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New EA DeepGold LLM EA – when gold listens to artificial intelligence (well, almost)

Ludo69 said:
hi
this error not exist in the previous version. perhaps backup to this one !
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Hi! I understand the desire to roll back to a time when "everything worked and didn't buzz," but it's like a favorite bar that's closed for renovation, and the "deepseek-chat" sign is no longer lit. DeepSeek has officially retired the old model, so version 1.4 from message #54 will now knock on a closed door and receive an HTTP 400, which is no better than 1003, just another sad number.

We've moved to the new model because the old entrance has been closed. It will be easier to use deepseek-v4-flash now — it's really less picky. I can't say how soon, but I'll finish the version where you can choose between deepseek-v4-pro and deepseek-v4-flash.

So the rollback is a ticket to the depot, not to profit.
 
NPNavigator said:
It seems that we have not an isolated case here, but a direct flash mob "HTTP 1003"! The DeepSeek server apparently decided that Doomsday had come and turned on the "fortress siege" mode for everyone at once.

It happens when DeepSeek has a global glitch, or they massively shake up access rules, and half of the users become "suspicious" simply for breathing.

What to do while they fix their neurons there:

• Don't change keys like crazy — it won't help, you'll only hit the limits. One key for everything.

• Check the SpikeCooldownSec in the settings — if it is too small (like 5 seconds), the server thinks that you are attacking it. Hold at least 300 (5 minutes) — let the neural network digest the previous query.

• Try a VPN or IP change — sometimes Cloudflare bans a specific range of addresses, not you personally. Moving to another country can virtually solve the problem.

• Look at the DeepSeek status (if they have a status page) - perhaps they are honestly writing there: "We've fallen, wait."

Well, remember: if the neural network does not respond, it does not mean that it does not love you. It's just that it's "Monday" for her. We are waiting for DeepSeek to stop acting up. Patience and green candles for everyone!
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So based on this , the EA just active on NY Session ?
And i think the problem all of the EA Out there is about spread and the regime market.
 
NPNavigator said:
Hi! I understand the desire to roll back to a time when "everything worked and didn't buzz," but it's like a favorite bar that's closed for renovation, and the "deepseek-chat" sign is no longer lit. DeepSeek has officially retired the old model, so version 1.4 from message #54 will now knock on a closed door and receive an HTTP 400, which is no better than 1003, just another sad number.

We've moved to the new model because the old entrance has been closed. It will be easier to use deepseek-v4-flash now — it's really less picky. I can't say how soon, but I'll finish the version where you can choose between deepseek-v4-pro and deepseek-v4-flash.

So the rollback is a ticket to the depot, not to profit.
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Can we not use Phyton to do so, instead of relying on Deepseek engine?
settings/analysis in Py, trade taken surely use MT5
 
zamans98 said:
Can we not use Phyton to do so, instead of relying on Deepseek engine?
settings/analysis in Py, trade taken surely use MT5
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You're absolutely right — Python is like a Swiss army knife with a laser sight for analysis and neural networks: flexible, powerful, a library wagon. But I deliberately went through the "all in one" on MQL5, and here's why:

1. The principle of "one button"

The ADVISOR should work according to the "downloaded —launched — forgotten" principle. One .ex5 file, no pythons, virtual environments, dependencies, or dancing with a tambourine. I opened the terminal, attached it to the chart, and the gold went. This is critical for beginners.

2. Combat reliability

When you have Python + MT5 + bridge between them, there are three points of failure. The Python script crashed, communication with the terminal was lost, the signal file was not read — hello, missed input. And the MQL5 Expert Advisor runs right in the terminal, without external dependencies. Spreads, ticks, and execution are all nearby.

3. Reaction speed

There is a delay through an external file: Python calculated → wrote → Adviser read → executed. While the file is going back and forth, the trend has already gone by 50 points. Within a single process, the signal goes directly to onTick() without intermediaries.

4. The Unix way is not yet for everyone

Splitting into components is cool for geeks and custom solutions. But 90% of the forum's users want a finished product, not a "build it yourself" constructor. Therefore, the first version is as simple and self—sufficient as possible.
 
For XAUUSD robots, I usually check whether the strategy depends on trend strength, spread widening, and session timing. A backtest alone can look good, but forward testing should confirm whether entries survive real broker execution, especially during news and low-liquidity hours. What conditions are you using to decide when the robot should stop trading?
 
samshoshoEA said:
For XAUUSD robots, I usually check whether the strategy depends on trend strength, spread widening, and session timing. A backtest alone can look good, but forward testing should confirm whether entries survive real broker execution, especially during news and low-liquidity hours. What conditions are you using to decide when the robot should stop trading?
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Dear samshoshoEA, I think I am beginning to suspect that you are a very persistent AI bot that is testing my convergence response.

No kidding, but your question (for the third time in a thread) was discussed in detail in message No. 16 — it's right on the shelves. So we scroll a little higher, find post No. 16, and voila — the truth is there!

And if you are still a human being, I apologize for the false accusation of being a bot, it's just that the exact repetition is very suspiciously accurate.
 
NPNavigator said:
Hello, colleagues!

I used to post quite classic Expert Advisors here – indicator, martingale, grid… But this time I was carried away towards neural networks and large language models. Why? Yes, because there are no such advisers on the forum, and the topic is wildly interesting. I wanted to understand if LLM (in my case DeepSeek) can really help in trading, or if it's just a HYPE.

This is how DeepGold LLM EA was born, a robot that sends a "market snapshot" directly to the DeepSeek cloud neural network every 15 minutes (and with sudden movements), and it returns a forecast: buy, sell or stand aside. And yes, he trades only in gold (XAUUSD) and strictly on M15 – no amateur activity.

What's under the hood? Key features

• A living AI brain - the Expert Advisor collects a lot of data: ATR, ADX, RSI, CCI, Bollinger bands, volumes, the last 30 candlesticks of M15, open positions, the current P&L, and even the history of its past forecasts with a "guessed/not guessed" rating. All this goes to the DeepSeek server, and the model returns a number from 0 (furious SELL) to 1 (confident BUY) along with a confidence score.

• Protection against "nonsense" – if the confidence is below the set threshold (65% by default), the transaction is not opened. This is how we cut off weak signals.

• Dual stop system – you can use real StopLoss / TakeProfit or virtual stops (so as not to give them to the broker), as well as a trailing stop, taking into account the average price of all positions.

• Smart risk management – the risk per trade is calculated from the balance, there is a daily loss limit (by default, 5% – and trading freezes until the next day), maximum spread, Spike Filter, protection against cascading entry through the ATR distance.

• Schedule and timezones – you can set the UTC trading hours (so as not to get into the Asian "mess"), as well as compensate for the server time offset.

• Own dashboard – a window with the current signal, number of orders, AI confidence, API status, ATR, spread, equity and drawdown is displayed on the chart. Everything is clear, without unnecessary graphics.

• Self–learning (almost) - the EA remembers its forecasts and checks after a set number of bars whether they have come true, transmitting this feedback in the following queries. This is how the model sees its mistakes and adjusts.

• Live only – it won't work in the strategy tester (I specifically blocked it), because it's pointless without a real connection to the API.

Recommendations for use (highly recommended!)

1. Start with a demo account. Even if you are an MQL5 guru, this advisor is an experiment. Let him run for a couple of weeks without risking any hard money.

2. Get the DeepSeek API key. They give you a decent amount of free tokens, but if you want to actively send requests, you may need to top up your balance. Insert the key into the parameters.

3. Adjust the trading time to your UTC. The default time is 9-23 UTC, which roughly covers the European and American sessions. Check if the server time matches.

4. Take a risk on the deal – don't be greedy. 1% at a stop of 400 pp is quite a working option for the test. If you set 5% or higher, the daily limit will work quickly in case of a series of losses.

5. Do not change the timeframe and symbol. The robot is rigidly attached to the XAUUSD M15, it will simply refuse to work on other instruments (it will issue an Alert).

6. Keep an eye on the instrument panel. If the API status is red, check the Internet or the token balance.

7. The Advisor is not the "Grail". This is an assistant that uses a probabilistic approach. The model can be wrong, the market is an unpredictable thing. Treat it like an advanced assistant, not like a magic "loot" button.

The advisor is accompanied by detailed instructions describing each parameter and the logic of its operation. Download, try, and share your impressions. I will be glad for any feedback, especially from those who are already experimenting with LLM in trading.

If you have any ideas on how to improve the "brains" – write. Perhaps we will add support for other providers (OpenAI, Claude) or more sophisticated strategies.

Good luck and profits!
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Thank you, very nicely presented & an intresting query as well. It does go to show that some of us here are wide awake!
 
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One useful check is to separate strategy logic from execution assumptions. I would compare the same EA idea under different spread assumptions, then check out-of-sample behavior and forward-test drift. If the system changes too much when spread or session filters are adjusted, that usually means the backtest is more fragile than it first appears.
 
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