repeated reloads?
Fast, because each reload is its own independent roll, not a fresh coin flip. In the report's illustrative example, using a 40% chance of full recovery per attempt, the odds of still not being even climb from 60% after one reload to 98% after four.