Alex Ribeiro

overtrading is your 9-5 brain tricking you into thinking activity equals progress your entire life you were conditioned to believe more input = more output the more you study, the better grades you get the more work you do, the more money you earn in trading, that equation doesn’t work more trades don’t equal more profits, but more decisions and more decisions mean more room for error not being in a position is also a position you’re positioned not to lose money you have two jobs as a trader 1) generate profits 2) protect profits the 2nd doesn’t increase your PNL, but it determines whether the first one lasts doing is often the highest quality decision available rewire your brain activity doesn't equal productivity

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AlexandroTrd retweeted

marintrades

@marintrades

9 months ago

99% of you will never "make it" in trading even though you are so certain you will -> Full explanation thread of information your paid mentor wont tell you The statistics are brutal across markets and countries: In Brazils equity futures market (which is one of the worlds largest), researchers tracked every new day trader over multiple years. After 300+ days of trying 97% lost money , just 0.4% earned more than a bank workers wage, and the “best” traders daily profit came with using gambling level risk ( so luck ). There was no evidence of learning with experience ( pulled from IDEAS/RePEc ). In Taiwan one of the cleanest datasets on retail day trading ever assembled found that less than 1% of day traders earned reliably positive abnormal returns after costs. In CFDs/Forex where a lot of retail ICT traders end up regulators own samples show that 82% of UK clients lose ( look up FCA ), and EU regulators report 74 to 89% of retail accounts typically lose money. These arent some fucking Reddit/Twitter rumors , they're regulatory findings based on live accounts. Why do people still think they’ll be the exception? Its classic behavioral finance , for example - traders systematically overestimate their "edge" ( you don't have edge , edge is not having a positive winrate on FXReplay you fucktard ) and underweight costs, trading far too much and underperforming as a result. Barber & Odean work quantified this years ago ( men traded 45% more than women and earned lower net returns - soyboys ), and nothing about the big 2025 changed human psychology. ( pulled from Oxford Academic ) The journaling lie and why your mistake journal isnt and wont make you profitable: Most retail traders keep a journal but its basically a confession log: screenshots, a few lines of should’ve waited, moved stop, chased entry, I was shorting in discount , there was a 4H imbalance in my way to the draw , I picked a bad OB. That kind of journaling is I'd call it "cathartic", not diagnostic. It doesnt tell you whats repeatable, what has edge, or what/when to size up. This is the sole reason why you wont make it: Real traders don’t journal feelings they quantify their process. They collect labeled, queryable, auditable data and then they mine it for expectancy and variance with enough sample size which would make it matter. If you trade ICT concepts (liquidity grabs, FVGs, order blocks, premium/discount, London/NY sessions), your journal should look like a research dataset not a diary. For every trade, log fields like: Context: session (Asia/London/NY), day of week, macro day (CPI/FOMC?), overall trend regime. Setup taxonomy: liquidity sweep? FVG? order block? imbalance fill? HTF confluence (yes/no which timeframe )? Execution: entry trigger, stop model (structural vs volatility), initial RR, partials logic, slippage. Outcome metrics: MFE/MAE in R, time to target/stop, heat (drawdown before target), realized R, post trade excursion if managed differently. Filters: news filter on/off, kill zone window, volatility filter ( for example ATR>x ). Now ask quantitative questions your future P&L depends on: Whats the expectancy E[R] of my London liquidity sweep + 5m OB + X timeframe FVG continuation only when D1 is in discount and DXY diverges? How does that expectancy change on Tuesdays vs Thursdays? On CPI days? When spread is > X? Does adding HTF POI improve expectancy or just look pretty on charts? Whats my MAE distribution before target? Could I widen stops by 0.3R and increase hit rate enough to raise expectancy? Where do I actually earn ? First 90 minutes of London or the 10 minutes after NY open? If 80% of my R comes from one micro window, why am I forcing trades elsewhere? If you cant answer those with numbers, you’re not iterating you’re role playing a retard wannabe trader ( think TJR ). The mentor problem : Most people dont have free thinking ( and when I'm saying this I actually mean like I know maybe 2-3 people who do and they're millionaire and decamillionaire. They adopt their mentors framework and stop there. They copy whats been dumbed down for mass consumption , entry patterns, smart money vocabulary 🤡, and cherry picked examples and then they wonder why their equity curve flatlines. Heres the uncomfortable part you dont want to hear nor does your "mentor": Mentors almost never share the real edge ( most of them dont even have it cause they dont actually trade ) not out of malice, but because the true edge isnt a drawing, its a data advantage. It’s the years of private statistics that tell you which of the 20 chart patterns is actually worth risking 1R today, in this regime, at this time, with this filter on. Thats the part you don’t get in a video. You have to build it , and you wont because you have no free thinking ability. What “REAL data” collection looks like ( the thing almost nobody does ) Treat your trading like a small quant desk: Define a closed set of setups. Name them precisely ( for example “NY session Liquidity Sweep → FVG → OB Reclaim). No retarded lables. Pre define your rules. Entry, stop, management. If you change a rule, version it. Tag every trade with 20–40 features. Make it easy to group and filter. ( Dont overcomplicate it , Excel , Notion , Obsidian ) Compute expectancy and dispersion per setup, per regime (trend/volatility), per session. Size with math, not vibes. Kelly fraction paired with drawdown tolerances based on your real variance, not what your virgin mentor uses. Does “avoid Mondays” actually help your setups? Does “HTF bias” add edge or reduce sample size and kill expectancy? Remove what doesnt pay. Cutting out those useless variables raises your personal winrate and R expectancy without learning a single new pattern. I'll be different bro , I know the new ICT rectum block pattern paired with MMXM buy model 🤓 : Everyone says that. The data says otherwise ( dont believe data if you want to act like a ego driven retard that knows fuckall ) . Across jurisdictions and instruments the base rate is failure. 97% of persistent day traders in one futures market lost. <1% show repeatable skill and 74 to 89% of retail CFD accounts lose. Base rates dont determine your outcome, but they absolutely set the prior you must overcome with real edge, not optimism. ( pulled from ScienceDirect ) And heres the even sadder truth you dont want to hear: Even among the 0.01% who quote on quote "make it" most will only earn job replacement income. Why? Because they never turn edge into scalable process they dont concentrate on the few setups with outsize expectancy, they dont size rationally, and they dont treat trading like a repeatable manufacturing line. Real traders do. Quick reality check for you : If you cant show your top two setups 12 month expectancy, standard deviation, and worst peak to valley drawdown, you dont have an edge you have a schizo story. If your journal cant answer a filter question in <30 seconds, you’re journaling for therapy, not performance. If your trade thesis is, ICT said it works, you outsourced your thinking. Build your own stats or accept average outcomes ( not even average you're just going to be dead broke ).