Video: If You're About To Quit Trading, Watch This
Creator: Etienne Crete – Desire To TRADE
Original Video: Watch the original video
Difficulty: Intermediate
The Big Idea
A flat account can conceal better execution, but it can also reflect a weak method or unfavorable costs. The source argues for judging process, using a meaningful sample, and reducing financial pressure. The useful application is a bounded review that can justify continuing, modifying, pausing, or stopping—not a promise that a breakthrough is near.
Three Problems That Require Different Evidence
The creator describes three reasons a trader may abandon an approach: skill improvements are not yet visible in profit, a method is judged from too few trades, or financial and lifestyle pressure makes the learning period unsustainable. These are plausible mechanisms, not a diagnosis of every struggling account.
The source itself acknowledges that trading may not suit everyone. Its broader suggestion that many people quit just before improvement is not backed by a complete population of those who continued and those who stopped. A survivor’s experience cannot establish that the next month will reward persistence.
| Problem | Evidence to collect | What would not settle it |
|---|---|---|
| Execution progress | The same written adherence score over time. | Feeling more confident or calmer. |
| Method uncertainty | Complete outcomes, costs, sample definitions, and conditions. | A few wins or a losing streak alone. |
| Unsustainable pressure | Affordable exposure, time budget, and practical constraints. | A deadline for replacing employment income. |
Keeping those questions separate prevents an execution improvement from being mistaken for proof that the method works. It also prevents a poor financial result from automatically being interpreted as a personal failure.
Use Two Scorecards, Not One Replacement Score
The source recommends asking after every trade whether the plan was followed and calculating the percentage each week. That is a useful execution measure if the plan is specific. It is not a replacement for recording actual profit, loss, costs, exposure, and drawdown.
A trader can follow a negative-expectancy rule perfectly. Conversely, a profitable trade that violated the plan can obscure a repeated process problem. Keep adherence and outcome in separate columns so each answers its own question.
A binary score also needs an explicit denominator. Are no-trade decisions included? What happens if entry rules were followed but size was not? Define those choices before calculating an improvement. Otherwise the score can rise because the grading changed.
An adherence percentage you can reproduce
This fictional record uses one fixed definition: every required eligibility and risk rule must be followed for the decision to count as compliant.
| Step | Observation or calculation | Interpretation |
|---|---|---|
| Review block A | 12 compliant decisions out of 20 | 12 / 20 = 60%. |
| Review block B | 17 compliant decisions out of 20 | 17 / 20 = 85%. |
| Improvement | 85% − 60% = 25 percentage points | A measurable change under the same grading rule. |
| Financial question | Outcomes and costs recorded separately | The improvement does not prove positive future expectancy. |
Losing Streaks Can Be Common Without Being Harmless
The transcript gives rough probabilities for five, six, or seven consecutive losses during one hundred trades with a fifty-percent win rate. Under an independent, identical fifty-fifty trial model, those figures are broadly consistent with an exact finite-state calculation. The assumptions are essential.
| Run somewhere in 100 independent trades | Calculated probability | Interpretation |
|---|---|---|
| At least five consecutive losses | 81.01% | A five-loss run is common under this model. |
| At least six consecutive losses | 54.61% | Slightly more likely than not under this model. |
| At least seven consecutive losses | 31.75% | Possible without implying that the next trade must win. |
These are our calculations from the stated model, not observed frequencies for the creator’s live method. They measure a run anywhere in the sequence, not the chance that the next five trades all lose. For one preselected block of five independent fifty-fifty trades, the probability of all losses is 0.5⁵ = 3.125%.
To reproduce the run calculation, keep states for zero through k−1 consecutive losses without yet reaching k. Begin with probability one in state zero. A win moves the surviving probability to zero; a loss moves each state to the next, dropping probability that reaches k. Repeat one hundred times and subtract the surviving total from one.
Real trades can be dependent, have changing win probabilities, and occur in clusters within one regime. Therefore the table is an illustration of sampling uncertainty, not a calibrated account warning threshold or permission to ignore a risk limit.
The Next Trade Is Not Due to Recover the Streak
The source’s language about abandoning a method just before it swings back should not be read as a mathematical recovery rule. Under the independent fifty-fifty model, the next trade still has a fifty-percent chance of losing after five losses. The streak does not create a debt that the market owes back.
A loss sequence can be ordinary sampling variation, a regime mismatch, poor execution, an edge that never existed, or an edge that deteriorated. Diagnose those possibilities from the record. The existence of normal streaks does not prove that any particular losing method deserves more capital.
A Review Sample Is Not a Compulsory Live-Trading Quota
The creator proposes fifty to one hundred trades before judging a method. That can be a planning convention, but it is not a universal sufficiency threshold. A hundred highly related trades in one environment can provide less independent information than their count suggests.
Do not continue live exposure merely to finish the count after an affordability limit, account rule, data problem, or prewritten stop condition has been breached. A review can move to simulation or replay, or the project can stop. A sample target and a financial boundary serve different purposes.
The source’s example of finding losses concentrated in an opening hour also needs an evaluation step. A pattern discovered in past results can arise by chance. Freeze the proposed time filter and test it later, retaining the winners it would reject as well as the losses it would avoid.
Small Percentage Risk Compounds Differently From Large Risk
Ten full-risk losses under fixed-fraction sizing
These original calculations assume a $10,000 starting balance, risk reset from current equity after every loss, exact planned exits, and no costs.
| Step | Observation or calculation | Interpretation |
|---|---|---|
| 0.5% per trade | $10,000 × 0.995¹⁰ = $9,511.10 | Drawdown 4.89%; recovery needed approximately 5.14%. |
| 5% per trade | $10,000 × 0.95¹⁰ = $5,987.37 | Drawdown 40.13%; recovery needed approximately 67.02%. |
| Recovery formula | Starting balance / remaining balance − 1 | The required gain is larger than the percentage loss. |
| Execution qualification | Losses can exceed planned fractions | Gaps, costs, and rule breaches are not included. |
The source mentions half-percent risk and reducing toward a quarter percent during difficulty. Those are the creator’s examples, not personalized recommendations or guaranteed safe levels. The transcript does not provide a universal drawdown trigger or a fully specified restoration rule; do not invent them.
Remove the Deadline the Market Never Agreed To
The source warns that an urgent income-replacement goal can encourage oversizing and emotional decisions. A practical response is to separate the learning budget from essential spending and keep realistic limits on time and money. The point is survivability, not an instruction to remain in the activity forever.
Choose one observable improvement for the next review period rather than trying to repair everything at once. A better record may support continuing the study, but it may also reveal that a pause, reduced exposure, different practice environment, or stopping is the most coherent decision.
Why There Is No Pine Script for This Guide
The source does not disclose a chart-entry method to implement. Its central variables are adherence, actual outcomes, dependence, risk fractions, and financial pressure. The probability and account worksheets address those questions without inventing an unrelated price indicator or predicting the next winning trade.
Practice: Build a Thirty-Day Review You Can Audit
- Define the score: write the exact plan rules and denominator. Record instrument, session, setup, risk, eligibility, adherence, costs, and outcome for each decision.
- Separate the questions: calculate adherence and net results independently. Identify whether the evidence concerns execution or the method itself.
- Check the streak model: explain why 81.01% for a run somewhere in one hundred trials is not 81.01% for the next five losses. State whether independence is plausible for your dataset.
- Calculate capacity: reproduce both ten-loss account paths and recovery percentages. Add an explicit stop or reassessment condition before any live study.
- Choose one change: freeze a single process intervention or method hypothesis and evaluate it on later observations. Record the option to pause or stop.
Answer check
Seventeen compliant decisions out of twenty is 85%. In the independent model, a five-loss streak does not change the next trial’s fifty-percent loss probability. The ten-loss balances are approximately $9,511.10 and $5,987.37, with recovery requirements of 5.14% and 67.02%. A rising adherence score is evidence about execution under that score, not proof of an edge.
Research and Comparison Lab
These are original proposed experiments, not results established by the source. Change one main feature at a time, retain failures and missing opportunities, and reserve later observations for evaluation rather than repeatedly selecting rules from the same outcomes.
Is the process improving under one stable definition?
Use consecutive review blocks with unchanged scoring and record rule breaches by type. Keep actual net outcomes alongside the score. Look for fewer specific errors, not merely a more flattering overall grade.
Does a discovered time filter survive later data?
Freeze one time-of-day hypothesis after development, then evaluate a later period with the same setup and costs. Record all rejected winners and losers. Avoid repeatedly revising the supposedly untouched evaluation period.
Are the trades independent enough for the illustration?
Group results by session, instrument, and regime and inspect whether losses cluster. Compare the observed structure with the independent model without claiming that one hundred trades calibrate future streak risk. Use the finding to refine the study design, not to forecast a recovery.
Check Your Understanding
Does a flat account prove no skill progress? No, but financial outcomes still need to be recorded.
Does 85% adherence prove a profitable method? No. Rule quality and costs remain separate.
After five independent losses, is a win due? No. The next probability is unchanged under that model.
Must fifty to one hundred trades be completed live? No. Financial and operational stop conditions take priority.
Can stopping be a rational result of review? Yes. Persistence is not a substitute for evidence or affordability.
Final Takeaway
The source encourages better measurement and less pressure. Use those ideas to separate execution progress, method uncertainty, and financial capacity. A clear review should preserve the ability to continue, refine, pause, or stop rather than promise that results are about to catch up.
Risk Disclosure
This material is educational and is not personalized financial, investment, or trading advice. Trading can cause substantial losses. Source-reported results, hypothetical examples, and probability illustrations do not establish future performance. Calculations depend on their assumptions and omit costs unless stated. Commissions, spread, slippage, gaps, leverage, liquidity, borrowing, financing, and changing market conditions can materially affect outcomes. Indicators do not simulate broker execution or establish profitability. Short exposure can involve losses beyond the initial sale value. Evaluate any approach with appropriate data, realistic costs, and explicit risk limits before considering live use.
This is an independent educational companion and is not affiliated with, sponsored by, endorsed by, or authorized by the source creator, channel, or TradingView.