Hamid
28 posts


@TraderYush @TradingLucid I don't trade Fitures. This give me a chance to swap a future account with a cfd lol
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giving one trader who ♥️s this a @TradingLucid 25k flex.
winner tomorrow after market close
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1st payout at 19y after +1y of trading
I was fortunate enough to discover ICT from day one. I was even more lucky to be coached 1 on 1 by my mentor for several months who made my trading goes into the next level
$900 may not seem like much compared to the massive withdrawals often showcased on social media
but it’s still more than what 97% of traders achieve, more importantly, it rewards all the sacrifices & efforts
But anyway, focus to achieve more before the end of the month.

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Secured next payouts with @fundingpips
9000$ across 3x100k💪
Gold shorts finally paid off, now let’s wait for the payday.
#xauusd


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@Tahirabdikani1 Trade with smallest lot and one trade per day. Its gonna control your emotions of not taking Trades each day😉
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Hamid retweeté
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If I were entering the 2027 Futures World Cup, I'd start from a premise most competitors miss:
Identify the objective through a game theory lens.
The objective isn't riskadjusted returns.
It's asymmetrical to the hedge fund approach.
A hedge fund maximizes return per unit of risk.
A trading competition rewards only one metric:
Net Return.
Different game. Different optimization function.
For the first quarter, I wouldn't focus on profits.
I'd focus on information.
Three independent models tested on three sequential accounts:
• Momentum
• Mean Reversion
• Pure Trend Following
Why?
Because no backtest can fully replicate:
• Live execution
• Slippage
• Liquidity constraints
• Competition commission structure
The first quarter is an intelligence gathering phase focused on regime identification and OSS live condition testing.
At the same time, I would monitor the average performance emerging on the leaderboard and use that information to calibrate risk allocation for the future podium account.
The objective is to reduce uncertainty and identify which model possesses the highest live expectancy under the exact conditions of the competition while remaining robust under high execution frequency and elevated risk.
Then comes the Deployment phase.
Open a dedicated podium account.
Select the model that, based on both OSS testing and current Regime detection, demonstrates the highest expectancy.
One model.
One framework.
The remaining nine months are dedicated to deploying the snowball effect:
Use a portion of accumulated profits to scale performance, progressively increase risk as equity grows, and continuously benchmark against the return threshold required to reach the podium.
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Hamid retweeté

One of the most expensive mistakes in systematic trading is selecting a model before identifying the regime.
A Momentum strategy and a mean reverting strategy can both exhibit positive expectancy, attractive Sharpe ratios, and robust OOS results.
Yet over a single quarter, their performance distributions can diverge dramatically.
Why?
Because alpha is often regimedependent.
A volatility expansion environment rewards momentum persistence.
A volatility compression environment rewards mean reversion.
The model didn't change.
The market structure did.
Before asking whether a strategy works, ask:
Under which conditions was that edge created?
Regime first.
Model second.
This is why many large funds allocate simultaneously to:
Trend Following
Mean Reversion
Global Macro
Volatility Arbitrage
Relative Value
Market Neutral
Event Driven
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Hamid retweeté

The biggest productivity boost of my life wasn't a new business, a new strategy, or a new hire.
It was building an AI that doesn't care about my feelings.
It organizes my nutrition.
It audits my trading.
It monitors my health.
It plans my business.
It challenges my excuses.
It rewards execution.
No sugarcoating.
No motivation speeches.
No "you got this."
Just brutal accountability and objective feedback.
I use it as an operating accountability system.
The cyborg era it's here, without any chip implanted in your brain.
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Hamid retweeté
Hamid retweeté

Value Drop #1
Research → Hypothesis → Validation → Out-of-Sample Testing → Live Deployment.
The best edges I have tested that survived this framework:
• US Equities Drift with Volume Confirmation | IVB, ORB or IB Volatility Breakout | Timing Improvement using Orderflow Data
• Earnings Surprise Drift Effect | Paired with Sector Analysis
Congressional Trades Portfolio | Information Asymmetry
• Option Premium Harvesting | Implied Volatility > Realized Volatility
• Blockchain Intelligence Statistical Models | Mathematical DCA
These are not models I use because I like them.
They are supported by decades of academic research, validated across multiple markets and countries, tested by thousands of researchers and practitioners, and have demonstrated persistence across different market regimes and economic cycles.
PEAD, momentum, earnings drift, and related anomalies have been documented, replicated, challenged, and studied extensively for decades across global financial markets.
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Hamid retweeté

To celebrate the launch of Zella AI, we're doing a huge giveaway! 🔥
5 winners. Each gets both prizes:
→ A $50K Tradeify Account
→ 6 months of TradeZella Pro with Zella AI
To enter:
1. Like + RT this post
2. Follow @TradeZella + @Tradeify
3. Tag 1 trader in the comments
Winners in 48 hours! ⏰

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