Oceanus EA: a gold M1 scalper that mostly waits

Gold on M1 moves enough every day to look like free money. Then you run a scalper on it for a month and find out where the money went: spread, commission and a few dollars of slippage on every single trade. Most M1 gold EAs aren't wrong about direction. They just trade too often for whatever small edge they have to survive the costs.

Before you read further: I built Oceanus and I sell it, on the MQL5 Market and on GogoJungle. So this isn't an independent review. The numbers below come from my own simulation on real Exness ticks and from the MT5 Strategy Tester, and they're backtests unless I say otherwise. There's also a live signal on a real account that you can check yourself.

The product pages are short by design. This post covers what didn't fit there: what the EA actually does all day, how to read the backtest, and which account and deposit make sense. That last part matters more than I expected.

What a selective gold scalper EA actually does

Most of the time, nothing.

Oceanus has three layers, and only one of them is about entering trades:

1. Timing. Two machine-learning models run inside the EA and look at the gold tick stream once a minute. Their only job is to say whether the next stretch of time is worth trading. Most of the time they say no.
2. Direction. When the models allow it, a simple rule waits for price to commit to one side and enters that way, buy or sell.
3. Management. Stop loss from the first tick. A quick move to breakeven, set $0.30 in profit per 0.01 lot so commission is covered. A trailing stop that only tightens. And a time limit, so a trade that hasn't done its job gets closed instead of left open for days.

I'm not going to publish the exact rules or the model inputs, for the obvious reason. But the split matters, because it explains how the EA behaves. The models never decide buy or sell. I tested that: models asked to predict direction from price features scored no better than a coin flip (AUC 0.47 to 0.52). Models asked whether gold is about to move a lot did much better. On the 2026 data, which they never saw during training, they were right about 70% of the time, against 58% for always guessing the most common answer.

So the ML picks the moment and the rules handle the rest.

In practice that means a median of 4 trades on days when it trades, up to 37 on a wild day, and about one weekday in ten with no trade at all. Median time in a trade is 13 minutes, and 90% of trades are closed within an hour.

How I got here (the short version)

Oceanus didn't start as a breakout system. It started as an attempt to make a grid EA safer by letting the models decide when the grid could open. I simulated that across 4.7 years of ticks and the grid made roughly zero before costs, whatever the models said. After costs it lost. So I dropped the grid and kept the models.

The part that took the longest wasn't the strategy, honestly. It was getting the models inside the .ex5 to give exactly the same answers as my Python originals, minute by minute. They now match to the seventh decimal place. When I ran the finished EA in the MT5 Strategy Tester on every real tick from March to May 2026, it took 888 trades. My research simulation took 889 on the same months.

One decision that surprised me: the time limit. About 12% of trades end because time ran out, and as a group those trades lose money (-$2,167 at 0.01 lot over the full test). The obvious fix is to drop the limit and give them more room. I tested that on October 2. It was worse. Trades that are still red after the window tend to go on and hit their original stop. Cutting them early is part of the edge.

Backtest results, read properly

Conditions for everything in this section: XAUUSD, Exness Raw Spread tick data, real spread on every tick, commission $0.04 per 0.01-lot round trip, fixed 0.01 lot, current trading logic (v1.23). January 2022 to September 16, 2026.

Year	What gold did	Trades	Result at 0.01 lot
2022	choppy, rate hikes	952	-$0.30
2023	quiet range	539	+$29
2024	rally starts	808	+$75
2025	strong trend	1,509	+$654
2026 (to Sep 16)	big swings	2,367	+$1,091
Total		6,175	+$1,848, profit factor 1.13

From January 2024 on (the period in the charts): 4,684 trades, +$1,819, profit factor 1.14, max drawdown $224, which is 9.8% measured from the equity peak on a $2,000 start.

Look at the yearly table again, because it tells you what kind of EA this is. It earns when gold moves. In 2022 and 2023 it barely did anything useful, it just didn't lose. In 2025 and 2026 gold had its busiest stretch in years and that's where nearly all the profit is. If gold goes quiet for a year, expect a flat year.

Over the whole test, 30 months closed green and 27 red. Worst month: September 2024, -$83. Best: October 2025, +$405.

Why a 74% win rate and only PF 1.13? Because most wins are small. 70% of trades close at a stop that's already been moved to breakeven or trailed, averaging +$3.41. Only 38 trades out of 6,175 ever reached take profit. The losers that hit the original stop are 17.5% of trades, and they average -$10.61. In 2024-2026 the average win was $4.21 and the average loss $10.79. So the win rate is high because the breakeven locks in a little on most trades, not because the EA is clever at picking winners.

The 10 worst trades

I publish these for every EA I test. All at 0.01 lot, times in UTC.

#	Entry	Exit	Side	Entry price	Exit price	P/L	Exit reason
1	2026-02-03 01:32	02:26	Buy	4856.80	4769.02	-$87.83	original SL
2	2026-01-30 15:05	15:18	Sell	4981.44	5058.63	-$77.23	original SL
3	2026-03-09 01:01	02:10	Sell	5018.09	5091.34	-$73.29	original SL
4	2026-03-24 02:11	02:46	Sell	4307.74	4378.06	-$70.36	original SL
5	2026-02-05 08:13	09:04	Buy	4941.19	4883.23	-$58.00	original SL
6	2026-02-03 19:04	19:38	Sell	4884.92	4939.41	-$54.54	original SL
7	2026-02-05 16:54	18:16	Buy	4902.92	4851.70	-$51.26	original SL
8	2026-06-24 13:13	13:42	Sell	3967.06	4017.13	-$50.12	original SL
9	2026-02-03 16:38	17:08	Buy	4989.02	4941.19	-$47.87	original SL
10	2026-02-04 14:39	14:54	Sell	4971.54	5017.84	-$46.35	original SL

This is the weak spot, and I'd rather you see it here than find it on your account. One of these trades wipes out 10 to 20 small winners. Nine of the ten happened between late January and March 2026, when gold was swinging $100+ in an hour. The stop is placed by market structure, not a fixed number of pips, so in a violent market it sits far away. The EA survived that stretch and finished 2026 well up, but those weeks were rough.

Costs. Add up to $0.10 extra cost to every single trade (wider spread, higher commission or slippage) and the profit factor stays above 1.10.

If you want to check any of this, Oceanus is on the MQL5 Market with a free demo for the Strategy Tester. Backtesting instructions are further down.

Which account type should you run it on?

A raw-spread account. The account choice moves the result more than any input setting does.

Same EA, same rules, same gold, run on tick data from different account types. First, Exness Raw against Exness Standard Cent over the full period:

Account	Trades	2022-2024	2025-2026	Total	Profit factor	Max DD
Exness Raw	6,123	+$103	+$1,769	+$1,872	1.13	$224
Exness Standard Cent	6,076	-$248	+$1,595	+$1,347	1.09	$425

v1.23, Jan 2022 to Sep 16 2026, results expressed for a standard 0.01 lot (on a cent account the same figures are in US cents at 0.01 cent lot). March 30-31, 2026 is excluded for both accounts because the Exness tick archive for the cent symbol is missing those two days.

The gap in gold spread makes a cent account cost roughly $0.10 to $0.20 more than Raw on every trade, even after you count Raw's commission. Gold spread on the cent account ran $0.16 to $0.36 in the months I checked, against $0.04 to $0.14 on Raw. That's about $0.08 less profit per trade, and with an edge this thin it's the difference between 2022-2024 at -$248 and the same three years slightly positive on Raw.

Then a wider comparison over a shorter window, including a second broker:

Account	Total, Apr 2025 to Sep 16 2026	Profit factor	Max DD
Exness Raw	+$1,797	1.16	$233
Exness Zero	+$1,913	1.17	$275
Pepperstone Razor	-$246	0.98	$608
Pepperstone Standard	-$284 to -$420	0.97-0.98	$536-554

Earlier build (v1.21: same entries, breakeven at zero instead of +$0.30), 0.01 lot. Pepperstone Standard was simulated as Razor prices plus a 0.10-0.13 markup.

Pepperstone surprised me. Part of it is cost (wider spread, higher commission), but the bigger part is how its price moves at the exact moment Oceanus enters. When gold starts running, Pepperstone's quotes jump further past the entry level than Exness quotes do, so the entry price is about $0.18 worse per trade on average, and much worse around US news at 12:00-15:00 UTC. That's before any commission.

My take, account by account:

• Exness Raw or Zero: what I use and what all the main numbers are based on. Raw has the more predictable cost.
• Another broker's raw/ECN account: possibly fine, but backtest on that broker's own real ticks first. Low commission alone isn't enough, as the Pepperstone line shows.
• Exness Standard Cent: it works, more weakly. Good for running it live on small money while you watch it. Not where I'd expect the full result.
• Standard accounts with wide gold spreads: I wouldn't.
• Prop firm accounts: stop loss on every trade and one position at a time suit most rules. There's no built-in daily loss limit, though, and a single bad trade can reach $88 at 0.01 lot, so size against your firm's daily limit.

How much capital, and what profit is realistic?

At 0.01 lot on a raw account, I'd start with $2,000. That put the worst drawdown in the test at 9.8%.

Setup	Deposit per 0.01 lot	What the backtest says
Conservative	$2,000	max DD 9.8% (2024-2026)
Moderate	$1,000	same $224 drawdown, now roughly 20% of the account
Compounding	add 0.01 lot per $1,000 of balance	$10,000 to $39,511 over 4.7 years, max DD 22.5% (closed trades, earlier build v1.21)
Cent account	$50	worst DD in the test was 425 cents ($4.25), so the deposit isn't the issue, the thinner edge is

On profit, think in dollars per 0.01 lot per year rather than a monthly percentage, because the answer depends on gold. In a quiet year the backtest made somewhere between nothing and +$75 per 0.01 lot. In a busy year, several hundred. If someone promises you a fixed monthly return from a system like this, they're guessing.

I deliberately didn't build in "% risk per trade" sizing. I tested it: profit came out about the same as a fixed lot while the drawdown went to 39-46%. Small stops make small risk-based lots, and commission is a fixed cost, so the tight-stop trades become expensive. A fixed lot that you raise yourself works better here.

Getting the most out of it

• Use a VPS close to your broker. Entries are market orders taken while gold is moving fast, so milliseconds turn into cents. My VPS in Vietnam pings the Exness server at 63 ms. The first one I used, in Germany, was at 190 ms.
• Set InpServerUtcH correctly. It's your broker's server time minus UTC (0 for Exness). It's the one setting people skip, and it shifts everything the models see.
• Start small. Two to four weeks on demo or at 0.01 lot before you size up.
• Read the slippage log. The EA writes every fill against its expected price to Common\Files\Oceanus. If your fills are consistently worse than about $0.10, your broker or your VPS is eating the edge.
• Don't switch it off in a drawdown. The profit comes in a few busy months. Pausing after a bad week is a good way to miss the month that pays for the year.
• Raise the lot after you've sat through a real drawdown, not after a good week.

For backtesting: set InpModels to Exam, use "Every tick based on real ticks", and start the test 16 days before the period you care about so the EA can warm up. The Exam models were trained only up to the end of 2025, so a 2026 test is genuinely out of sample. That's the one I'd look at first.

Questions you're probably asking

"Almost all the profit is from 2025-2026. Isn't that overfitting?"
Fair question. Two things argue against it. The 2026 results come from models that never saw 2026 data. And the pattern has a plain cause: the EA trades movement, and 2025-2026 had the most movement. What I can't promise is that gold stays this busy. If it goes quiet, expect results closer to 2023.

"How is the live account doing?"
The live signal has run on a real Exness Raw account at a fixed 0.01 lot since October 1, 2026. That's days, not months, so it doesn't prove anything yet. I'm using it to measure real slippage against the backtest. I'll update this section as the record builds.

"Why didn't it trade today?"
The models didn't like the market. The panel on the chart tells you whether it's waiting or armed.

"Can I run it on another symbol or timeframe?"
No. The models were trained on gold M1 and nothing else.

If you're still reading

You probably care more about how the numbers were made than about the numbers themselves, and that's the reader I write for. I review other people's strategies on this blog the same way. The TradingView SuperTrend strategy backtest and the follow-up on optimizing SuperTrend for gold are good examples: one setup looked great right up until I shifted the candle open by an hour.

Oceanus is available on the MQL5 Market and on GogoJungle. Updates are free, and every new version gets re-run on the full tick history and in the MT5 tester before it ships.

Last updated October 5, 2026.

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Risk warning: trading gold and CFDs carries a high level of risk. All figures above are backtests on historical data unless stated otherwise. Past performance does not guarantee future results. Test on a demo account first and only trade money you can afford to lose.