AI FX Bot Lab: Real Trading Experiments

A ¥728 Exit Turned the Whole Bot Run Negative


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Conclusion

The day ended at -1,180 yen across four MT5 bots, and the uncomfortable part is that the record did not look broken at first glance. There were 9 winning exits and 7 losing exits overall, so the surface was not ugly. But the payoff ratio was only 0.26, and the largest single loss was -728 yen from GateGrid AI. I paused on that number for a moment, because it was bigger than the total gross profit of every bot combined.

The main theme today is exit quality. For the bots that hand judgment to an LLM or an AI layer, the question is no longer just “was the entry right?” It is whether the model knows when the original idea has expired. Today, that part still feels unfinished.

Bot-by-bot results

■ GateGrid AI -512 yen

Record: 5W / 2L

Win rate: 71.4%

Gross profit: +235 yen

Gross loss: -747 yen

Payoff ratio: 0.13

Max loss: -728 yen

■ BoundSniper -25 yen

Record: 2W / 1L

Win rate: 66.7%

Gross profit: +52 yen

Gross loss: -77 yen

Payoff ratio: 0.34

Max loss: -77 yen

■ LLMBridgeTrader -175 yen

Record: 1W / 3L

Win rate: 25.0%

Gross profit: +162 yen

Gross loss: -337 yen

Payoff ratio: 1.44

Max loss: -201 yen

■ MLScore GF-T4 GB -468 yen

Record: 1W / 1L

Win rate: 50.0%

Gross profit: +144 yen

Gross loss: -612 yen

Payoff ratio: 0.24

Max loss: -612 yen

■ Total -1,180 yen

Record: 9W / 7L

Win rate: 56.3%

Gross profit: +593 yen

Gross loss: -1,773 yen

Payoff ratio: 0.26

Max loss: -728 yen

Today’s theme

The strange thing about this run is that the losing day was not caused by constant bad entries. GateGrid AI won most of its exits. BoundSniper also had more winning closes than losing ones. Even MLScore was split one and one. And still, the day sank because the losing trades were far larger than the winning trades.

That makes this less of a signal problem and more of an exit problem. The bots can find small profitable windows, but when price moves against them, the stop behavior and close timing are still too heavy. A 71.4% record with a 0.13 payoff ratio is not strength; it is a warning label written in small numbers.

GateGrid AI

GateGrid AI was the most painful bot to read today. It finished with 5 wins and 2 losses, which sounds fine until the -728 yen loss appears at the end. The five wins added only +235 yen, so one late loss erased all of them and then some. Seeing -728 yen after a string of small wins had that familiar “not this shape again” feeling.

The entry filter may still be doing something useful. GateGrid AI did not spray random losing trades all day. The problem is that the grid logic and exit logic allowed one position to become too large relative to the normal win size. If the bot is designed to collect small moves, then a single loss cannot be allowed to equal fifteen small wins. That is where the current structure looks fragile.

For an ML plus LLM hybrid bot, the next review should focus on the moment it stops believing in the setup. CatBoost and Ollama may help filter entries, but once a position is live, the bot also needs a stronger “the idea is no longer valid” trigger. I suspect the issue is not the first decision. It is the delay in giving up.

BoundSniper

BoundSniper ended at -25 yen, and this one is a different kind of result. The trade logic itself is not AI-driven; it passes TradingView signals into MT5. So I do not read this as a model judgment failure. It is more about execution, signal timing, and the cost carried by the position.

The first close showed +28 yen on price movement, but after swap it became a net drag. That is small, but it matters because the other wins were only +10 yen and +42 yen. A tiny edge disappears quickly when the holding cost is not small relative to the expected win.

BoundSniper did not collapse today. Still, its payoff ratio was only 0.34 on a net basis. That means it needs either cleaner exits or larger average wins, because a bot that depends on TradingView rules cannot count on AI interpretation to rescue weak trade economics later.

LLMBridgeTrader

LLMBridgeTrader is the most interesting bot today, even though the result was negative. It only won once and lost three times, but its payoff ratio was 1.44. That means the structure is not hopeless. One winning exit was large enough to cover more than one average loss, at least in theory.

The issue is frequency and sequence. After the +162 yen win, the bot took -57 yen, then -201 yen, then -79 yen. The model is allowed to decide OPEN, HOLD, CLOSE, and REVERSE, so the exit decision is part of the experiment, not just a mechanical afterthought. Today, the AI did close trades, but it did not avoid the cluster of small-to-medium losses that followed.

This is where LLM trading gets uncomfortable. The model can describe a reason, and the log can preserve that reason, but the account only cares whether the reason led to a better exit. I would not throw away this setup from one day. I would look harder at confidence thresholds for CLOSE and REVERSE, because the bot may need to be more conservative once it has already taken a directional loss.

MLScore GF-T4 GB

MLScore GF-T4 GB had only two closed results, so I do not want to overstate the sample. Still, the shape was clear: one net win of +144 yen after swap, then one loss of -612 yen. That gave it a 50.0% record but a payoff ratio of only 0.24. Half right is not enough when the wrong side is four times heavier.

The -612 yen loss is the second biggest single loss of the day. It did not come from a long sequence of mistakes; it came from one trade that carried too much damage. That makes the review simple, though not easy. The bot needs a better hard stop, or it needs to size down when the expected stop distance is wide.

This bot may still be useful as a scoring layer, but today it behaved like a model that can be directionally right sometimes while still failing the risk shape. I do not have enough from one day to say the score is bad. The exit width is the part I would question first.

Summary

Today was not a clean “AI failed” day. It was more specific than that. The bots found winners, and some of the entry logic looked alive, but the loss distribution was badly tilted. Total gross profit was +593 yen against -1,773 yen in gross losses, and that gap tells the story more honestly than the win count.

For the next tuning pass, I would not start by chasing more entries. I would start with maximum loss rules, earlier invalidation, and stricter handling of HOLD turning into CLOSE. The experiment is still worth running, but today the market reminded me that a smart entry is only half a trade



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AI FX Bot Lab: Real Trading ExperimentsBy Kimi | Japan FX Bot Lab