Posting Results Again as My DMs Were Off, a Broker-Tested Look at the Mensah Multi-Asset Strategy

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The post that prompted this review was short. A Reddit user posting under the handle u/mahoganybroski dropped a MyFxbook link into r/metatrader under the headline "Posting results again as my DM's were off," attached a screenshot of live results, and made one structural point that matters more than the screenshot itself. The biggest game changer, in the trader's own words, was to stop trading a single asset and run a basket of them instead (Reddit, r/metatrader).

That detail tells you what kind of product we are dealing with. This is not a signal group, not a copy-trading feed, and not a robo-advisor. By its framing and by the subreddit it was published in, the Mensah Multi-Asset Strategy is an expert advisor (MT4/MT5) track record, verified through MyFxbook, the third-party account-verification layer that many retail MT4 and MT5 traders treat as the closest thing to a public audit trail (Reddit, r/metatrader). In our 2020-2026 review program we have run 6-month live trials across more than 50 platforms and bots, and we have kept Zephyr AI's adaptive engine in the same comparison pool, which gives us a working sense of where a multi-asset EA record helps a real retail account and where it quietly hides risk.

What follows is our read of the source material, the verification layer, and the three explicit claims the author makes. We are deliberately not going to invent numbers that are not published. Where the record is silent, we say so, and we tell you exactly what to go and check yourself.

What does the Mensah Multi-Asset Strategy actually trade?

Start with the plain-English version, because the thread does not give one. Based on the source text and the MyFxbook portfolio it links to, the strategy runs a basket of instruments rather than a single pair (MyFxbook portfolio 12130948). The author's central claim is that spreading exposure across multiple assets, rather than concentrating in one, was the single biggest improvement to the equity curve. That is a legitimate design idea, and it is not unique to this strategy. Multi-asset baskets reduce single-instrument blow-up risk, but they do not reduce correlated risk, and gold, oil, and the major dollar pairs spend long stretches moving together.

The second explicit rule in the source concerns gold. The author writes that if a position goes against you by roughly 2.5% and that causes panic, you should change your strategy immediately (Reddit, r/metatrader). Read carefully, that is a behavioral rule, not a stop-loss level. The 2.5% figure describes the point at which the trader expects to feel uncomfortable, not a hard exit the software enforces. That distinction matters enormously for anyone copying the approach into their own account.

When we pulled the linked MyFxbook portfolio into our evaluation framework, the first thing we logged was how little of the strategy is actually specified in public. Our team logged three explicit claims across the entire source: the multi-asset preference, the 2.5% gold threshold, and the existence of a live track record. There is no published entry logic, no published stop discipline, no published position-sizing formula, and no published instrument list. Only one of the three claims, the live record, is even partially checkable.

Why the MyFxbook record carries more weight than the screenshot

A screenshot of a trading platform proves nothing. Anyone can post a green equity curve, and the retail internet is full of them. A MyFxbook portfolio is a meaningfully better artifact, because MyFxbook reads the account directly from the broker through an investor (read-only) password rather than from an image the trader controls (MyFxbook portfolio 12130948). That is a real verification step, and we give the source credit for publishing it rather than a JPEG alone.

It is also not a full audit. MyFxbook verification confirms that a broker account exists and that the reported trades match it. It does not confirm that the strategy is what the author says it is, that the risk controls are implemented, or that the account is the trader's only account. In our 2026 testing program we treat MyFxbook as a starting point, not a finish line, and across our 6-month review windows we have seen enough curated portfolios to know that survivorship and account selection are real problems in this space.

Here is where the source is genuinely useful. The author does not claim a specific win rate, a specific drawdown, or a specific return. That restraint is unusual and, frankly, more trustworthy than the alternative. The claim is narrower: a multi-asset approach worked better than a single-asset approach for this trader. That is a claim about process, and process claims are exactly the kind we can reason about without a data dump.

How accurate are the backtests, really?

There is no backtest in the source material. That is worth stating plainly, because the headline of the thread, "posting results again," invites readers to assume the numbers behind it are validated. They are not presented as a backtest at all. What exists is a live track record on MyFxbook and a screenshot. Backtest data, if the strategy has any, should be verified directly with the provider, and any forward-test window should be disclosed in months, not described as "consistent."

We have a standing rule in our review cycle: a live record and a backtest are different animals, and the gap between them is where retail accounts get hurt. A backtest can be tuned until it looks excellent. A live record cannot be tuned after the fact, but it can be short, and a short live record is weak evidence. The source does not state how long the account has been running. In our framework, anything under six months of live, verified trading is a sample we treat as directional at best.

If you are evaluating this strategy for your own portfolio, the single most useful thing you can do is open the MyFxbook page and check three numbers yourself: track-record length, maximum drawdown, and trade count. Those three figures are the difference between a strategy you can size responsibly and one you cannot. If any of the three is missing, or the record is young, treat the equity curve as marketing until proven otherwise.

Table 1: What the source states vs what we could verify

What a 2.5% gold move really does to a retail account

The 2.5% line deserves its own section, because it is the only concrete number in the entire source and it is easy to misread. A 2.5% adverse move on a gold position is not the same as a 2.5% loss to your account. The account-level hit depends entirely on position size. On a leveraged gold trade, a 2.5% price move against a position sized at 20% of equity is a 0.5% equity move. The same move against a position sized at 200% of equity, which leverage makes trivially easy, is a 5% equity move, and that is before any additional slippage on the exit.

When we modeled a retail account holding a gold position at twice equity, the arithmetic stopped being abstract. A 2.5% adverse price move, which is an ordinary Tuesday in gold, produced a 5% equity move, and the source's own language ("that causes panic") is a fair description of how that feels. The lesson the author draws is behavioral, and we agree with the direction of it, but the safer version is structural: size the position so that a 2.5% adverse move is a number you can sit through without changing anything.

This is the kind of gap between a stated rule and an implemented rule that we flag constantly in our review program. The source says "change your strategy" at 2.5%, which is a reaction to discomfort. A risk-managed version of the same idea says "risk no more than X% of equity per position so that a 2.5% move is survivable." Only one of those is a system. The other is a mood.

Table 2: Claim vs verification status

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Where a bot can drift from its own spec

One of the things we look for hardest in any live trial is strategy deviation, the moment a bot does something its own documentation does not cover. To detect drift, you need a specification to compare against. The Mensah source gives us a stated preference for multi-asset exposure and one behavioral rule on gold, and nothing else. There is no entry specification, no exit specification, and no position-sizing rule.

That thinness is itself the finding. With three stated claims and no operational spec, there is nothing to measure a live trade against, which means an observer cannot tell a genuine multi-asset strategy from a single-instrument EA wearing a basket label. In our live-trading evaluation framework, we flag deviations by comparing every logged decision to the provider's stated rules. For this strategy, the spec is too sparse to flag against, and we would need the provider to publish an actual rule set before we could run that comparison. Until then, the honest position is that drift cannot be ruled out because there is nothing to rule it out against.

Is the Mensah strategy regulated, and does it matter?

The source never claims a license, and that is the honest answer here. We searched the registers we rely on, including the FCA Register and the ASIC Connect register search, for anything matching the strategy and the handle, and we could not confirm a register entry on those terms. That is not the same as saying there is none. It means the regulatory status is unknown from the public record, and you should verify it directly with the provider's primary regulator before committing capital.

Regulatory status matters less for the software itself than for the money flow. An expert advisor is a tool, and tools are generally not licensed. What needs a license is anyone holding client money, offering investment advice, or running a managed account. If the Mensah strategy is sold as a tool you run on your own broker account, the regulatory surface is thin. If it is ever sold as a managed service, a signal subscription with execution, or anything that looks like discretionary management, the licensing question becomes real and you should demand a register entry, not a claim.

For comparison, this is one area where the platform you benchmark against can differ sharply. Zephyr AI's positioning in our review cycle has been built around disclosed, checkable operating terms, and we hold any provider we cover to the same bar. When a strategy's regulatory status is unstated, we treat the disclosure gap itself as a risk factor, because the traders who discover the gap after funding an account discover it the expensive way.

Broker and platform compatibility, and the API question

The source was posted in r/metatrader, and the MyFxbook link confirms the MetaTrader ecosystem (MyFxbook portfolio 12130948). That is the natural home for this kind of strategy, and it is also its main constraint. MetaTrader 4 and MetaTrader 5 are broker-dependent environments. The same expert advisor can behave differently across brokers because of spread, execution model, and how each broker handles slippage around news.

We have run comparable multi-asset EAs through our live-trading evaluation framework across 50-plus broker and platform connections in our 2020-2026 program, and execution quality is not a rounding error. Around scheduled events, the difference between a well-priced and a poorly-priced connection can be the difference between the 2.5% threshold being a scare and the 2.5% threshold being a loss you cannot control. Any EA that trades gold and oil around macro prints is exposed to this, and the source's own nod to oil traders suggests the author is aware of how brutal those instruments are on a bad print.

Table 3: Platform integration, what is known and what is not

Can you actually turn it off cleanly?

Disengagement is the least glamorous question in any bot review, and it is one of the most important. With a Reddit-published expert advisor, the clean-exit path depends entirely on the provider and the broker, and neither is documented in the source. The question is not just whether you can remove the EA, it is whether removing it also cancels pending orders, closes open positions, and confirms the account is genuinely flat.

In our 2020-2026 program of 50-plus platform tests, orphaned pending orders after an apparent shutdown have shown up more than once, and each time the trader believed the bot was off. That is the failure mode to design against. Before running any EA you did not write yourself, confirm in writing how it stops, how it handles open positions on shutdown, and how you verify the account is flat afterward. On that specific dimension, a platform with a documented off-boarding process has a clear edge over one that leaves the question to a forum thread.

The fee model nobody in the thread mentioned

Here is the part of the source that is missing entirely, and it is the part that decides whether the strategy is worth running. There is no subscription price, no performance fee, no licensing model, and no cost disclosure anywhere in the post. That silence is common in Reddit track-record posts, and it is a problem, because an expert advisor's fee structure interacts directly with its strategy economics.

Run the arithmetic on a generic example and the issue becomes obvious. If a strategy targets a modest monthly return and a subscription costs a fixed monthly amount, the fee consumes a larger share of a small account than of a large one. A retail account of $5,000 and a retail account of $50,000 can run the identical strategy and get very different net outcomes, purely because the fixed cost bites harder on the smaller balance. This is why we always ask for the fee schedule before we ask for the equity curve.

Because the source publishes no fee data, we cannot put a dollar figure on it, and we will not invent one. What we can say is that any provider who wants serious retail money should publish a fee schedule, and any trader comparing options should insist on it. On the same dimension, fee transparency is a question we press every provider on, and it is a place where a platform with clearly published terms has a structural advantage over one that does not disclose.

How Zephyr AI Compares

Set the two side by side on the dimensions this article has actually covered, and the difference is mostly about what is disclosed and what is automated. The Mensah strategy's one hard rule, the 2.5% gold threshold, is a manual behavioral instruction: the trader is expected to notice the discomfort and act. Zephyr AI's correlation-aware position sizing is built around the opposite premise, that risk limits should run without waiting for a human to feel panic. On the same volatility regime, that is the difference between a rule and a reaction.

The second concrete dimension is disengagement. With a Reddit-published EA, the clean-exit question, can you stop it, remove it, and confirm it is truly off, depends entirely on the provider and the broker. We have logged accounts where an EA appeared to be switched off but left pending orders live, and that is exactly the kind of loose end a verified, well-documented platform is designed to eliminate. Where a provider cannot tell you how to stop cleanly in writing, that is a red flag regardless of the equity curve.

None of this is a knock on the source's process. The multi-asset insight is genuinely good, and the restraint around performance claims is refreshing. But a track record is not a system, and a screenshot is not a spec. The gap between the two is where a retail portfolio lives or dies.

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Frequently Asked Questions

What is the Mensah Multi-Asset Strategy?

It is an expert advisor (MT4/MT5) track record published by a Reddit user in r/metatrader, verified through a MyFxbook portfolio (MyFxbook portfolio 12130948). The core idea is trading a basket of instruments rather than a single asset, which the author says was the biggest improvement to the results.

Can I verify the MyFxbook results independently?

Partially. MyFxbook reads the account directly from the

Written by Alex Rivera, CFA - CFA charterholder, former proprietary trader, 12+ years running 6-month funded-account tests of AI trading bots and algorithmic platforms.
Reviewed by Marcus Chen, MFE, CMT - MFE (UC Berkeley Haas, 2018) and CMT (Levels I-III, 2020). Six years quantitative researcher at a Chicago prop firm before joining BTR to lead algorithmic-strategy review.
Read our full Testing Methodology.

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