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Forex trading is broken not because the market doesn’t work, but because expectations are wrong. In this conversation with a forex creator TRIPN , we broke down: - why most beginners fail - what selling education in Ghana actually looks like - where forex education is heading - and... what AI can (and cannot) do in trading If you’re thinking about forex, or selling knowledge online, this matters. 0:00-The biggest lie people believe about forex 2:33-When trading finally “clicked” (why strategy hoping is bad) 3:36-Why selling forex education is difficult 4:59-Trust vs shortcuts: what buyers actually want 8:00-AI in trading: what people get wrong 11:00-What AI cannot do in forex 12:37-If you had $1,000, how should you start? 15:46-God as the source of inspiration and strengthshow more

Michael Asiedu

23,066 subscribers

14,009 次观看 • 6 个月前 •via X (Twitter)

Anya Rossi• Live Now

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[The next retail mania won’t be forex, it’ll be crypto social trading] “Social trading is gonna get a lot more popular.” “You can hit 100x’s and 1000x’s in crypto. You cannot do that in forex.” “The real money comes from being early.” Ansem 🐂🀄️ compared today’s crypto market to the forex boom during COVID. Back then, people paid for trading groups hoping to find alpha. Forex never offered the kind of upside they were chasing. Crypto is different. The biggest winners catch new narratives before everyone else. That’s why he sees social trading becoming a core part of the next cycle, where finding the right people matters as much as finding the right trade.

[The next retail mania won’t be forex, it’ll be crypto social trading] “Social trading is gonna get a lot more popular.” “You can hit 100x’s and 1000x’s in crypto. You cannot do that in forex.” “The real money comes from being early.” Ansem 🐂🀄️ compared today’s crypto market to the forex boom during COVID. Back then, people paid for trading groups hoping to find alpha. Forex never offered the kind of upside they were chasing. Crypto is different. The biggest winners catch new narratives before everyone else. That’s why he sees social trading becoming a core part of the next cycle, where finding the right people matters as much as finding the right trade.

Kaiz 🐂🀄️

78,492 次观看 • 2 个月前

Ansem explains why crypto creates better opportunities than Forex Ansem: “Forex was huge because people had this idea in their mind that they could make a lot of money trading these pairs but you're never going to hit a 1,000x trading Forex” “In crypto and now with Hyperliquid enabling perps on stocks, you can trade these markets and make a lot of money doing so” “Yes, trading is very PvP but it's a skill-based game that you can get better at” FaZe Banks: “Stories like Kimchi, Rowdy and Insentos, Cupsey… these kids are young. Insentos was a janitor before he got rich. Kimchi was a Fortnite pro”

Ansem explains why crypto creates better opportunities than Forex Ansem: “Forex was huge because people had this idea in their mind that they could make a lot of money trading these pairs but you're never going to hit a 1,000x trading Forex” “In crypto and now with Hyperliquid enabling perps on stocks, you can trade these markets and make a lot of money doing so” “Yes, trading is very PvP but it's a skill-based game that you can get better at” FaZe Banks: “Stories like Kimchi, Rowdy and Insentos, Cupsey… these kids are young. Insentos was a janitor before he got rich. Kimchi was a Fortnite pro”

Jack

134,043 次观看 • 1 个月前

Losses in forex is inevitable Basically what happens is that when a trader loses money in the Forex market, the money does not go to any particular person or entity. Instead, the money is considered a loss and disappears from the trader's account. When a trader loses money, the losses are simply deducted from their trading account balance. When a stock tumbles and an investor loses money, the money doesn't get redistributed to someone else. Drops in account value reflect dwindling investor interest and a change in investor perception of the stock. The best way to deal with a big trading loss is to take a small break. Consider your strategy and your position size before jumping back in. When you do decide you are ready, start small. If you are trading as an institutional trader, you will be taxed just as any other employee. In case you are a retail Forex trader, you will need to report your profits and losses. Retail Forex traders use a Form 1040 or Form 1040NR in the USA. Either trading too big or too often is the most common reason why Forex traders fail. Overtrading might be caused by unrealistically high profit goals, market addiction, or insufficient capitalization. The maximum loss per trade can be categorized into three levels: conservative, moderate, and aggressive. Traders who are conservative about safeguarding their capital will take a chance of no more than 1% on their total trading capital per trade. Good morning traders

Losses in forex is inevitable Basically what happens is that when a trader loses money in the Forex market, the money does not go to any particular person or entity. Instead, the money is considered a loss and disappears from the trader's account. When a trader loses money, the losses are simply deducted from their trading account balance. When a stock tumbles and an investor loses money, the money doesn't get redistributed to someone else. Drops in account value reflect dwindling investor interest and a change in investor perception of the stock. The best way to deal with a big trading loss is to take a small break. Consider your strategy and your position size before jumping back in. When you do decide you are ready, start small. If you are trading as an institutional trader, you will be taxed just as any other employee. In case you are a retail Forex trader, you will need to report your profits and losses. Retail Forex traders use a Form 1040 or Form 1040NR in the USA. Either trading too big or too often is the most common reason why Forex traders fail. Overtrading might be caused by unrealistically high profit goals, market addiction, or insufficient capitalization. The maximum loss per trade can be categorized into three levels: conservative, moderate, and aggressive. Traders who are conservative about safeguarding their capital will take a chance of no more than 1% on their total trading capital per trade. Good morning traders

FxLion

25,437 次观看 • 2 年前

I sat down with who was buying $SOL under $10 and had made 7 figures trading memecoins 🐶 if you're trading this memecoin market, this is a MUST WATCH video we discussed: ➡️ how we find memecoins early ➡️ how to come up with a trading strategy ➡️ advice for beginners If you're looking for a trading group, you should join Kanto Labs Timestamps: 0:00 Intro 2:20 Why Were You Buying Solana At $8 8:52 Why Trading Is Skill Based 9:46 Best Advice For Beginners 15:32 Coming Up With YOUR Trading Strategy 20:30 Why Controlling Emotions Is Important 22:08 How Are You Finding Tokens Early 25:00 Why Being In Groups Is Essential 30:14 Closing Thoughts From Easy

I sat down with who was buying $SOL under $10 and had made 7 figures trading memecoins 🐶 if you're trading this memecoin market, this is a MUST WATCH video we discussed: ➡️ how we find memecoins early ➡️ how to come up with a trading strategy ➡️ advice for beginners If you're looking for a trading group, you should join Kanto Labs Timestamps: 0:00 Intro 2:20 Why Were You Buying Solana At $8 8:52 Why Trading Is Skill Based 9:46 Best Advice For Beginners 15:32 Coming Up With YOUR Trading Strategy 20:30 Why Controlling Emotions Is Important 22:08 How Are You Finding Tokens Early 25:00 Why Being In Groups Is Essential 30:14 Closing Thoughts From Easy

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14,345 次观看 • 1 年前

EDGE REVEALED: How an Ex-Jane Street Trader Finds Edge in Markets & Life Agustin Lebron Agustin Lebron (former Jane Street trader, author of The Laws of Trading, now working at an AI startup applying reinforcement learning to market execution) breaks down what edge really means — and how to find yours in trading, careers & life. “Edge is something that either you know or you can do that the marginal participant in that market either doesn’t or can’t.” We cover: - What edge actually means & how Jane Street builds organizational edge (their worst skill is still "pretty decent") - Why you can never truly know if you have edge — the statistical vs intuitive approaches - The consolidation of quant trading: from dozens of options firms to a handful of giants - The gamblification of everything — retail trading, sports betting & prediction markets fueling quant profits - What it was like having Sam Bankman-Fried (SBF) as a Jane Street intern: "Day one, I'm going to ask all the questions" - How to apply edge thinking to your own career: find what you're differentially good at - Raising teenagers in the AI age: why the traditional path still works, but other paths are opening up 00:00 Introduction 00:44 What is edge in financial markets 01:43 Jane Street and organizational structures for quant trading 03:46 Identifying and validating edge in trading 06:22 Navigating extreme market events and volatility 09:37 Future of quant trading and consolidation 12:15 Why quant firm profits have increased 14:42 The gamblization of everything 15:55 Who should pursue a career in quant trading 18:19 Applying the concept of edge to career and life decisions 20:56 Advice for interns to excel in quant trading 23:44 Predicting long-term success in trading interns 25:08 Sam Bankman-Fried as an intern and FTX reflections 28:15 Reasons people leave Jane Street and what they do next 31:19 Advice for young people in a changing world 36:09 Navigating job insecurity in tech-driven roles 38:55 Where to live if you want to be successful 40:28 Raising kids for a rapidly changing future 42:55 Questions young people should ask themselves 44:45 Outro and book recommendation

EDGE REVEALED: How an Ex-Jane Street Trader Finds Edge in Markets & Life Agustin Lebron Agustin Lebron (former Jane Street trader, author of The Laws of Trading, now working at an AI startup applying reinforcement learning to market execution) breaks down what edge really means — and how to find yours in trading, careers & life. “Edge is something that either you know or you can do that the marginal participant in that market either doesn’t or can’t.” We cover: - What edge actually means & how Jane Street builds organizational edge (their worst skill is still "pretty decent") - Why you can never truly know if you have edge — the statistical vs intuitive approaches - The consolidation of quant trading: from dozens of options firms to a handful of giants - The gamblification of everything — retail trading, sports betting & prediction markets fueling quant profits - What it was like having Sam Bankman-Fried (SBF) as a Jane Street intern: "Day one, I'm going to ask all the questions" - How to apply edge thinking to your own career: find what you're differentially good at - Raising teenagers in the AI age: why the traditional path still works, but other paths are opening up 00:00 Introduction 00:44 What is edge in financial markets 01:43 Jane Street and organizational structures for quant trading 03:46 Identifying and validating edge in trading 06:22 Navigating extreme market events and volatility 09:37 Future of quant trading and consolidation 12:15 Why quant firm profits have increased 14:42 The gamblization of everything 15:55 Who should pursue a career in quant trading 18:19 Applying the concept of edge to career and life decisions 20:56 Advice for interns to excel in quant trading 23:44 Predicting long-term success in trading interns 25:08 Sam Bankman-Fried as an intern and FTX reflections 28:15 Reasons people leave Jane Street and what they do next 31:19 Advice for young people in a changing world 36:09 Navigating job insecurity in tech-driven roles 38:55 Where to live if you want to be successful 40:28 Raising kids for a rapidly changing future 42:55 Questions young people should ask themselves 44:45 Outro and book recommendation

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214,514 次观看 • 7 个月前

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.Scott Wu to Joe Lonsdale on why Cognition uses AI in job interviews: "One or two years ago, people had this mentality of 'How do we make sure people aren't using AI while we're interviewing them?' And I think that has totally flipped. Honestly, I think that was wrong... If you're asking the question of like, how do we evaluate people on exactly the thing that AI can already do, that seems kind of the wrong. Our interview process has always been... you can use as much AI as you want to use. We're going to give you a few hours. Just build your whole own product surface. A lot of these are projects that, frankly, is like, if you were trying to do this by hand, you would not be able to get done in a few hours. So you kind of have to use AI for this. But in reality, what we actually want to test is, in addition to how familiar you are with these tools, what we actually want to test is, what do you think is the right thing to build? Or how do you make these product decisions? How do you make these trade-offs? How do you decide or collect information about what you should be doing?"

American Optimist

13,182 次观看 • 6 个月前

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Full interview with the founder and CEO of Propr Lou sits down with me to discuss Hyperliquid and the future of prop trading Timestamps: 00:00:00 Intro 00:00:16 Meet Louis: from TradFi to crypto 00:01:52 How the crypto market has changed 00:03:49 Why build on Hyperliquid 00:06:52 How propr got started 00:08:40 Scaling a lean team (and the grind) 00:12:24 What a prop firm actually is 00:15:33 Agents, bots, and the future of trading 00:18:32 What Louis is most proud of 00:21:02 Thinking about the token and TGE 00:24:14 Where propr goes in 5 years 00:25:57 Best and worst trades 00:27:50 Life outside crypto + shoutouts

ryandcrypto

43,328 次观看 • 4 个月前

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Insilico Terminal

22,370 次观看 • 21 天前

My full conversation with Chris Camillo 1:20 How I discovered Chris Camillo 0:33 World's first narrative trader 8:05 Why you need to call your trades 10:13 Making 70% a year for 20 years 14:03 The Michelle Obama dress trade 17:00 Trading Damn Daniel 21:34 What hedge funds get Wrong 33:15 IRL trade research 49:01 Trading the iPhone launch 56:36 The female edge in trading 1:02:19 Trading the Swatch AP 1:16:38 Chris's worst trade 1:26:20 Crypto traders can crush the stock market 1:37:33 Not selling Amazon

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threadguy

456,856 次观看 • 4 个月前

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252,984 次观看 • 5 个月前

India is the world’s second-largest gold buyer… but what if Indians suddenly reduce gold buying for one year? Could it actually help India avoid an economic crisis? In this video, we break down the real connection between gold purchases, forex reserves, the rupee, and India’s Current Account Deficit (CAD) in simple language. But why is everyone suddenly concerned about gold imports? Here’s the reason - India imports most of its gold from abroad. And every time India buys gold, payments happen in US dollars. That means massive dollar outflow from the country. What do you think? Will Indians ever reduce gold buying? And what do you personally prefer, Physical Gold or Gold ETFs? Source: CNBC, Economic Times

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Kotak Neo

135,429 次观看 • 4 个月前

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70,737 次观看 • 8 个月前

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Anthony Scaramucci

24,994 次观看 • 5 个月前

#WATCH | Mumbai: Chief Economist, CareEdge Ratings, Rajani Sinha says, “India's forex reserves are falling mainly because of weak capital flows into the country. Because of this, we are seeing a sharp weakening of the currency, and the RBI has been intervening in the forex market to control the depreciation of the rupee. That is why, since the start of the West Asia crisis, we have seen our forex reserves deplete by around 27 to 28 billion dollars. When I say capital flows, not only are we seeing high FII outflows since the West Asia crisis started—so for March and April, cumulatively we have seen FII outflows of around $20 billion—but if we look at the whole of the last fiscal year, we also saw FII outflows of around $16 billion or so…”

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19,689 次观看 • 4 个月前

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The Wolf Of All Streets

90,982 次观看 • 1 年前

I really needed this conversation. Was rage trading, chasing BS, forcing trades, and slowly chopping up my capital to $0. Seeing how Mike was moving made me rethink what I was doing and come back to center, to winning systems. Funny enough, after this conversation I went on to make over $200K. It ended up being a pretty important inflection point in my recent trading journey. Hope you guys enjoy. Chapters: 0:00 — Why Copy Trading Usually Goes Wrong 4:55 — How to Build a Trading Thesis 7:37 — Taking Profits Without Killing the Upside 11:42 — Learning From Better Traders 13:38 — Why Ego Is Expensive 16:32 — Greed, Round-Tripping and Knowing When to Sell 19:06 — When a Thesis Changes in Real Time 24:27 — Position Sizing That Lets You Sleep at Night 28:46 — Moving Down the Risk Curve as Capital Grows 31:50 — Selling Too Early vs. Staying Alive 34:05 — How Good Traders Actually Find Ideas 40:18 — The Biggest Lessons Trading Teaches 42:58 — What Still Takes Years to Figure Out 46:45 — When Trading Starts Changing Your Life Let me know if these are helpful, they 10000% are for me selfishly. Who else do you want to see? Any other questions you have?

I really needed this conversation. Was rage trading, chasing BS, forcing trades, and slowly chopping up my capital to $0. Seeing how Mike was moving made me rethink what I was doing and come back to center, to winning systems. Funny enough, after this conversation I went on to make over $200K. It ended up being a pretty important inflection point in my recent trading journey. Hope you guys enjoy. Chapters: 0:00 — Why Copy Trading Usually Goes Wrong 4:55 — How to Build a Trading Thesis 7:37 — Taking Profits Without Killing the Upside 11:42 — Learning From Better Traders 13:38 — Why Ego Is Expensive 16:32 — Greed, Round-Tripping and Knowing When to Sell 19:06 — When a Thesis Changes in Real Time 24:27 — Position Sizing That Lets You Sleep at Night 28:46 — Moving Down the Risk Curve as Capital Grows 31:50 — Selling Too Early vs. Staying Alive 34:05 — How Good Traders Actually Find Ideas 40:18 — The Biggest Lessons Trading Teaches 42:58 — What Still Takes Years to Figure Out 46:45 — When Trading Starts Changing Your Life Let me know if these are helpful, they 10000% are for me selfishly. Who else do you want to see? Any other questions you have?

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38,105 次观看 • 1 天前

Professional trader and former prop firm performance coach, Imre, breaks one of the biggest myths in trading: “Most people think edge is discipline… Or mindset… Or some secret setup.” But what if that’s completely wrong? Because if your “edge” disappears the moment conditions change… Was it ever an edge to begin with? The truth is uncomfortable: Edge isn’t what you see on the charts. It’s what’s forcing other participants to act. Rebalancing flows, Gamma exposure, Stops getting cleared; That’s where moves actually come from. And if you’re not trading the cause… You’re just reacting to the effect. So here’s the real question: Are you trading patterns… Or do you understand what’s forcing the market to move? Full Episode 👇

Professional trader and former prop firm performance coach, Imre, breaks one of the biggest myths in trading: “Most people think edge is discipline… Or mindset… Or some secret setup.” But what if that’s completely wrong? Because if your “edge” disappears the moment conditions change… Was it ever an edge to begin with? The truth is uncomfortable: Edge isn’t what you see on the charts. It’s what’s forcing other participants to act. Rebalancing flows, Gamma exposure, Stops getting cleared; That’s where moves actually come from. And if you’re not trading the cause… You’re just reacting to the effect. So here’s the real question: Are you trading patterns… Or do you understand what’s forcing the market to move? Full Episode 👇

Riz Iqbal

38,690 次观看 • 4 个月前

AI has entered education, now the harder question is, What does QUALITY look like in the age of AI? 🤔 This Sunday, I sit down with Dr Violet Makuku, a quality assurance specialist, to explore what AI means for standards, assessment, teaching, learning & the credibility of our qualifications. This is not a conversation about fearing AI and not a conversation about celebrating it blindly, but a conversation about quality. 🗓️ Sunday, 27 September, 17:00 SAST 📍 Sunday Sessions LIVE 👉🏽 Teachers, academics, students, parents & education leaders, come and join us. Bring your questions! #SundaySessions #AIinEducation #QualityEducation #FutureOfEducation #ArtificialIntelligence #Education

AI has entered education, now the harder question is, What does QUALITY look like in the age of AI? 🤔 This Sunday, I sit down with Dr Violet Makuku, a quality assurance specialist, to explore what AI means for standards, assessment, teaching, learning & the credibility of our qualifications. This is not a conversation about fearing AI and not a conversation about celebrating it blindly, but a conversation about quality. 🗓️ Sunday, 27 September, 17:00 SAST 📍 Sunday Sessions LIVE 👉🏽 Teachers, academics, students, parents & education leaders, come and join us. Bring your questions! #SundaySessions #AIinEducation #QualityEducation #FutureOfEducation #ArtificialIntelligence #Education

Kgethi Phakeng, PhD(Wits); Hon DSc (UBristol)

12,487 次观看 • 6 天前

⚫️ UNCANNY VALLEY: THE AI CLASSROOM REVOLUTION: ARE TEACHERS READY? What if AI isn’t just disrupting education… but detonating it? Ethan Mollick, Professor at The Wharton School, joins Dr Danish for one of the most explosive Uncanny Valley episodes, lifting the lid on how classrooms are collapsing, colleges are scrambling, and apprenticeships are vanishing in real time. From AI tutors replacing professors to the rise of one-person unicorns, this isn’t just a change in learning…it’s a reset of work, meaning, and what it even takes to succeed. This episode doesn’t ask whether AI will change education. It shows you how it already has. Fridays at 4:20PM ET. Only on 𝕏. 00:18 – Is AI destroying school, or forcing us to teach better? 01:13 – “100% they’re cheating.” The honesty about academic dishonesty. 02:41 – Why good pedagogy still matters—even with AI tutors. 03:51 – Elon Musk says college is obsolete. Is he right — or just early? 05:01 – “AI gives you the answer—but you don’t learn.” The Turkey study. 06:31 – From calculators to GPT: How cheating evolves—and what to do. 08:24 – What the flipped AI-powered classroom of the future looks like. 09:23 – Inside Ethan’s Wharton classes: Simulations, games, and AI everywhere. 10:09 – “AI is an always-on tutor.” What humans still do better. 11:08 – Can AI actually launch a company? Where Ethan draws the line. 12:44 – “AI cofounder” is real, but jagged edges still slow it down. 14:07 – Why bad ideas fail faster when filtered through AI. 15:45 – Confidence vs. capability: the psychology of starting up. 16:51 – The average founder is 42. What that really means for AI. 18:04 – Will a flood of new entrepreneurs fix—or break—the market? 19:50 – AI as advisor: How a chatbot could help your catering business. 21:37 – Why most Americans are founders-in-waiting—and AI unlocks them. 22:30 – Prototyping is cracked. Scaling? Not yet. 24:33 – Youth unemployment and the collapse of on-the-job learning. 25:51 – “The apprenticeship model is broken.” And how to fix it. 27:06 – Losing the talent pipeline — and why companies must step up. 28:22 – Why the youth don’t want factory jobs—and shouldn’t. 29:26 – Is AGI inevitable—or just imagined? 31:07 – What should we teach our kids? The answer might scare you. 32:27 – Bundled jobs, fragmented futures: how humans stay relevant. 33:59 – The real singularity? When we can’t predict what happens next. 35:25 – The AI assumption no one wants to question. 36:55 – What are agents, really? Why no one agrees on the definition. 37:55 – Co-intelligence vs. substitution: what agents skip over. 38:50 – Plain-English goals, rogue pricing, and collusion-by-default. 40:02 – Nested agents are here, and Wharton’s building them. 40:58 – Management > Coding: What great prompters actually do. 41:12 – Product managers might be more vital than ever.

⚫️ UNCANNY VALLEY: THE AI CLASSROOM REVOLUTION: ARE TEACHERS READY? What if AI isn’t just disrupting education… but detonating it? Ethan Mollick, Professor at The Wharton School, joins Dr Danish for one of the most explosive Uncanny Valley episodes, lifting the lid on how classrooms are collapsing, colleges are scrambling, and apprenticeships are vanishing in real time. From AI tutors replacing professors to the rise of one-person unicorns, this isn’t just a change in learning…it’s a reset of work, meaning, and what it even takes to succeed. This episode doesn’t ask whether AI will change education. It shows you how it already has. Fridays at 4:20PM ET. Only on 𝕏. 00:18 – Is AI destroying school, or forcing us to teach better? 01:13 – “100% they’re cheating.” The honesty about academic dishonesty. 02:41 – Why good pedagogy still matters—even with AI tutors. 03:51 – Elon Musk says college is obsolete. Is he right — or just early? 05:01 – “AI gives you the answer—but you don’t learn.” The Turkey study. 06:31 – From calculators to GPT: How cheating evolves—and what to do. 08:24 – What the flipped AI-powered classroom of the future looks like. 09:23 – Inside Ethan’s Wharton classes: Simulations, games, and AI everywhere. 10:09 – “AI is an always-on tutor.” What humans still do better. 11:08 – Can AI actually launch a company? Where Ethan draws the line. 12:44 – “AI cofounder” is real, but jagged edges still slow it down. 14:07 – Why bad ideas fail faster when filtered through AI. 15:45 – Confidence vs. capability: the psychology of starting up. 16:51 – The average founder is 42. What that really means for AI. 18:04 – Will a flood of new entrepreneurs fix—or break—the market? 19:50 – AI as advisor: How a chatbot could help your catering business. 21:37 – Why most Americans are founders-in-waiting—and AI unlocks them. 22:30 – Prototyping is cracked. Scaling? Not yet. 24:33 – Youth unemployment and the collapse of on-the-job learning. 25:51 – “The apprenticeship model is broken.” And how to fix it. 27:06 – Losing the talent pipeline — and why companies must step up. 28:22 – Why the youth don’t want factory jobs—and shouldn’t. 29:26 – Is AGI inevitable—or just imagined? 31:07 – What should we teach our kids? The answer might scare you. 32:27 – Bundled jobs, fragmented futures: how humans stay relevant. 33:59 – The real singularity? When we can’t predict what happens next. 35:25 – The AI assumption no one wants to question. 36:55 – What are agents, really? Why no one agrees on the definition. 37:55 – Co-intelligence vs. substitution: what agents skip over. 38:50 – Plain-English goals, rogue pricing, and collusion-by-default. 40:02 – Nested agents are here, and Wharton’s building them. 40:58 – Management > Coding: What great prompters actually do. 41:12 – Product managers might be more vital than ever.

Mario Nawfal

1,613,286 次观看 • 1 年前

Forex trading is a d@nger®us skill. Not d@nger©us because you lose money… D@ngerous because once you understand it, you can’t go back to small thinking. After testing $10,000 in the market, tell me how you’ll be excited about making ₦200 online again. That’s why I tell traders: scale up when your strategy is proven. If you have $10k: Split it into 10 parts. Use $1k per attempt. One clean trade on $XAUUSD with 10.0 lot and a 1:17 RR can turn $1k → $40k. Even if 9 trades fail… one winner changes everything. But if you lose all 10 tries… be honest: maybe the strategy isn’t profitable yet. This year we’re not just making mama proud. We’re shocking mama with tears of joy. Be honest… Are you still trading scared, or are you ready to scale?

Forex trading is a d@nger®us skill. Not d@nger©us because you lose money… D@ngerous because once you understand it, you can’t go back to small thinking. After testing $10,000 in the market, tell me how you’ll be excited about making ₦200 online again. That’s why I tell traders: scale up when your strategy is proven. If you have $10k: Split it into 10 parts. Use $1k per attempt. One clean trade on $XAUUSD with 10.0 lot and a 1:17 RR can turn $1k → $40k. Even if 9 trades fail… one winner changes everything. But if you lose all 10 tries… be honest: maybe the strategy isn’t profitable yet. This year we’re not just making mama proud. We’re shocking mama with tears of joy. Be honest… Are you still trading scared, or are you ready to scale?

Bonafide Brand

15,269 次观看 • 6 个月前