A Honest Annual Trading Review: Losses, Lessons, and 2026It’s December 11th, and there are maybe ten real trading days left in the year. At this point, there isn’t much more to do. The market won’t change my year, and I won’t change the market.
So it’s the right moment for an annual review.
I’m not the kind of trader who does weekly or even monthly “performance summaries” that don’t actually mean anything. For me, the only question that matters is this:
With how much did I start the year—and with how much am I ending it?
And after fourteen consecutive positive years, this is the year I end in the red.
So the question becomes: Why?
Why did I lose this year?
Before I dive into the lessons, the mistakes, and the changes I’ll implement starting in 2026, I need to give you some context—because no trading journey exists in isolation.
From 2002 to Today: A Long Road Filled With Luck, Lessons, and Reality
I began trading in 2002, investing in stocks right after the dot-com bubble. And things went incredibly well— not because I was smart, not because I understood markets, but because I had one of the greatest advantages a trader can have:
Perfect timing after a major market collapse.
In other words: pure luck.
In 2004 I discovered Forex, and by 2007 I had shifted entirely to Forex trading.
Until 2009, everything worked almost effortlessly. Every year was green. Even the 2008 crisis was profitable for me—I happened to hold some exceptional short positions.
And then came 2009.
The market didn’t humble me. My own arrogance did.
“ I can’t be wrong. I predicted the 2008 crash. I see the market clearly. I’ve got this.”
That mindset cost me 50% of everything I had accumulated.
That was my first real wake-up call.
It forced me to understand a truth that every long-term trader eventually learns, one way or another:
Humility in front of the market is not optional. It is survival.
That realization became the first major shift in how I approach trading.
What Changed After 2009: A Short Summary of a Long Transformation
As a brief summary of what shifted after 2009—beyond drastically reducing my appetite for risk—the biggest change was my transition toward pure price action and swing trading as the foundation of my approach.
Before that, the market felt almost binary, almost predictable.
- If NFP came in above expectations, the USD strengthened—and it stayed strong, not just for a few intraday spikes.
- When Hurricane Katrina hit, the narrative was straightforward: weak USD.
- Carry trade on JPY was the play all the way until 2008, so buy every substantial dip
- Breakouts were real breakouts—not whatever we have today, with fakeouts layered on fakeouts.
It was a different environment.
Cleaner. More directional. More narrative-driven.
And I traded it exactly as it was.
But markets evolve, and if you don’t evolve with them, you get left behind.
So I adapted.
I shifted from being a trader who reacted to news flows and macro momentum to a trader who reads structure, context, and price behavior first.
I shifted from chasing moves to waiting for high-probability rotations.
I shifted from assuming I understand the market to accepting that the market owes me nothing and can invalidate my ideas at any moment.
There’s much more to say about that transition—how painful it was, how long it took, and how it changed the way I think not just about trading, but about myself. But that’s a story for another time.
For now, it’s enough to say this:
2009 forced me to mature as a trader.
What followed shaped the next decade and a half.
It’s Not About Trump, and It’s Not About Excuses
This isn’t about Trump coming to the White House.
This isn’t about macro narratives or politics.
Yes, the markets did shift around that period — but this article is not about searching for excuses.
Because when it comes to Forex and XAUUSD, I managed the environment just fine.
I adjusted. I adapted. I traded often from instinct shaped by experience, and overall, that part of my trading year held up.
What dragged my year down — completely and undeniably — were my crypto investments.
I Was Never a “To-the-Moon” Guy — And Still Lost Substantially
I’ve never been a moonboy.
I’ve always been realistic with my targets: soft, achievable gains in the 30–50% range.
I never believed in the mythical “altcoin season.” I said repeatedly that it was wishful thinking and that the glory of past cycles would not repeat.
I didn’t gamble on new projects, I didn’t throw money at memes, and I didn’t YOLO into narratives.
And yet — I still lost.
So why?
Because I allocated too much capital, even within my fixed conservative approach.
Not because I believed in altcoin season, but because I believed we would see a meaningful recovery in the autumn.
I sized like someone expecting a bounce.
When the bounce didn’t come, instead, the flash crush from October, the weighting crushed the year( BTW, I wasn't leveraged)
Simple as that.
What I Will Change in 2026 (Crypto Edition)
The fix is straightforward:
- No more long-term investing in crypto, regardless of narrative.
- Maximum time exposure: a few days, maybe a few weeks.
- Stick strictly to major, established projects.
- Trade only what behaves cleanly from a technical perspective.
In other words, crypto will no longer be a long-term play in my portfolio.
It will be treated exactly as I should've be treated it from the beginning:
a short-term speculative instrument — nothing more, nothing less.
Forex and XAU/USD / XAG/USD: The Adjustments Going Into 2026
On the Forex and metals side, the changes are more nuanced — and in some ways, more strategic.
The core shift is this: shorter-term focus, smaller targets on Forex, larger targets on Gold, and a more active approach on Silver.
Here’s the breakdown:
1. Smaller Targets in Forex (EUR/USD as the Example)
In previous years, a 200–250 pip target on EUR/USD was perfectly reasonable.
The volatility allowed it, the market structure supported it, and the flow followed through.
But today, that kind of moves — consistently — is simply not realistic (look at it in the past 6 months).
So the adjustment is straightforward:
From 200–250 pip targets → to sub-100 pip targets.
It’s not about aiming lower.
It’s about aligning targets with actual market behavior, not nostalgia for a volatility regime that no longer exists.
2. Larger Targets on Gold (Because the Volatility Demands It)
Gold is the opposite story.
Volatility has exploded, rotations are massive, liquidity pockets run deep, and intraday swings are two or three times what they used to be.
So the shift here is:
From 300–400 → to 500+ being the new standard.
You can’t trade for 50-100 pips an instrument that behaves like a hurricane.
You adapt to its nature — or it eats you alive.
3. A More Active Approach on Silver (XAG/USD)
Silver has become a much more attractive instrument for me:
- Cleaner technical behavior
- Larger relative percentage moves
- Alignment with Gold, but with more exploitable inefficiencies
So 2026 will include more active trading on XAGUSD, treating it as a strategic middle ground between Forex and Gold volatility.
4. Integrating More ICT/SMC Into My Framework
Another important change is methodological:
I’ll incorporate more ICT/Smart Money Concepts into my analysis and execution.
Not as a religious shift — I’m not replacing classical TA and price action — but as an enhancement.
SMC concepts:
- map exceptionally well onto today’s liquidity-driven markets
- clarify sweeps, inducement, fakeouts
- explain displacement and rebalancing
- blend naturally with the price action approach I already use
In other words, this is not a stylistic change — it’s an upgrade of the internal framework.
Price action stays.
Classical TA stays.
But SMC becomes a bigger part of the decision-making process.
What This All Means for 2026: A Cleaner, Tighter, More Adapted System
When you put all these adjustments together — the crypto restructuring, the refined Forex targets, the larger Gold plays, the increased activity on Silver, and the deeper integration of SMC — the message becomes clear:
2026 won’t be about reinventing myself.
It will be about refining myself.
This year wasn’t a catastrophe ( around 15% loss overall)
It wasn’t an identity crisis.
It was a recalibration — a reminder that longevity in trading is not about perfection, but adaptation.
I didn’t lose because I became worse.
I lost because my allocation in one corner of my portfolio didn’t match the reality of the market.
And the only unforgivable mistake in trading is refusing to learn from the forgivable ones.
The markets haven’t betrayed me.
Crypto hasn’t betrayed me.
Forex and metals haven’t betrayed me.
The responsibility is mine — and so is the path forward.
In 2026, my system becomes:
- Simpler — fewer narratives, more structure.
- Tighter — smaller Forex targets.
- More opportunistic — bigger Gold moves, active Silver plays, short-term crypto speculation.
More aligned with how markets actually behave, not how past versions of me used to trade them.
And that’s the real conclusion of this year:
After almost 25 years in the markets, the only edge that never expires is the willingness to evolve.
Some years, you win because you’re right.
Some years, because you're lucky.
Some years you lose because you’re human.
But the trader who survives is the trader who adapts — again and again, without ego, without excuses.
And that’s exactly what 2026 will be about.
P.S:
And One More Thing… I Kind of Expected This After 14 Years
If I’m being completely honest, part of me always knew this moment would come.
You don’t go fourteen consecutive years without a losing one and expect the streak to last forever.
Statistically, psychologically, realistically — a red year was inevitable at some point.
So no, this wasn’t a shock.
It wasn’t a dramatic fall from grace.
It was simply… the year that was eventually going to arrive.
And that’s actually liberating!:)
Because once you accept that even long-term consistency includes the occasional step backward, you also see the bigger picture clearly:
This year doesn’t define me — the next one will.
Risk Management
Radio Yerevan: Is Crypto the Biggest Wealth Transfer in History?Answer: Yes. But not in the direction people hope.
In the last decade, crypto marketing has repeated one grand promise:
“This is the biggest wealth transfer in human history!”
And in classic Radio Yerevan fashion, this statement is both true and misleading.
Yes — a historic wealth transfer took place.
No — it did not empower the average investor.
Instead, it efficiently moved wealth from retail… back to the very entities retail thought it was escaping from.
Let’s break it down: structured, clear, and with just the right amount of irony.
1. The Myth: A Decentralized Financial Uprising
The early crypto narrative was simple and beautiful:
- The people would reclaim financial independence.
- The system would decentralize power.
- Wealth would flow from institutions to individuals.
The idea was inspiring — almost revolutionary.
Reality check: Revolutions are expensive.
And someone has to pay the bill.
In crypto’s case, the average investor volunteered enthusiastically.
2. The Mechanism: How the Transfer Actually Happened
To call crypto a wealth transfer is not an exaggeration.
The numbers speak loudly:
Total market cap peaked above $3+ trillion.
Most of the profit was extracted by:
- VCs who bought early,
- teams with massive token allocations,
- exchanges capturing fees on every trade,
- and whales who mastered liquidity cycles.
Retail investors, meanwhile, contributed:
- capital,
- liquidity,
- hope,
- hype
- and a remarkable tolerance for drawdowns.
It was, in essence, the perfect economic loop:
money flowed from millions → to a concentrated few → exactly like in traditional finance, only faster and with better memes.
3. The Irony: A Centralized Outcome From a Decentralized Dream
Here lies the great contradiction:
Crypto promised decentralization. Tokenomics delivered centralization.
When 5 wallets hold 60% of a token’s supply, you don’t need conspiracy theories — you need a calculator.
The “revolution” looked more like:
- Decentralized marketing
- Centralized ownership
- Retail-funded exits
- And a financial system where “freedom” was defined by unlock schedules and vesting cliffs
But packaged correctly, even a dump can look like innovation.
4. Why Retail Was Doomed From the Start
Not because people are unintelligent, but because:
- No one reads tokenomics.
- Unlock calendars sound boring.
- Supply distribution charts kill the romance.
- Liquidity mechanics are not as exciting as „next 100x gem”.
- And hype travels faster than math.
In a speculative market, psychology beats fundamentals until the moment fundamentals matter again — usually when it's too late.
5. The Real Wealth Transfer: From “Us” to “Them”
The slogan said:
“Crypto will redistribute wealth to the people!”
The chart said:
“Thank you for your liquidity, dear people.”
The actual transfer looked like this:
- Retail bought the story.
- Institutions created the tokens.
- Retail bought the bags.
- Institutions sold the bags.
- Retail called it a correction.
- Institutions called it a cycle.
Everyone had a term for it.
Only one group had consistent profits from it.
6. So, Was It the Biggest Wealth Transfer in History?
Yes.
But not because it made the average investor rich.
It was the biggest because:
- no previous financial system mobilized so many people
- so quickly
- with so little due diligence
- to transfer so much capital
- to so few beneficiaries
- under the banner of liberation.
It wasn’t a scam.
It wasn’t a conspiracy.
It was simply financial physics meeting human psychology.
7. The Lesson: Crypto Isn’t the Problem — Expectations Are
- Blockchain remains a brilliant invention.
- Tokenization has real use cases.
- DeFi is a groundbreaking paradigm.
- And so on
The issue wasn’t the technology.
It was the narrative that convinced people that buying a token was equivalent to buying financial freedom.
Real freedom comes from:
- understanding liquidity,
- reading tokenomics,
- respecting supply dynamics,
- and asking the only question that matters:
“If I’m buying… who is selling?”
In markets — especially crypto — this question is worth more than any airdrop.
8. Final Radio Yerevan Clarification
Question: Will the next crypto cycle finally deliver the wealth transfer to the masses?
Answer: In principle, yes.
In practice… only if the masses stop donating liquidity.
How to Use ATR in TradingViewMaster ATR using TradingView's powerful charting tools in this step-by-step tutorial from Optimus Futures.
ATR, or Average True Range, is a volatility indicator that helps traders measure market movement, set appropriate stop losses, and adjust position sizing based on current market conditions.
What You'll Learn:
Understanding ATR as a volatility measurement tool that tracks price movement regardless of direction
How ATR calculates the average range between highs and lows over a specified period — typically 14
Why rising ATR signals increasing volatility and larger price swings
Why falling ATR indicates decreasing volatility and quieter market conditions
Using ATR to set dynamic stop losses that adjust to current volatility rather than arbitrary dollar amounts
How to calculate stop distances by multiplying ATR by factors like 2x or 3x
Applying ATR for position sizing to maintain consistent risk across different volatility environments
Setting profit targets based on ATR multiples to align with actual market movement
Filtering trade setups using ATR levels to avoid low-volatility periods or confirm breakout momentum
How to add ATR on TradingView via the Indicators menu
Understanding the default 14-period setting and how shorter or longer periods affect responsiveness
Practical examples using the E-mini S&P 500 futures chart
Applying ATR across daily, weekly, and intraday timeframes for risk management and trade planning
This tutorial is designed for futures traders, swing traders, and risk-focused analysts who want to integrate volatility-based risk management into their trading approach.
The methods discussed may help you set smarter stops, size positions appropriately, and adapt your trading strategy to changing market conditions across multiple markets and timeframes.
Learn more about futures trading with TradingView: optimusfutures.com
Disclaimer
There is a substantial risk of loss in futures trading. Past performance is not indicative of future results. Please trade only with risk capital.
We are not responsible for any third-party links, comments, or content shared on TradingView. Any opinions, links, or messages posted by users on TradingView do not represent our views or recommendations.
Please exercise your own judgment and due diligence when engaging with any external content or user commentary.
This video represents the opinion of Optimus Futures and is intended for educational purposes only. Chart interpretations are presented solely to illustrate objective technical concepts and should not be viewed as predictive of future market behavior.
In our opinion, charts are analytical tools, not forecasting instruments.
Risk Management Basics 95% of Traders IgnoreWhen traders try to improve their results, they often jump straight to indicators, new setups, or refined entries.
But here’s the uncomfortable truth:
Most traders don’t fail because of their strategy — they fail because they don’t control their risk.
Let’s break down the two fundamentals that separate professionals from the 95%:
1️⃣ The 1% Rule: Your Built-In Survival System
Most beginners risk 5–20% per trade.
Professionals risk a maximum of 1%. Why?
Because the goal isn’t to win every trade — the goal is to stay in the game long enough for your edge to play out.
Risking only 1% means:
✔ A losing streak won’t destroy your account
✔ Your emotions stay stable and rational
✔ Your system has room to unfold statistically
✔ You avoid the #1 account killer: overexposure
Here’s the key mindset shift:
Risk management is not about fear — it’s about increasing your probability of long-term profitability.
2️⃣ Positive Expectancy: The Math Behind Winning Traders
Most traders judge a setup based on the last one or two trades.
Professionals evaluate it based on expectancy — the average profit per trade across a large sample.
Here’s a simple example:
Win rate: 40%
Average win: +60 pips
Average loss: –30 pips
Expectancy =
(0.4 × 60) – (0.6 × 30) = +6 pips per trade
Meaning:
You can lose more trades than you win — and still be profitable.
This is the principle beginners never understand.
A system with positive expectancy + 1% risk per trade becomes extremely powerful.
You stop caring about individual losses and start thinking in probabilities, not emotions.
The Truth Most Traders Miss
➡️ Risk management is the strategy.
➡️ Expectancy matters more than your win rate.
➡️ Risking 1% won’t make you rich fast — but it will prevent you from blowing up.
➡️ Trading becomes easier when you remove the illusion of certainty.
If traders spent more time understanding expectancy and risk instead of chasing “perfect setups,” half of their frustration would disappear overnight.
Thanks for reading — and have a disciplined start to your trading week!
If you found this post valuable, let me know in the comments.
I might create a full series on applied risk management and expectancy modeling.
Jonas Lumpp
Speechless Trading
Disclaimer: This tutorial is for educational purposes only and does not constitute financial advice. Its goal is to help traders develop a professional mindset, improve risk management, and make more structured trading decisions.
AI Revolution: How the Retail Trader Can Finally WinA step-by-step guide for traders who want to stop staring at charts and start letting AI do the heavy lifting.
For years, trading meant one thing:
Sit at your desk.
Stare at charts.
Wait.
Hope.
React.
Repeat.
But in 2025, that’s ancient history.
AI has changed everything.
Now any retail trader — even a complete beginner — can create a TradingView strategy, test it, refine it, and fully automate execution to MT5 or cTrader using webhooks… without writing a single line of code.
If you can type instructions, you can build an automated trading system.
Here’s the full blueprint — updated with the crucial Step 0 that most people don’t even know exists.
⭐ STEP 0 — Build Your Master AI Prompt (The Secret Weapon)
Before you write a single strategy rule…
Before you ask AI to code…
Before you try to automate anything…
You MUST build a Master Prompt.
This is the “operating system” for the AI — it tells the model:
how to write the Pine Script
how to structure entries & exits
how to format alerts
how to avoid compile errors
how to respond when you paste broken code
how to preserve your logic perfectly
Without a Master Prompt, AI guesses.
With a Master Prompt, AI produces clean, professional, error-free trading systems consistently.
Here’s the master prompt you’ll use:
🔥 MASTER PROMPT (Copy + Paste Into ChatGPT Before Giving Your Strategy Rules)
You are now my expert TradingView Pine Script v5 strategist, quant developer, and compiler-level debugging assistant.
Your job is to:
1. Build a complete TradingView strategy() script based on the rules I give you.
2. Ensure the script compiles with ZERO errors.
3. Write clean, structured, commented code using professional conventions.
4. Include:
– strategy.entry()
– strategy.exit() with SL & TP
– Input parameters
– alertcondition() for webhook automation
5. Structure alerts so they work with strategy.order.action.
6. NEVER change my trading logic. Follow it EXACTLY.
7. If the code fails to compile:
– Identify the REAL root cause
– Fix only what’s necessary
– Return a fully corrected script
8. When I ask for improvements, optimize the code without altering the core idea.
After loading this master prompt, wait for my rules before generating the strategy.
Now your AI assistant is fully “trained” before it begins coding.
Once Step 0 is done?
The real fun begins.
🚀 STEP 1 — Decide What You Want Your Strategy To Do
Define the basics:
What triggers your entry?
What ends the trade?
What confirms the setup?
How much risk?
Example simple idea:
Buy when price closes above the 20 EMA after RSI oversold.
Sell when price closes below the 20 EMA after RSI overbought.
Stop = 1 ATR.
Take profit = 2 ATR.
Once you define this?
You're ready for the AI to code it.
🤖 STEP 2 — Use AI to Turn Your Idea Into a TradingView Strategy
Paste your Master Prompt.
Then paste your rules.
Example instruction:
“Build the strategy using my Master Prompt.
Here are the rules…”
AI outputs a ready-to-paste Pine Script.
If it errors?
You tell it:
“Fix all compile errors without changing my trading logic.”
This is the magic of Step 0 — the AI already understands exactly how to fix your code properly.
📊 STEP 3 — Backtest Directly on TradingView
Paste the script.
Add to chart.
Open Strategy Tester.
Check:
Win rate
Drawdown
Profit factor
Stability
Number of trades
If it sucks?
Ask AI:
“Improve this strategy’s performance. Keep the overall concept but add filters.”
AI gives you Version 2.
⚙️ STEP 4 — Turn Your Strategy Into Webhook Alerts
Click Alerts → Condition → Your Strategy Name
Choose:
Strategy Entry Long
Strategy Exit Long
Strategy Entry Short
Strategy Exit Short
Turn on Webhook URL.
Use structured JSON:
{
"signal": "{{strategy.order.action}}",
"symbol": "{{ticker}}",
"price": "{{close}}",
"position_size": "0.10"
}
Now TradingView is alert-ready.
🌐 STEP 5 — Send Alerts to MT5 or cTrader Using Webhooks
You need a bridge.
Best options:
PineConnector
TradeConnector
cTrader Open API bot
Make/Zapier → Python Server → MT5 EA
Example webhook:
{
"action": "BUY",
"symbol": "XAUUSD",
"lot": 0.10,
"sl": 50,
"tp": 100
}
🧠 STEP 6 — Use AI to Build the MT5 or cTrader Execution Robot
If you want a custom bot instead of PineConnector:
Ask:
“Write an MT5 EA that receives webhook commands in JSON format and executes market orders with SL and TP.”
Or:
“Write a cTrader cBot that listens for webhook signals and places trades automatically.”
AI builds your execution engine.
🔁 STEP 7 — Your Fully Automated Trading Pipeline
STEP 0 — Build your Master AI Prompt
STEP 1 — Define your strategy
STEP 2 — AI generates TradingView strategy
STEP 3 — Backtest & refine
STEP 4 — Create alert webhooks
STEP 5 — Bridge → MT5/cTrader
STEP 6 — AI builds execution bot
STEP 7 — Enjoy hands-free AI-powered trading
🎯 Final Thoughts — This Is the New Era
The trader who wins is the one who:
uses AI
automates everything
removes emotion
builds systems, not guesses
executes consistently
Tools like TradingView + AI + MT5/cTrader automation are the biggest level-up in retail history.
And it all starts with:
STEP 0 — Build your Master Prompt.
Let the fun begin
Get Funded and make $20 000 Monthly. Complete plan for 2026.Hey traders let's have a look at prop trading again. It's a great opportunity for the skilled traders who has good strategy, discipline and mastered risk management. Let's start with the numbers which many traders and misunderstood.
📌 Prop firm facts
- $100K account with 10% max drawdown means you got $10K account, not $100K
- Goal of 10% to pass phase 1 while you can risk 10% means 100% gain
- Goal of 5% to pass Phase 2 while you can risk 10% adds another 50% gain.
- You will literally be funded after making 150% not 10% and 5%
⁉️ Does it mean it's impossible to get funded ?
Yes it's possible, next to good strategy you need, discipline and mainly you just need to adjust your risk management. If you make 150% in year as a Hedge fund manager you will be a superstar trader. Yet people still want to pass prop challenge in a less than week or in a few trades which means not sticking to the risk management.
🔗 Click to the picture below to Learn more about Prop Risk management 📌 How to make $20 000 a month ? Magic of 3%
Yes, you actually need to make only a 3% a month. Is it difficult ? No, It's not. You need 3 wins with 1:2 RR while risking 0.5% Risk.
1️⃣Your Ultimate goal - -$100K Funded account - 3% Gain - 80% Profit split = $2400 Payout
2️⃣Let's take it to $20 000 a Month
Don't try to increase your % gains per month, increase your capital under management
- Get another 4 x $ 100K Challenges pass them - You will have $500K AUM:
- $ 500 000 - 3% Gain - 80% Profit split = $12 000
3️⃣Reinvest buy another 3 - 5 challenges aim for $ 1000 000 funded across few solid props firms. 🎯 $ 1000 000 - 3% gain - 80% Profit Split = $24 000 Payout
📌 Have a long term plan
this is not gonna happen in few months. It's a year plan - But you got this... 💪
With approximate cost of $500 - $600 per $100K challenge you will need to spend apron. $5500 to get $1000 000 funding. You will fail some, its unavoidable, so let's count with more might $10K. But still , you can start with first $100K an then reinvest to another challenges. You dont need $10K investment right now. But later this $10K and 3% gain and 80% profit split is $24 000, even more then $20K.
📌 Difficulty is not technical, but in patience
I speak from experiences that my biggest mistakes was trying to pass quickly or when I was in drawdown I started to gamble. Be patient and stick to the rules. If we stick to 3% a month without progressive risk management it would be 4 months to get funded. If you do progressive risk management you can do it faster, and once you are confident you can run multiple challenges at the same time.
📌 Long term plan requires perfect planning
Find 60 minutes just for yourself and this about these questions below, write the answers to to the paper, think about the execution of your project. I know you didn't do it now, but come back to this and do it again. You need to visualize your future successful yourself and remind that visualization every day. I recommend a book - Psycho-cybernetics from Maxwell Maltz it will help you define your self-image of successful trader in the fact this book will change your life.
📌 Essential Rules for Prop Trading
-Its not a straight forward game
-Reduce number of trades - Only A+ Setups
- Grow Your Capital Under management in multiple firms not % gains
- 3% is a golden profit in prop space to live from trading
❌ Dont do this
If you don't trade well on small account, getting prop firm will not change it.
Don't expect it to be a solution to bad financial situation. It's extension. 🧪 Trading is not hard we often overcomplicate it
I believe you already few great trades in a month, but you also have many unnecessary ones, look at your last few month results and check if would be able to make 3% if you excluded those unnecessary trades. I sure you could ant thats what you have to do
Switch from machine gunner to a Sniper.
Write this on a paper and put it somewhere so you see it every day.
🎯 $ 1000 000 - 3% gain - 80% Profit Split = $24 000 Payout
🎯 $ 1000 000 - 3% gain - 80% Profit Split = $24 000 Payout
🎯 $ 1000 000 - 3% gain - 80% Profit Split = $24 000 Payout
$1000 000 Funding !! - Your ultimate goal for 2026 💪
I promised myself I’d become the person I once needed the most as a beginner. Below are links to a powerful lessons I shared on Tradingview. Hope it can help you avoid years of trial and error I went thru.
📊 Sharpen your trading Strategy
⚙️ 100% Mechanical System - Complete Strategy
🔁 Daily Bias – Continuation
🔄 Daily Bias – Reversal
🧱 Key Level – Order Block
📉 How to Buy Lows and Sell Highs
🎯 Dealing Range – Enter on pullbacks
💧 Liquidity – Basics to understand
🕒 Timeframe Alignments
🚫 Market Narratives – Avoid traps
🐢 Turtle Soup Master – High reward method
🧘 How to stop overcomplicating trading
🕰️ Day Trading Cheat Code – Sessions
🇬🇧 London Session Trading
🔍 SMT Divergence – Secret Smart Money signal
📐 Standard Deviations – Predict future targets
🎣 Stop Hunt Trading
🧠 Level Up your Mindset
🛕 Monk Mode – Transition from 9–5 to full-time trading
⚠️ Trading Enemies – Habits that destroy success
🔄 Trader’s Routine – Build discipline daily
🛡️ Risk Management
🏦 Risk Management for Prop Trading
📏 Risk in % or Fixed Position Size
🔐 Risk Per Trade – Keep consistency
When to Trade — When to Stay OutWhen to Trade — When to Stay Out: A Deep, Practical Guide for Traders
Timing is a core edge. Not every hour, session, or chart condition is trade-worthy. The difference between a profitable trader and an active losing trader is not how many trades they take — it’s which trades they take and when. This article gives you a detailed, systematic framework to decide when to trade and when to stay out, with concrete rules, time windows, checklists and worked examples.
Big-picture logic
Markets are driven by liquidity (where orders sit), volatility (how fast price moves) and participants (who is trading). Good timing aligns these three:
Liquidity concentration (institutions, marketmakers) produces cleaner, higher-probability moves.
Right volatility means enough movement to reach targets but not so much that stop losses are random.
Recognizable market structure (trends, ranges, breaks) allows rules to be applied consistently.
If any of the three is missing, edge declines and risk of random losses rises.
Session windows — when the market is most tradable
Below are standard session definitions in UTC+00:00. Adjust for daylight savings if required (noted where relevant).
Tokyo / Asian Session
⏵ UTC+00:00: 23:00 – 08:00 ( main liquidity often 23:00–02:00 UTC )
⏵ Characteristic: lower liquidity for major FX pairs, choppier price action. Exceptions: JPY crosses, pairs with Asia-led liquidity, and crypto (24/7).
London Session
⏵ UTC+00:00: 07:00 – 16:00 (most active 08:00–11:00 UTC)
⏵ Characteristic: heavy institutional flow, high liquidity. Many clear directional moves begin here.
New York Session
⏵ UTC+00:00: 12:00 – 21:00 (most active 13:00–16:00 UTC)
⏵ Characteristic: continuation or reversal of London moves; major news releases occur here.
Key overlap (best single window)
⏵ London–New York overlap: UTC+00:00 ~12:00–16:00. Highest combined liquidity and volatility; most “clean” trends and reliable breakouts occur here.
Rule of thumb: Prefer intraday trades during the London session and the London–New York overlap. Be selective in Asia unless trading JPY pairs or range-break strategies designed for low liquidity.
Concrete: Best times to trade (prioritized)
Session open impulse — first 60–120 minutes of London or New York sessions.
Overlap window — London + New York overlap (UTC+00:00 ~12:00–16:00).
Post-news verified moves — 10–30 minutes after high-impact macro prints, if market structure becomes clear and isn’t just noise.
Clear breakouts after consolidation during active sessions (volume confirmation, sweep of liquidity, not just a one-bar spike).
When to avoid trading (and why)
Low-volume Asian hours for majors — price tends to chop and give false signals.
Right before major macro releases (NFP, CPI, FOMC) — price can gap or spike unpredictably. Exceptions: defined volatility playbook with strict hedges.
Midday lulls after initial session impulse — often flat ranges and low edge.
On unclear structure / messy price action — wide, overlapping candles, no clear swing highs/lows.
During market holidays or early close days — liquidity is thin; spreads widen.
Pre-trade checklist
Time window OK? (London / NY open or high liquidity event)
Major news? (No significant release within ±30 mins)
Higher timeframe structure clear? (H4 or Daily trend / range)
Trade idea defined (entry, stop, target) — use price levels, not indicators only.
Risk per trade ≤ planned % of account (see position sizing).
Reward : Risk ≥ your minimum (e.g., 1.5–3:1 depending on edge).
Catastrophic stop capability confirmed (can you absorb worst-case slippage?)
Exit rules set (profit-taking scale or full exit)
Trade logged in journal immediately after (reason, setup, time, bias)
Position sizing — exact worked example (step-by-step)
Use a fixed % of equity for risk per trade (commonly 0.5%–2%). Example uses 1% risk.
Assume:
Account size = $10,000.
Risk per trade = 1% of account = $10,000 × 0.01.
We compute digit-by-digit: 10,000 × 0.01 = 100. So maximum $100 risk on this trade.
Generic position-size formula:
Position size (units) = (Account Size × Risk%) ÷ (Stop Distance in price units × Value per price unit per 1 unit)
Always recalc pip/value for cross rates and for instruments (stocks, futures, crypto) — adapt the “value per price unit” accordingly.
Money Management is much more important than a strategy. You should learn Money Management before trying any strategy.
Order types & execution rules
Limit entries at confluence levels (support/resistance + liquidity sweep zone) — better price and less slippage.
Stop orders for breakout entries — use when you want to enter only after momentum confirms.
OCO (One Cancels Other) for scaling / invalidation management — reduces manual errors.
Avoid market entries during major news due to slippage/gap risk, unless your plan accounts for it.
Trade management & exits
Initial target: defined by structure (previous swing, ATR multiples, measured moves).
Scale out: consider taking partial profits at the first reasonable target, let the rest run with a trailing stop.
Stop relocation: only move stop to breakeven after a predefined profit multiple reached (e.g., after +1R or after price clears a new structure). Don’t move stops based on emotion.
If price returns and breaks your entry zone invalidating the setup, exit — the market changed.
Strategy-specific timing tweaks
Trend-following: prefer strong sessions (London/NY) and avoid Asian low-liquidity hours. Enter on retracements that align with higher timeframe trend.
Range / mean-reversion: worst during session opens; best during mid-session lulls, but only if volatility is low and boundaries are clear.
Breakout strategies: require confirmation — e.g., breakout during overlap or accompanied by increased volume / volatility. Avoid breakouts in thin Asian hours.
News scalping: high risk; only for experienced traders with defined entry, strict spread/latency controls, and capital to absorb spikes.
Common mistakes (and how to fix them)
Trading outside your chosen time windows — fix: enforce a trading clock.
Overtrading in chop — fix: increase minimum R:R and wait for clear structure.
Ignoring spreads and liquidity — fix: include spread in stop/target math and avoid thin sessions.
Moving stops prematurely — fix: use rules (e.g., only move after +1R).
Trading news impulsively — fix: have a news plan: either avoid or have a predefined volatility playbook.
Emotional trading (e.g. not closing the position when the price hits stop-loss)
Psychological & routine rules
Trade only when rested and focused.
Limit screen time to your pre-set sessions.
Keep a journal: reason for trade, outcome, lessons. Review weekly.
Daily routine: pre-market scan 30–60 minutes before your active session, post-session journal entry.
FAQ
Q: Can I trade during Asian hours?
A: Yes — but selectively. Prefer JPY pairs, Asia-centric instruments, or strategies built for low volatility.
Q: What if my timeframe and session disagree?
A: Give priority to higher timeframe structure. If H4 / Daily shows trend, trade during active sessions for better fills.
Q: How much should I risk per trade?
A: Conservative traders use 0.5%–1% per trade. More aggressive ones use up to 2%. The key is consistency and drawdown planning.
Focus your trading during high-liquidity windows (London, New York, and their overlap), avoid low-volume and pre-news periods, always validate trades with liquidity + volatility + clear market structure, use strict risk management (e.g., 1% per trade with position sizing), and follow a pre-trade checklist to avoid low-quality setups. Better timing = better edge.
Enjoy!
Gold Forex Trading During Major Economic Events & News Releases
I guess you already noticed how impulsively the markets may react to economic events and news.
In this article, I will teach you a simple strategy to follow during important news release s and how to trade news.
1. Sort out the economic calendar
There are a lot of news in the economic calendar.
They are not equal in their impact.
Most of the economic calendars indicate the potential significance of each event: while some news have low importance, some have medium importance and some are considered to be extremely important.
For example, above is the list of coming UK fundamental news.
You can see that these news have different degree of importance.
My recommendation to you is to sort out the economic calendar in a way, so it would display only the most important news.
Among the news that we discussed above, only one release has high importance.
2. Know on what trading instruments does the news have an effect
While some of the news in the economic calendar may impact many financial markets and trading instruments, some news may affect very particular instruments.
For example, a FED Interest Rate decision may have a very broad effect on financial markets.
At the same time, Interest Rate Decision in Australia may affect only Australia - related instruments.
3. Don't trade one hour before the news and one hour after the release
Once you see the important fundamental news coming, don't trade the trading instruments that can be affected by the new s 1 hour before and after the release.
For example, in 5 minutes we are expecting important UK news - CPI data.
I stopped trading GBP pairs 1 hour before the release of the news, and will resume trading them one hour after the release.
4. Protect your trading positions 5 minutes ahead of the news
If you have an active trading position and related important news are expected, move your stop loss to entry 5 minutes ahead of the release of the news.
For example, I have a short trade on GBPAUD. I see that in 5 minutes important UK data is coming. I will move stop loss to entry 5 minutes ahead of the news and make a position risk-free.
I always say to my students, that news trading is very complicated. Due to a high volatility, it is very hard to make wise decision during the news releases.
The approach that I suggest will help you to avoid all that and trade the markets when they are calm.
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I am part of Trade Nation's Influencer program and receive a monthly fee for using their TradingView charts in my analysis.
Trading Future - 1-Minute TimeframeTrading Future - 1-Minute Timeframe CME_MINI:MES1! CME_MINI:ES1! CME_MINI:M2K1!
RSI Low (Reversal) Entry Strategy
Spot ENTRY
Trend completed - Succeed !
Entry Criteria
✔ RSI Low alert
✔ RSI crosses above MA
✔ Price crosses above SMA9
✔ Price pullback holds SMA9
✔ Optional: Price above SMA20 for stronger confirmation
Exit Criteria
❌ Price closes below SMA9
❌ Price falls below HMA-Low (secondary exit)
❌ Price hits target below HMA-High line
Indicators Setup:
1. HMA Low/High – Length 15
Entry: Price crosses above HMA-Low and stays inside the HMA channel.
Exit: Price falls below SMA 9 OR price goes below HMA-Low line (secondary exit).
2. SMA 9 (Blue)
Entry: Price pulls back to SMA9 but does not fall under it.
Exit: Price falls under SMA9.
3. SMA 20 (Red)
Confirmation trend line.
Entry Confirmation: Price crosses above SMA20.
4. SMA 70 (Teal)
Higher-timeframe trend bias.
5. RSI (14) – Low/High 30/70
Reversal signal at RSI Low.
RSI extreme lows highlight with BG color.
6. MACD Histogram (12/26/9)
Trend confirmation: Histogram cross above 0 = momentum shift upward.
Trading Steps:
1. Identify the RSI Low (Alert)
RSI prints a lowest point and background highlights in the extreme zone.
2. RSI Crosses Above Its MA (Yellow)
RSI breaks above its MA = early upward momentum.
At the same time:
Price crosses above SMA 9 (blue).
3. Entry Trigger
Wait for a price pullback to SMA9,
BUT price must not break below SMA9.
If SMA9 holds support → Enter long.
4. Stop Loss Rules
Primary Stop Loss: Price closes below SMA 9 (blue).
Secondary Stop Loss: Price dips just under HMA-Low = early trend failure.
5. Position Hold Conditions (Confirmation)
Hold the trade ONLY IF:
Price stays above SMA 9.
MACD Histogram crosses above 0
→ Trend shifts from negative to positive, confirming upward movement.
6. Ride the Trend
Let price continue inside HMA channel.
Wait for trend to complete (usually when RSI approaches 70 or MACD weakens).
7. Profit Taking (Exit Rules)
Option A: HMA-High line target
Set take-profit just below HMA-High line.
Option B: SMA9 Breakdown
Exit when price falls below SMA 9 (blue).
How to set % risk per trade based on your statistical dataHey whats up traders today it will be a short one in the bullet points but I believe a valuable points to think about. The setup matters, but the real foundation is how much you risk per trade. If you don’t control this, nothing else works. Your edge collapses. Your psychology collapses. And your results become completely random.
If you are not gambler you most likely risk between 0.5 -2% risk per trade. Good, but why?
Many traders use this risk because it's kind of well known and recommended value risk per trade. Ok, it's relatively safe, but if you don't have it build based on your statistical data. You can be also risking to low while you could make more. So In this post is not about why we should use risk management and calculate if for each position based on SL distance. I already did this post below 👇Click the picture to learn more In this post I will try to give advice how you can calculate best risk per trade for you based on your strategy and risk.
I always recommend backtest at least 300 examples of strategy. When you do that, you know your average win rate on average target. From the tab bellow you can see how many % of trades you need to win with the specific risk reward. Here is also important to consider your ability to hold in the trade. Its amazing to catch 1:5 risk reward trades, but it mostly comes with low win ratio in other words, you will get stopped out few times until you get big trade. Also 1:5 risk reward usually has a pullback during the move. Can you face it without emotions being affected?
Most importantly, you finally understand something every professional lives by: you don’t know the distribution of the trades.
You may have a 65% percent win rate. It still means that you can have 35 losses out of 100 traders. Remember distribution of wins and losses is random , you never know outcome of next trade.
It could be win win loss win. Or loss loss loss win win. Or a brutal streak of seven losses before the market pays you back.
✅✅❌✅❌❌✅✅✅✅❌✅
When wins and losses are evenly distributed it's quite comfortable to continue in opening new trades. You still believe your strategy and it's simply normal to have loss time to time.
✅❌❌❌✅❌❌❌❌❌✅✅
But what you gonna do when such a streak comes? Are you gonna doubt your strategy? Are you gonna look for different strategy? Remember 65% success rate means 35 possible losses out of 100. If 20 losses comes in a row your long term statistics still was not broken.
Dont think this cant happen to you. If this didnt happen to you yet, you are not trading for long enough. It will come and its better to be prepared.
📌 Lets look at the Monte Carlo simulation with our 65% win ratio and 2RR
As we can see on the picture below if you start with 10K and follow your strategy in a short period of one month we can face drawdown and end unprofitable even when we did everything right. Why? We did everything right and we have positive winning ratio and Risk reward
📌 Random distribution of the trades
I don't win every trade, you don't win every trade. No one does. Trading is longterm game and short term result can be a bit random. Because you are might trend trader and market can stay in the range during some months or you are a reversal trader and its still trading against you. So how to beat it - Time.
📌 Lets have a look at the same setup 65% Win rate and 2 RR
But now let's have look at the long-term results. As we can see on chart below. after some time even the worst case distribution is getting in to the profit. However there still was 3 months around break even - Frustrating but its the reality 📌 Lets improve Risk reward to 2.3
You will be getting slightly bigger wins so every loosing streak will be recovered faster.
And you should not stay in the prolonged drawdowns for long periods
📌 Lets improve win ration to 70%
And its even better less often you got loss and 2.3 RR recover slightly better.
📌 So what should be my risk per trade
First done look on how much you want to make, trading is mainly about protecting capital. After you got your statistical data. Run Monte Carlo simulations and try to model the worst case distribution of the trades.
For example if you got 70% win rate - means you can lose 30 trades out of 100. Be ready that it can happen, even its unlikely and if that really happens it means something is wrong with your strategy or you made too much mistakes. But count with it that it can happen.. Setup your risk per trade in such % that you would be comfortable if that happens.
📍 0.25% Risk - 30x Loss = - 7.5%
📍0.5% Risk - 30 x Loss = - 15%
📍1% Risk - 30 x Loss = -30%
📍2% Risk - 30x Loss = - 60%
📍3% Risk - 30x Loss = - 90%
Define what would you be able to accept and be comfortable even during a loosing streak.
📌 Have more accounts
This will give you flexibility. Im running 3x personal accounts. Each with different risk. with copy trading system to distribute my positions. 🎯 Account 1: Here Im opening all trades which I has well defined risk and its A+Setups. If I open a trade on this account they goes automatically to the other 2 accounts. So I got proportionaly this positions on whole capital with 1% risk.
🎯 Account 2: Here are running copied trades from Account 1 + Im opening another positions when I want to add or increase the risk also used for short terms setups. Its 3% risk only form this one specific account and its not copied to other accounts.
🎯 Account 3: Here are running trades from account 1 + This account is also used mainly for the crypto trades and news trading. Trades are also isolated just for this account and not copied to the whole portfolio.
🎯 Prop Firm Trading
For the prop trading where more strict rules Im using completely different approach which I described in this post below 👇Click the picture to learn more Final tip: Try to have strategy with win rate between 65 - 70% and 2 - 2.5 RR.
If you got anything lower than that you can go thru some dark periods, but you will survive if stick to your plan based on the statistics. If you don't have statistical data of your strategy, stop trading for while , step back and do a bit of backtesting Tradingview has great backtesting features.
David Perk aka Dave FX Hunter
Stop Loss: Feelings vs. Statistics (Why Fixed SL Fails)Most traders set their Stop Loss based on feelings: "I’ll put my stop below this wick" or "I always risk 50 points."
The problem? The market doesn't care about your 50 points.
The market has a natural heartbeat called Volatility. If you use static rules (fixed pips) in a dynamic market, you are gambling, not trading. Today, we replace "feelings" with Statistics using the Average True Range (ATR).
1. The Statistical Reality
Market volatility expands and contracts.
In low volatility: A 50-point move is a trend change.
In high volatility: A 50-point move is just "noise" (random fluctuation).
If your Stop Loss is placed inside the "Noise Zone," you will get stopped out even if your direction was correct. You are paying the market a fee for being too tight.
2. The Solution: The ATR Bands
The Average True Range (ATR) measures the average size of the last 14 candles. It calculates the "noise."
Instead of a fixed number, your Stop Loss should be dynamic. The Rule: A statistical stop loss should be outside the current noise—usually 2x the ATR.
3. The Tool in pinescript example
I have written a simple script for you. It draws a "Noise Channel" around the price.
If price is inside the gray zone: It is just noise.
If price breaks outside the band: The trend is statistically significant.
Open your Pine Editor and paste this in : ( before you paste the code to your pine editor keep the first line which is the version 6 then delete everything and past this code )
indicator("Kodologic: ATR Noise Bands", overlay=true)
// 1. Input for Sensitivity
multiplier = input.float(2.0, title="ATR Multiplier (Stop Distance)")
length = input.int(14, title="ATR Period")
// 2. Calculate the 'Heartbeat' (Volatility)
atrValue = ta.atr(length)
// 3. Define the Upper and Lower Statistical Bands
upperBand = close + (atrValue * multiplier)
lowerBand = close - (atrValue * multiplier)
// 4. Plotting
// The Gray Zone represents 'Market Noise'.
// A safe Stop Loss usually belongs OUTSIDE this zone.
p1 = plot(upperBand, color=color.new(color.red, 50), title="Statistical Short Stop")
p2 = plot(lowerBand, color=color.new(color.green, 50), title="Statistical Long Stop")
fill(p1, p2, color=color.new(color.gray, 90), title="Noise Zone")
4. The "Secret" to Consistency
When you switch to ATR stops, your Stop Loss distance will vary. Sometimes it will be wide, sometimes tight.
"But what if the ATR stop is too far away for my account?"
Do not tighten the stop. Lower your position size.
Amateurs try to force the market to fit their account size.
Pros adjust their position size to fit the market's reality.
Trade the data, not the hope.
I am building a series on how to move from subjective trading to objective, data-driven strategies using Pine Script. Follow for the next update.
Master the Market with This Secret StrategyHey traders! If you’ve ever watched XAUUSD suddenly explode up or crash down and wondered “What just happened?” — this is the answer. And that’s exactly why today’s topic matters.
To truly master gold, you need to understand one thing better than most traders do: how interest rates and the FED shape every major move on this chart.
When I first started trading, I relied heavily on patterns, indicators, and momentum signals. But the longer I traded, the more obvious it became: gold doesn’t make its biggest moves because of a pattern — it moves because the flow of money shifts. And nothing shifts money faster than the FED.
Interest rates are basically the “price of the dollar,” and gold reacts to that instantly:
High rates → strong USD → gold usually drops.
Lower rates or a dovish tone → weaker USD → gold rallies hard.
But here’s the part most traders never realize:
The FED doesn’t need to change rates to move gold.
Sometimes a single hawkish or dovish sentence is enough to push XAUUSD $20–$30 in minutes. That’s why understanding the tone of the FED — not just the numbers — is your real edge.
And this leads to the strategy I’ve used consistently with XAUUSD:
If the market expected hawkish but hears dovish → gold pumps.
If the market expected dovish but gets hawkish → gold drops fast.
That “expectation gap” is what gives us the clean moves we love trading.
On TradingView, I keep it simple:
I never enter on the first spike — that move is almost always engineered to grab liquidity. Instead, I wait 15–30 minutes for the real structure to form, watch for a break and retest, and then I follow the true direction. This approach has saved me from countless traps during FED weeks.
So when you’re analyzing XAUUSD, don’t just stare at the candles.
Look at the interest rate environment.
Listen to the FED’s tone.
Measure what the market expected versus what actually happened.
Master that connection — and suddenly the gold chart feels less chaotic and a lot more predictable.
How to Calculate Lot Size for Trading XAUUSD on TradingView
Very few people know that there is a free position size calculator for any trading instrument and, of course, for GOLD on TradingView.
It is absolutely free , it does not require a paid subscription, and it can be used to measure position size for XAUUSD trading for any account size, leverage and broker.
In this article, I will teach you how to calculate lot size for your XAUUSD trades in 3 simple steps.
Set It Up
The first step will be to simply create a free TradingView account.
Then open Gold price chart and find a trading panel.
It will be at the bottom of the screen.
Click " expand " in the right corner.
In the suggested options, choose TradingView Paper Trading and click " Connect ".
In paper trading window, click " create an account ".
Choose the account balance, leverage and commissions exactly as you have with your real gold trading account.
And now your best free gold position size calculator is ready .
How to Use It
Once you found a trading setup, know the exact stop loss level and your desired risk per trade.
Let's imagine that we want to buy Gold now.
To calculate the best lot size for our trade, we should know the exact level of our Stop Loss.
Let's take 2770 level for the sake of the example.
Right-click on that chart and choose " trade " and " create new order " then.
The window that will appear on the right side of the chart. It will be your lot size calculator on TradingView.
Select " stop loss " checkbox and input the desired risk percentage for a trading position.
Let's take 1% as the example.
In the price field, input the exact price level of your stop loss : 2770 in our case.
In Gold XAUUSD, trading 1 standard lot equals 100 units/ounces.
Your lot size will be based on the number of units.
Take that number and divide it by 100.
In our case, we have 54 units.
Our lot size will be 54 dived by 100 or 0,54.
That will be your lot size for the Gold trade.
What I like about TradingView position size calculator is that once you set your default parameters, the only thing that you need to adjust for the measurement of a lot of size is the level of stop loss of your Gold trading position.
If you use TradingView for charting, it will be very convenient for you to use it.
❤️Please, support my work with like, thank you!❤️
I am part of Trade Nation's Influencer program and receive a monthly fee for using their TradingView charts in my analysis.
Why Set and Forget Can Be Costly: A Judas Swing Recap on $EURUSDThis week offered a powerful reminder that even a strong setup can turn into a losing trade if you rely solely on a set-and-forget approach. While the Judas Swing strategy continues to deliver consistent opportunities, this particular FX:EURUSD setup showed us why active trade management matters especially in fast-moving sessions.
Going into the session, FX:EURUSD presented a clean range with well-defined liquidity above and below. As expected, price swept the Judas Swing zone lows, the first step in our Judas Swing framework which immediately shifted our attention to potential buying opportunities
Once price took liquidity from the lows and broke structure to the upside, all the pieces aligned:
- Liquidity sweep
- Break of structure
- Retracement into FVG
Everything checked out, and we entered the long position with our standard 1% risk and a 2% target.
The trade moved beautifully in our direction. In fact, we came within just a few pipettes of hitting our take-profit level. At this point, a trader who is actively managing the trade may consider scaling partial profits, reducing risk, or adjusting stops to protect open equity especially when price delivers most of the move.
But with a pure set-and-forget approach, none of those protective actions take place.
And that’s where the trouble began.
After almost reaching our TP, momentum shifted. Price stalled and slowly pushed back against us. What looked like a clean continuation setup turned into a full reversal, and the market drove straight through our stop loss. Instead of closing the week with a solid win, we took a loss not because the strategy failed, but because we didn’t adapt to the information the market was giving us in real time.
A set-and-forget approach sounds appealing:
- No emotions
- No second-guessing
- No screen time
But here’s the reality markets aren’t static. They evolve candle by candle.
Sometimes the difference between a +2% week and a –1% week is simply staying engaged enough to protect partial profits or take action when price hesitates near your target.
This trade wasn’t a failure. We followed our rules and we don't regret it. Do you prefer to set and forget or you manage the trade
The Anatomy of a Good Trade: Focus on Decisions, Not ResultsLet's find out - what is a good trade?
Most beginners answer: a trade that makes money.
But in professional trading, a good trade has nothing to do with the outcome.
It has everything to do with the quality of the decision.
1️⃣ A good trade starts with an A-Setup:
An A-Setup is not a feeling — it’s a repeatable pattern with structure and logic.
✔ Clear market context
✔ Direction aligned with market structure
✔ Liquidity levels identified
✔ Entry trigger confirmed
✔ Risk defined before the trade
If one of these is missing, it’s no longer an A-Setup — it’s hope.
2️⃣ A good trade has positive expectancy:
Winning one trade means nothing. Winning a sample size of 100 tells you everything.
A positive expectancy means your setup:
loses small - wins bigger - and performs consistently over time
You don’t need to win every trade — you need a system where the average outcome is in your favor.
3️⃣ A good trade follows process, not emotion:
A professional doesn’t judge a trade by profit or loss. They judge it by one question:
“Did I execute my plan without breaking the rules?”
If yes → it was a good trade. Even if it ended in a loss.
Because long-term success comes from repeatable behavior, not from chasing single outcomes.
The Truth:
➡️ A good trade is not defined by green or red.
➡️ A good trade is defined by discipline, structure, and execution.
If beginners understood this idea, half of their frustration would disappear.
Thanks for reading, and have a great start to your trading week!
Let us know in the comments if you found this post valuable - and we might create a full series on applied trading psychology.
Jonas Lumpp
Speechless Trading
Disclaimer: This tutorial is for educational purposes only and does not constitute financial advice. Its goal is to help traders develop a professional mindset, improve risk management, and make more structured trading decisions.
USE THE VIX TO TRADE BETTERSince the market has been a bit crazy lately, it's a good time to teach everyone about the VIX (Fear/Volatility Index) and how to use it to make your trading better.
In this video, I show you how I organize the VIX and use it every day to make my day trading and swing trading more adaptable to an ever-changing market environment.
VIX GUIDE:
Below 15: Low volatility. Calm markets, clean trend. Good for trend traders and swing traders.
15-20: Moderate volatility. This is the average level for the VIX. Market moves noticeably more.
20-25: High volatility. Big moves in the market start to happen at these levels. Great for experienced traders who like volatility. Caution for most other traders.
25-30: Extreme volatility. Tradable for experienced traders, but much greater difficulty level of trading. Most traders are advised to step back in this range.
30+: Chaos. Elite traders may profit, but it is very dangerous for the unprepared trader.
How to control risk? Some risk management tricksRisk management is fundamental in the investment ecosystem, and having absolute control over capital is often overlooked. Today I’m going to show you something new: How to keep the same percentage of profits or losses set by our trading plan under all circumstances.
When is leverage strictly necessary?
Leverage is essential if we want to trade in low-volatility conditions, where small price fluctuations would not translate into consistent profits.
For example, currencies have low volatility. In a trade I posted on my Spanish-speaking profile on April 22 in GBP/JPY, I was able to calculate beforehand that from the entry point to the Stop Loss (SL) there was a price movement of 1.27%. Without leverage, trading this would have been a terrible decision. It would mean that with a 1:1 risk-reward ratio we would be willing to win or lose only 1.27%. On most platforms, commissions alone would have eaten us alive.
However, wisely used leverage changes everything.
If I was only willing to lose 15% of the trade amount, I just had to divide 15% by 1.27% to know the necessary leverage:
Leverage = % of loss you’re willing to accept / % of volatility from entry point to exit point (SL)
15% / 1.27% = 11.81
With 11x leverage, my profits (or losses) would be the ones I had previously set (approximately 15%) if my SL or TP was triggered.
When should you NOT use leverage?
In Figure 1, I show an analysis (Tesla) that I published on May 2 on my Spanish-speaking profile. The volatility percentage from the entry point to the SL in my trade was 23.38%. Such a high movement percentage makes leverage completely unnecessary, considering that according to my trading plan I aim to keep my losses controlled (15% per trade). A 1:1 risk-reward ratio would mean that without leverage I would be exposed to winning or losing 23.38% of the invested capital.
Figure 1
How to keep my 15% loss limit in a highly volatile asset?
In the Tesla example, where volatility is high, the solution is simple: reduce the percentage of capital invested.
To do this, we just subtract 23.38% and 15% (the percentage of loss we are willing to accept per trade) and then subtract the result from our usual trade amount.
23.38% - 15% = 8.38%
Let’s imagine I use $200 per trade.
To calculate 8.38% of $200, we simply multiply 200 × 8.38/100. With this simple calculation we determine that 8.38% equals about $16.76 of the $200. Then we subtract that value from $200:
$200 - $16.76 = $183.24
In summary, if we reduced the trade amount to $183.24, it wouldn’t matter if Tesla moved up or down 23.38%. We would still be making or losing 15% of the original $200, thereby respecting our risk management.
Conclusions:
I believe risk management is the weak point of most investors. My intention has been to show, with practical examples, how easily trades can be executed while respecting the parameters of a trading plan.
Thank you for your time!
The Prop Trader’s Guide: Win Challenges. Keep Funding. Scale upHey Traders, today we are going to look at the prop trading. It can be solution for traders who has tested and proven their strategies. In this article, we’ll break down the risk rules that keep traders funded, the habits that build consistency, and the mindset that separates steady growth from emotional gambling. If you can master this part of the game, the rest becomes much simpIer.
1️⃣ You must have your strategy well defined and proved on your capital. Prop firms are not solution to the poor financial situation. If you dont trade well and consistently on small capital, bigger capital is not solution. First you need to solve this and have strategy with good winning ration and risk reward. You can check my one. for inspiration I have described it in this post below.
👇 Click the picture to learn more 2️⃣ Understand that in prop firms you are not trading real capital. They just sold you a demo with strict rules and if you pass and earn, they will pay you from what they earned on others who lost challenges. Hence rules are set such that it's not easy to pass and keep the account - but it's not impossible if you adapt.
3️⃣ $100K capital is not $100K if your maximum drawdown is 10%. In the fact your account is 10K - the amount you can really risk. Hence making 10% to pass first phase with 10% max drawdown equals making 100% gain. And second phase 5% adds another 50%. So to get funded you literally need to make 150% not 15%.
📍 If we know that 90% of traders , loose 90% of capital in 90 days on the normal accounts. What will be statistics of prop firms ? Even worse. But you have a chance. if you have a good winning ratio. Which you achieve by filtering just to the best trade setups. I have made it multiple times and still Im funded in Crypto and Forex prop firms. Most important think it this game is risk management. But before I will explain my dynamic risk management for each phase and funded account I give you some tips from my experience.
🧩 Essential Rules for Prop Trading
🧪 1) Its not a straight forward game
You must be ready to loose challenge and have money to buy another one. Don't expect get funded and keep the account forever. Unless you will risk 0,1% per trade. We want risk more, because you don't want spend passing challenge for a year. At some point you can loose account even with a good risk management. I lost over 30 challenges in different phases and funded accounts. My total investment was not small, but I withdrew multiple times more in 2025.
🧪 2) Reduce number of trades - Take only best trading setups
I trade less on prop account than on my personal accounts. I take there only A+ setups the ones which are obvious and Im confident to taking them. In the fact I should trade like this on my personal ones also, but I trade more often.🤷♂️
Don't fall for a trap to trade every day every move up and down. Have your routines. For your inspiration you can check this article 👇 Click the picture to learn more 🧪 3) Grow prop capital not % gains
If you would be hedge fund manager who deliver 3% a month consistently you would be considered as top star trader. However we as retail traders want more. Because we mostly don't have bilion dollars portfolio's. But if you work well in prop trading 3% Is life changing and its actually not difficult to achieve.
⁉️ How to achieve a 3% a month
Is 3% gain a month difficult ? If you risking 0.5% per trade with 1:2 RR it actually means That you must win just 3 trades. Now look at your Trade journal, you definitely had 3 good wins in a month. Only thing you need to do is to eliminate those other unnecessary trades.
$ 100K Funded account - 3% gain - 80% Profit split = $2400 payout
How to make more ? Don't go for bigger % gains. Get another funded accounts and build your capital. If you pass another 4 x $100K challenges you will get $500K AUM capital. Then with your 3% gain and 80% profit split = $12 000 payout.
Then you reinvest and you aim for $1000 000 funding to aim for $20K a month with making 3% a month.
🧪 4) Be patient and have a long term vision
Don't expect this happen in month or two. Write down your plan how you will acquire and will work on your prop trader career. Getting funded $1000 000 is a work for at least a year.
🧪 5) Don't trade all challenges at the same time
Yes you will be missing profits if you doing well, but if you loosing it will be affecting your portfolio completely. Take trades separately. I trade each pair on different props and Crypto also separately in the different prop firm.
🧪 6) Start with small $10K account to practice
Trading is performance discipline, dont put yourself under the stress by buying $100K or $200K challenge on the beginnings. Start with $10K just to practice and trade within their rules. Once you pass these easily you are ready to go big.
🧩 Dynamic Risk management for the Prop trading
When it comes to successfully passing Crypto prop challenges, an effective risk management strategy is crucial. Finding the right balance between risking too little and too much is key. Both extremes have their downsides; risking too little may result in prolonged evaluation phases while risking too much can lead to blowing through challenges quickly and struggling with the emotional aspects of trading.
Therefore, you can employ a dynamic risk management approach that combines the strengths of both methods. The specific risk management protocols may vary within different phases of the funded account, typically consisting of two evaluation phases and the funding stage upon successful completion of both.
1️⃣ The 1st Challenge Phase:
In this phase, where a 10% profit target is required for quick progress, you can adopt an aggressive risk management approach. With the following dynamic risk management
Start with risking 0.5% per trade
if your balance increases +1% increaser risk pert trade to 1%
if your balance increases +3% increaser risk pert trade to 1.25%
if your balance drops back to 0% reduce risk to 0.5% If your balance drops below 3% reduce risk per trade to 0.25%
If your balance drops below 5% increase risk to 1%
You might wonder why the risk per trade increases to 1% even when the drawdown exceeds 5%. This is to minimize time opportunity costs. Rather than slowly trading out of drawdown, you can prefer to increase risk and attempt to either break even quickly or accept the possibility of losing the challenge.
If you can not afford to lose a challenge, sticking to lower risk like 0.25% per setup until the account returns to break even might be a better option.
2️⃣ The 2nd Evaluation Phase – Verification
Once phase 1 is completed, and a lower profit target is required, a less aggressive risk management approach is employed:https://www.tradingview.com/x/Lrf4f1XO/ Aim to keep our time-based opportunity costs relatively low in the 2nd evaluation phase. Losing the 2nd phase account would mean having to repeat the 1st phase, which is why we adopt a more cautious approach and strive to minimize potential drawdown.
Risk is only increased when we have a cushion of at least +2%. If the drawdown falls below -2%, we maintain a risk of a quarter percent until the drawdown is fully recovered and back above the -2% threshold. This approach is designed to create a balance between preserving capital and meeting the objectives of the 2nd evaluation phase.
🎯 The Funded Account:
In the funded account, where both phases have been passed, preserving the account becomes the top priority, followed by receiving the first pay-out and refund of the signup fee. Funded accounts should be approached conservatively, and the risk management protocol is adjusted as follows:https://www.tradingview.com/x/QncyMGOz/ Lowering the risk per setup as the drawdown increases serves as a protective measure to prevent breaching the maximum drawdown rule. This approach may result in a longer process of trading out of drawdown, but it is a more favorable alternative to losing the account Completely.
As mentioned, your goal should be build longterm big capital and diversify between prop firms. For instance, you might allocate one account for swing trades and another for day trades. This diversification is just one example; there are various possibilities to explore.
👉 Prop Firms Selection
Opening a prop firm is easy, you just need couple thousands and you buy complete setup with platform and system. Then you start selling demo accounts. Hence there is thousands of prop-firms these days. You want to go just with the serious ones. Which means not the easiest conditions and not the cheapest challenges. But these will most likely last longer.
‼️ Avoid Prop firm which has:
- Cheap challenges or massive discounts
- Easy conditions to pass challenges
- Trailing Drawdown rules
- Too big profits splits
- Too many consistency rules
- Restrictions trading news
- Too many bad reviews (they will most like have more good reviews than bad - its Fake)
- If you Trade Crypto look for prop firm on Crypto exchange. Not in CFD broker.
Trading is not easy and prop firms makes it even more difficult, but its not impossible.
Expect failures and frustration on your journey. You can handle it, you will handle everything, you will always find solution. Keep going re-invest profits and build portfolio.
Main goal is to build personal account from their money without their rules.
Good luck
David Perk aka Dave FX Hunter
Improving My Win Loss Ratio In Forex Trading Achieved With 9.92%Not only I was able to achieve my Win Loss Ratio but I was able to make 9.92% profit in three weeks.
Improving my win loss ration in Forex Trading in this manner was amazing. Even when I started the improvements I didn't imagine I will turn the table 180 degrees. I was going to accept my Win Loss ratio to skew towards the loss side. With a good RRR the balance would still increase. But the result that I got is that my Win Loss is now 17:11 while before was something like 4:14. I don't have the exact old Win Loss ration anymore as the formula was damaged.
The search for a solid Forex Trading Plan is not over yet. The plan that I have is still scary and very risky, as it does not have any Stop Loss or Take Profit in it. I open several positions and then close them all as one batch once they reach an acceptable percentage of the current balance.
With the current method of closing the whole batch I am still leaving money on the table, and since I am trading the daily timeframe, a position trigger does not come easily. Trading this time frame is really scary and intimidating not to mention that I am trading it without any stop loss or take profit.
Unfortunately, I still didn't find a way to include those protections yet, but next week I will try to solve the challenge of leaving money on the table. Next week I will start dealing with each trade as a thesis of its own. Each trade will have it own story. Once the story approaches its end I will close the trade whether it is winning or losing.
Meaning, the thesis that opened the trade needs to change to close the trade. I am testing if I will have the stomach for such a scary ride.
Improving My Win Loss Ratio In Forex TradingWell, Some good news, actually great news. The experiment worked and in this video I show how I am improving my win loss ratio in Forex trading.
From a disastrous Win Loss ratio using only SMC now with combining the classical school along with the Stochastic I have been nailing it for the past 20 days with 22 trades and 8.6% increase on my balance.
In many cases, especially with advantageous RRR, it is Ok to have the win loss ratio in favor of the Loss, as the RRR will compensate and the balance would increase, but in this case I have the win rate higher and the RRR if it was calculated is also higher.
I depend on opening multiple trades and closing them all at once once they hit an acceptable percentage. In the video I said I will close them around 2%, but to tell you the truth, even if it was 1% I would close because no business I know of would bring 1% profit in a day.
The concern now with this Forex Trading Plan is that it does not use Stop Loss nor Take Profit. I feel that I am hanging in the air, which is not a good feeling and this might get me inside an emotional imbalance in the long run.
Still, the test is going on to evaluate all that.
ABCD Pattern Part 1: Double BottomsWe find the root of technical analysis in the systematic study of repetitive patterns in the historical price record. In the previous article, I explored key aspects of this discipline, such as its history and the fundamentals of its creation. Today, I will focus on a specific pattern, which I like to call the ABCD pattern , and specifically show its logic and practical uses for detecting entries in double bottoms. If my contribution is well received, I will soon show other variants.
ABCD is a basic price action structure; what would be an impulse (AB), a retracement (BC), and the continuation of the impulse (CD).
Historical Background
Classic authors such as R.N. Elliott, Goichi Hosoda, and Alan Andrews dedicated decades to the study of impulsive and corrective waves in the markets. Specifically, the ABC pattern (composed of an impulsive segment and a corrective one) has been a pillar in these theories. For R.N. Elliott, Fibonacci ratios were essential to predict future fluctuations in his Elliott Wave Theory. Alan Andrews developed his own tool, known as the Andrews Pitchfork, and Hidenobu Sasaki contributed to the popularization of Goichi Hosoda's methods in the 1990s, showing how his mentor used measurements to project waves and corrections.
As a contemporary reference, we have Scott M. Carney, a pioneer in harmonic trading. His methodology, inspired by the ideas of Elliott, W.D. Gann, J.M. Hurst, and H.M. Gartley, seeks to predict probable reversal zones in price action through Fibonacci ratios. Carney popularized the AB=CD pattern as a four-point structure where the initial segment (AB) partially retraces (BC) and then completes with an equidistant movement (CD), allowing the identification of entry opportunities at market extremes. This pattern, along with its alternate variants, forms the basis of his approach in books like The Harmonic Trader, where he emphasizes the convergence of ratios to maximize trading precision.
Let’s Keep It Simple: Description and Psychology of the ABCD Pattern
It is extremely harmful to memorize tricks, formulas, and patterns while discarding understanding. Price charts are, above all, a psychological phenomenon. Forgetting this, at best, would be underestimating our greatest advantage as technical analysts.
After investors profit from an impulsive wave (AB), at some point many will take partial or full closes of their positions, triggering a correction (BC). Once the price resumes its impulse in the direction of the prevailing force (CD), the eyes of many participants will be on the next correction or inflection point (D).
There are many psychologically attractive zones for taking partial position closes, and a Fibonacci extension is a useful tool, but there are so many implications of each ratio that investors will often feel overwhelmed by so much information.
Practical Use in Double Bottoms
Figure 1.1
In Figure 1.1, I show what would be a bearish impulsive wave making a correction. The horizontal lines show the zones where the price can approximately change direction, forming a double bottom.
Instead of memorizing and aligning Fibonacci combinations, I recommend detecting ABCD patterns over the zone, which will increase the effectiveness of our market entries. As confirmation, we will wait for a high-volume entry and a candle pattern that shows strength (false low, bullish engulfing candle, bullish hammer with a large wick or shadow).
A false low occurs when the price falls below the price action and bounces upward with force, leaving a wick or shadow at the bottom of the candle and an elongated body at the top (preferably without a wick or shadow), indicating strong rejection by buyers.
Figure 1.2
In Figure 1.2, we can observe a real example of the ABCD pattern application in corrections. Our lower line of interest is the one that truly confirms a double bottom thanks to a notable volume entry and an engulfing candle pattern.
It is necessary to train our eyes to volatile scenarios, quite unlike those we would find in books.
Figure 1.3
Figure 1.3 shows the scenario of an ABCD pattern at our first line of interest. Generally, the first line of interest will be around the 0.786 Fibonacci retracement zone, while the second line of interest is a bit more imprecise, but volume will tend to provide solid confirmation of buying strength.
Figure 1.4
Figure 1.4 shows in more detail how, over the zone of our first line of interest, we find a notable increase in volume. In this case, our entry confirmation would come from a false low.
Why is the second line of interest more imprecise to calculate than the first line of interest, but one of my favorites?
When the price reacts strongly below what would be a support zone in a double bottom, we are generally facing a bear trap, a scenario of extreme volatility.
Many bears who entered expecting the continuation of the downtrend will be forced to capitulate in the presence of strong buyer entry. This, added to the capitulation or partial closes of sellers who had positions taken previously, generates a scenario of extreme bullish volatility. I especially like these formations because of the notable volume presence that precedes them and the bullish force unleashed afterward.
Trade Management and the Importance of Break-Even
A Stop Loss (SL) adjusted below the zone where a bullish candle shows us strength will be extremely necessary in this type of formation, but it will be equally useful to understand that we want to use the force in our favor in the safest way possible.
A scenario where we ensure we don’t lose a penny will be psychologically comfortable, so setting an SL at a break-even zone once the price moves in our favor will be an excellent decision, especially in bear trap scenarios, where volatility will generally be high and consistent.
We should ensure a risk-reward ratio superior to 1:1, which will be straightforward if we use the SL as described before.
In Figure 1.5, you can see how a failed entry in interest zone 1 (which did not confirm correctly with a bullish candle pattern) would not mean a monetary loss if the SL had been moved to break-even; and in Figure 1.6, you will observe the correct trade management in a confirmed entry in interest zone 2.
Figure 1.5
Figure 1.6
Importance of the ABCD Pattern
The ABCD pattern reflects a part of investor psychology that, in the right context, can give us an extra point of statistical effectiveness. In double bottoms, I recommend taking entries at the first line of interest (around the 0.786 Fibonacci retracement) without neglecting the detection of the ABCD pattern and the always necessary volume and price confirmations.
At the second line of interest, considering that bear traps are extremely volatile, I believe we could overlook the detection of this type of pattern (ABCD), without discarding the notable volume entry and the candle pattern that confirms the entry.
Final Words
There are many contexts where an ABCD pattern will be our edge, but I have limited myself to addressing my personal application in double bottoms due to the complexity of the matter and the considerable time it would take me to exemplify each scenario.
If what is presented here proved useful, I will continue sharing in subsequent articles about different ways to establish effective entries using this pattern.
Bibliography
Bulkowski, T. N. (2005). The simple ABC correction. Technical Analysis of Stocks & Commodities , 23 (1), 52-55.
Carney, S. M. (2010). Harmonic trading, volume one: Profiting from the natural order of the financial markets. FT Press.
Elliott, R. N. (1946). Nature's law: The secret of the universe.
Morge, T. (2003). Trading with median lines: Mapping the markets. Market Geometry.
The Formula to Make $10000 Daily👋 Hello traders!
If you’re looking for a real way to make $10000 every day from the markets, forget about the so-called magic strategies or secret expert tricks.
The truth is simple: there’s no overnight success formula. But there is a realistic path built on probability, discipline, and time — and that’s what I call The Formula to Make $10000 Daily .
⚙️ Step 1: Build a High-Probability Trading System
📊 This is your foundation.
A good trading system doesn’t have to be complex, but it must have clear rules and consistent logic .
You should always know:
✅ When to enter a trade
✅ When to stay out
✅ And most importantly — why you’re entering
Choose a strategy you can truly master and apply consistently — such as Break & Retest , Supply & Demand , or Market Structure Shift .
Every trade should have a Risk-to-Reward ratio (R:R) of at least 1:2 or higher.
💡 Example:
If you risk $2000 per trade and win just two out of three trades daily, you’ll make $4000.
Increase your lot size gradually and stay consistent — $10000 a day becomes a realistic outcome.
💼 Step 2: Capital Management – The Key to Survival
🧠 You can’t make $10000 daily if you lose $10000 in one bad trade.
Capital management isn’t just about protecting your balance — it’s about protecting your mindset and system.
Follow these golden rules:
💰 Risk only 1–2% per trade
🛑 Always use a stop loss
🎯 Set a clear take-profit target
With a $50,000 account, risking 1% equals $5000.
If your R:R ratio is 1:3, one winning trade a day earns $15000.
That’s not luck — that’s mathematics working in your favor .
🧘♂️ Step 3: Master the Trader’s Mindset
Once you have a solid system and money management plan, the final piece — and the most important — is your psychology .
Most traders don’t fail because their system is bad. They fail because they can’t control themselves .
Keep these principles close:
🚫 Don’t trade when emotions take control
🚫 Don’t revenge trade after losses
🚫 Don’t increase lot size out of greed
🚫 Don’t force yourself to take trades every day
A professional trader doesn’t aim to win every trade — they aim to lose less and lose smart .
🧩 The Real Formula
💎 (High-Probability System + Strict Risk Management + Strong Psychology) × Time = Sustainable Profit
There are no shortcuts.
No magic indicators.
Only you and your discipline .
📖 Real Story
One of my students, Ken, started with a $10,000 account.
He didn’t try to go big — instead, he aimed to earn 1% a day , or $1000.
After six months, by slowly increasing his trade size and staying disciplined, his average daily profit reached $10000 .
He told me:
“I didn’t need to change my system. I just needed to change myself.”
🎯 Final Thoughts
The formula to make $10000 daily doesn’t come from any special indicator, signal, or secret course.
It comes from understanding your system deeply, managing your capital wisely, and staying disciplined every single day .
💬 The market doesn’t reward the fastest traders. It rewards the most patient, consistent, and focused ones.
If you’re on your journey to becoming a professional trader, start today.
🔥 Build your own formula — and practice it every single day until it becomes second nature.
Quantitative TradingThere are two main approaches to seeking consistent profits through the study of price history: the discretionary approach, based on experience and logical reasoning, and the quantitative approach, focused on identifying and exploiting behavioral patterns under specific market conditions.
Contrary to what’s usually thought, neither approach is exclusively intuitive or mechanical. Discretionary traders don’t operate solely on intuition, and quantitative ones don’t lack reasoning when building their systems. Both share fundamental elements: they rely on analyzing price history, spotting repetitive patterns, and applying statistical knowledge and risk management.
The main difference lies in flexibility. Discretionary traders enjoy greater freedom to make decisions, which can be harmful for inexperienced investors but a huge advantage for seasoned ones. Quantitative traders, on the other hand, follow strict rules, which reduces emotional influence and often allows automating processes to generate profits consistently.
This article is dedicated to exploring some vital concepts and ideas for developing solid and effective quantitative trading.
Key concepts about systems
• Quantitative systems require strict entry and exit rules
A quantitative system must be based on clear and objective rules for trade entries and exits. Though it seems obvious, many educational resources highlight metrics like win rates without considering the subjectivity in the systems they present, making reliable calculations impossible. Before evaluating a system’s stats, the investor must ensure all parameters are quantifiable and precisely defined.
• Trading systems are not universal
Each market has its own nature, which can be studied based on its historical record. For example:
• Trending markets , like SPY or Tesla, are driven by factors such as economic growth or market sentiment, making them ideal for systems that aim to capture directional moves.
• Range-bound markets , like Forex, are influenced by central banks promoting stability, limiting extreme moves and favoring ranges under normal conditions.
Applying a trending system to a pair like EUR/USD, which tends to consolidate, can lead to disappointing results. Similarly, using a mean-reversion system in a strongly directional market like the SPY ETF is illogical and usually ineffective. Plus, traditional markets have a structural bias favoring bulls over bears, which can significantly impact the performance of certain strategies.
On the other hand, timeframe is a critical factor when developing and evaluating quantitative systems. In lower timeframes, volatility from news, emotions, or high-frequency trading makes it hard to apply trending systems. Instead, higher timeframes (H4, D, W) offer more stability, improving the performance of many systems by reducing market noise.
• An effective quantitative trading system must be backed by a broad and detailed historical record
The larger the volume of data analyzed, the greater the confidence in the system’s ability to produce predictable results in the future.
A key aspect in developing quantitative trading systems is ensuring consistency in results. Consistency in a system’s performance across different timeframes (D, H4, H1) is an indicator of its robustness and adaptability. For example, a system that generates solid and stable returns across multiple timeframes shows greater reliability than one that only works well in a specific timeframe.
• We should avoid trading systems with unstable equity curves or large drawdowns
A quantitative trading system must be designed to generate consistent profits with controlled risk. That’s why it’s essential to avoid systems with unstable equity curves (erratic fluctuations in gains) or large drawdowns (maximum accumulated losses). These issues indicate a lack of robustness and can jeopardize the system’s long-term viability.
• A high win rate doesn’t guarantee consistent profitability
A common mistake among investors is assuming a high win rate ensures high and sustainable profitability. However, a quantitative trading system’s profitability depends on multiple factors beyond the win rate, such as the risk-reward ratio, market exposure, and operational costs.
For example, trending systems can generate larger profits but often have lower win rates due to greater market exposure, while systems with high win rates may offer limited returns because of shorter exposure and accumulated costs from high trade volume.
• Commissions and the number of trades must be factored into system testing
Failing to include these costs in the analysis can create a misleading perception of the system’s profitability, artificially inflating results.
Even a system with a stable and consistent equity curve doesn’t guarantee success if commissions aren’t considered, especially in strategies with low win rates or high trade volume.
• The risk-reward ratio must be adapted to the system
There’s no universal formula that guarantees profitability in all scenarios based solely on this parameter. However, using an inappropriate risk-reward ratio for the chosen system can lead to costly mistakes.
For example, applying a tight (low) risk-reward ratio in trending systems, or a high risk-reward ratio in mean-reversion systems or those exploiting small patterns, is an inconsistency that often results in significant losses for traders.
• About backtesting in TradingView
When a system is quantified on the TradingView platform, by default, profits and losses are calculated relative to the percentage of volatility. This means our margin per trade will generate losses or gains based on price movement.
For example, if our entry occurs on a bullish engulfing candle that closes above the EMA 20, and our SL is placed at the candle’s low, the losses from the entry point to the SL will be highly variable and depend on the volatility percentage, not on solid position management (like setting a 20% SL per entry, which would mean adjusting leverage). We could get three trades right in a row, and it’d only take the entry candle of the fourth trade to be huge for the losses to be disproportionate if the SL triggers.
This is especially important to keep in mind when backtesting systems on low timeframes, where volatility is extremely low. Without accounting for leverage and fixed loss percentages per trade, we might discard highly profitable systems, since the platform—calculating gains and losses based on volatility percentage—will always show poor profitability.
An inexperienced investor might face a system with a 60% win rate and a 1:1 risk-reward ratio, but if the backtesting is done on a 5-minute chart (where volatility is low), they’ll likely discard it due to the apparent poor profitability.
Conclusions
Developing effective quantitative systems requires an approach that integrates clear rules, rigorous testing, and a deep understanding of market dynamics. In upcoming articles, I’ll dive deeper into the topic, plus share my views and experience on other investment approaches.






















