A coin makes a fast move while your feed fills with screenshots. Or a trade closes at a loss and the next idea suddenly feels like a way to get the money back. Those moments are often called FOMO and revenge trading. The labels are informal; the decision record is more useful. What was knowable before the urge, what rule was already written, and what evidence changed?
FOMO and loss-chasing are different triggers
Fear of missing out is the pressure to act because an opportunity appears rare, popular or already rewarding other people. A missed entry can create that pressure even when no position was open. Revenge trading describes a different sequence: a recent loss becomes a reason to take another trade, increase exposure or relax a rule in order to recover it. They can overlap, but they are not the same event, and a journal should record the observable trigger rather than diagnose a person.
Ask what information would still matter if the screenshot, post or last trade were removed. A public claim, a rising candle, a missed move and a red balance can prompt a review; none by itself establishes an entry condition. If the idea only looks valid after seeing the move, mark it as a new hypothesis. Do not edit the earlier plan to make it appear as if the signal was expected.
What the crypto research actually tested
Friederich and co-authors’ 2024 Psychology & Marketing study record and abstract reports five studies with eight experiments on externally presented FOMO appeals. The authors conclude that these appeals can influence crypto investment decisions, with affective processes mediating the effect and impulsivity moderating it. The abstract also reports repeated investment decisions after prior losses. These are findings from the reported experimental settings; they do not measure exchange-level “revenge trades,” show that all traders respond alike, or establish what any reader should trade.
That is evidence that a deliberately framed appeal can affect choices in those study settings. Much of the evidence concerns stated intention, short vignettes or small lab stakes. The authors explicitly discuss the gap between intention and behavior. It does not measure the frequency of “revenge trades” on an exchange, prove that every trader responds alike, or show that a pause routine prevents losses. Read the experiment as a reason to inspect how urgency enters a decision, not as a treatment result.
Market-level attention research asks another question. Suardi, Rasel and Liu’s 2022 Bitcoin study found that their attention measure predicted trading volume but not returns; sentiment dispersion was associated with greater return volatility. Al Guindy’s study used roughly 25 million posts about 23 large cryptocurrencies and reported that its attention measures predicted future volatility. Samples, attention definitions and models differ, and a relationship with activity or volatility is not a directional signal for a particular coin or a user’s next trade.
Barber and Odean’s 2000 study abstract reports that, among 66,465 U.S. discount-broker households trading common stocks from 1991 to 1996, the highest-turnover group earned an 11.4% annualized net return compared with 17.9% for the market benchmark. It is historical stock-account evidence about turnover and net performance, not a crypto study or a test of emotional decision-making. It supports counting all activity and costs; it cannot tell an individual what to trade.
A review routine for the moment the urge appears
First, preserve the timestamp and the source of the trigger. Note whether it was a missed move, social post, new loss, unusual price move or something else. Capture the plan version and the data visible at that moment. Avoid writing a motive as a fact: “saw three posts claiming a listing” is observable; “the market was about to leave me behind” is an interpretation.
Second, open the rule that existed before the move. Can you name the asset and venue, the completed-bar or event condition, the entry convention, the invalidation and the maximum exposure? If the answer is no, record “no prewritten setup” and do not turn the pause into an improvised signal. If a rule does apply, check whether its conditions are actually met using the declared data source and timing.
Third, run the mechanics separately from the emotion. Is the instrument spot, a linear perpetual or another contract? Which price is used for the trigger and for risk? What fees, spread, slippage, funding, collateral and liquidation rules belong in the estimate? If one important input is missing, leave it unknown. A screenshot or an exchange last trade may not answer every execution or margin question.
Fourth, use any cooling-off interval or second-person review that your plan established in advance. There is no universal timer supported by the studies above. If you have no written pause rule, do not invent a duration and call it evidence-based. You can still record the urge and review the decision later without entering a trade.
| Trigger | Record in the moment | Later review question |
|---|---|---|
| Price moved without you | Prior rule, visible data, and whether an order existed | Was a stated condition met before the move, or only after it? |
| A loss just closed | Planned or actual exit, known costs and next planned action | Did the next decision follow the old rule or a recovery target? |
| A post claims an imminent catalyst | Link or source, timestamp and claim wording | Was the claim independently verifiable at decision time? |
| No setup or cost input is clear | What is missing; leave the result unclassified | What evidence would be needed before testing this idea? |
Review the decision before judging the result
Add the eventual outcome in a separate field. A planned trade can lose; an unplanned trade can win. Neither result changes what was knowable at entry. Include skipped, cancelled and out-of-plan decisions as well as closed trades. Otherwise the journal can miss the exact moments when urgency changed the process.
When you review a defined sample, set its dates and classification rules first. Keep records with missing timestamps, plan versions or fills visible as unknown instead of forcing them into “followed” or “broke the rule.” A handful of notes can identify an evidence gap; it cannot establish a stable psychological pattern or a profitable strategy. If you change the rule after reviewing results, save a new version and test it on later data.
The CFTC warns that virtual-currency trading, particularly leveraged futures, carries substantial risk. This is not a mental-health assessment. If trading is disrupting sleep, relationships or essential spending, stepping away and speaking with a qualified professional or trusted support service may be more appropriate than another worksheet. SuperQuant’s journal preserves user-entered notes; it does not diagnose emotions or recommend trades.
For a reusable record, see the crypto trading journal, weekly review and trading-plan template. This page is process education, not individualized investment or health advice.