Zeta

Trader | Data Scientist

[Zeta @Zeta__fx]

@isthattyler7 Can you open source it? The reason is to check overfitted or overcomplicated params.

[Zeta @Zeta__fx]

@MrMilkTrading 😂😂😂

[Zeta @Zeta__fx]

@blackcitadelx @TheParagonGrp Nice are they for free on TV?

[Zeta @Zeta__fx]

@VikasRatnu4 @swiftcapeas Won’t change anything but the results get even worse on real ticks. So @swiftcapeas has another filter

[Zeta @Zeta__fx]

@flatmoonsoc @Londonstrategic Genious!

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@SystematicEdge1 Check DMs :-)

[Zeta @Zeta__fx]

@algojan Why should someone pay for something like that where there are many git repos for free with the same functionalities?

[Zeta @Zeta__fx]

@onlybreakouts Overfitted

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@SystematicEdge1 Good job!

[Zeta @Zeta__fx]

@MrMilkTrading MT5 logo at its peak😂

[Zeta @Zeta__fx]

@gonzalomukherj1 Check the strategy forum

[Zeta @Zeta__fx]

New strategy out now in the discord. Source code for free🤝

[Zeta @Zeta__fx]

@gonzalomukherj1 @MrMilkTrading @etbent1 @PropQuantX In the discord: https://t.co/CBqZMLPSh5

[Zeta @Zeta__fx]

Thank you @MrMilkTrading and @etbent1 for this great strategy! I rebuild it in mql5 as well and got insane results with real ticks. This is Nasdaq and S&P500 in M5 and M15!

🚨Free source code in the discord of @PropQuantX

[🇳🇱💰 the Dutch Warren day trades📈🇨🇭 @etbent1]

Took you up on the "test it yourself."

Rebuilt it from the Pine source — an MQL5 EA and a Python twin, neither tuned toward your numbers. Ran it on USTEC instead of NQ.

You: 12,994 pts (2019–26)
Me: 13,038 pts (2020–26, where my data starts)

Different index, different window, ~2% apart. It replicates.

First thing I checked was whether it's just beta, since the index rose the whole time. Buying every open in the same 9:30–11:00 window gives +6.5
pts/trade over 1,716 trades. Your signal: +35.0 over 373. It also beats 1000 out of 1000 random-entry variants. The edge is real.

Two changes improved it, and both held on train (2020–23) and test (2024–26):

1. End the window at 10:00 instead of 11:00. Profit factor 1.97 → 2.34, and return/drawdown roughly doubles. It's monotone — every widening of the window makes it worse. That fits the construction: ATR(14) on a 10m chart is 140 minutes, so at 9:30 the normalizer is all premarket, and by 11:00 it's full
of RTH bars. The 3-ATR threshold isn't measuring the same thing anymore.

2. Exit at 61.8 rather than the full traverse to −100. Profit factor 1.97 → 2.16. Saty already plots that level.

Your threshold is right where it should be, though — I swept 80 through 120 and 100 is a clean peak on both halves, not a fitted edge.

On the missing stop, I measured instead of guessing. Winners' MAE: median 35 pts, p95 137. Losers: median 117. Any stop tighter than 150 costs real money — at 60 pts you give up 53% of total profit, at 100 pts 21%. At 200 pts it costs 1%. So there's room for a catastrophe stop, but not for a working one.

One caveat worth flagging: US500 gives the same answer, but only in the back half. Its 2020–23 profit factor is 1.14 against USTEC's 1.60.

[Zeta @Zeta__fx]

@MrFamilyOffice The last is dope

[Zeta @Zeta__fx]

Result of the strategy:
- Asset: BTCUSD
- Timeframe: H1
- Direction: Long only
- Period: 1.1.2020 - 31.12.2025
- No optimization

We would need the ATR stop, the EMA slow and EMA fast values to get similar results.

Free source code in the discord. No financial advice.

[The System Theory @SystemTheoryHQ]

HOW TO BUILD YOUR FIRST TRADING STRATEGY

Don’t start with random indicators.

Start with one question:

Why should this idea make money?

That’s your hypothesis.

STEP1️⃣: BUILD THE RULES

Keep it simple.

Example:

Market: Bitcoin
Direction: Long only
Entry: Fast EMA crosses above Slow EMA
Exit: Opposite EMA cross
Stop: ATR-based

No discretion.
Everything must be objective and testable.

STEP 2️⃣: BACKTEST IT

Now test the exact rules over a large sample.

Look at:

Profit Factor
Drawdown
Trade Count
Sharpe
Win/Loss distribution

Don’t ask only:

“Did it make money?”

Ask:

“Does the behaviour actually look robust?”

STEP3️⃣: TRY TO BREAK IT

Test:

Different parameters
Different markets
Different periods
Higher costs
Out-of-sample data

If it survives…
you may actually have something worth trading.

Hypothesis → Rules → Test → Validate
That’s how you build your first system.

[Zeta @Zeta__fx]

@PropQuantX Appreciate you!

[Zeta @Zeta__fx]

@x_insider4 Another clickbait post…🤦🏼‍♂️

[Zeta @Zeta__fx]

@Mr1CT Pathetic

[Zeta @Zeta__fx]

@etbent1 @MrMilkTrading I coded it for MT5. Free source code in the discord enjoy!