Win Rate Lied This Week: The Rule-Based Bot Survived While the LLM Bots Bled
MT5 LLM auto-trading report, June 15–19, 2026.
This is Day 5 of the running log. The four-bot portfolio finished the window at -3,490 yen cumulative, even though several days showed decent-looking win rates on the surface.
The uncomfortable part is not the loss itself. It is the shape of the loss. GateGrid AI kept showing high win-rate behavior, yet one large basket loss could erase a pile of small wins. BoundSniper, the least “AI-like” bot in the group, quietly ended as the only steady positive contributor. That made me pause a bit; it is not the result I wanted from an LLM-heavy experiment, but it is the result on the screen.
The five-day total moved like this: +282 yen, -1,445 yen, -1,615 yen, -464 yen, -248 yen. Seeing a 53.3% win-rate day end at -1,445 yen still feels wrong at first glance. Then the payoff ratio explains it. The system was winning often enough, but not winning large enough.
Bot-by-bot results
Trade-level counts were not fully included in the provided block, so I treated each date’s final Bot result as one result unit. Where specific trade-level clues were given, I mention them in the analysis rather than pretending the missing rows are available.
■ GateGrid AI -1,367 yen
Record: 2 positive days / 3 negative days
Day-level win rate: 40.0%
Gross profit: +203 yen
Gross loss: -1,570 yen
Payoff ratio: 0.19
Max reported daily loss: -712 yen
■ BoundSniper +271 yen
Record: 4 positive days / 1 negative day
Day-level win rate: 80.0%
Gross profit: +303 yen
Gross loss: -32 yen
Payoff ratio: 2.37
Max reported daily loss: -32 yen
■ LLMBridgeTrader -816 yen
Record: 1 positive day / 4 negative days
Day-level win rate: 20.0%
Gross profit: +33 yen
Gross loss: -849 yen
Payoff ratio: 0.16
Max reported daily loss: -466 yen
■ MLScore GF-T4 -1,578 yen
Record: 0 positive days / 4 negative days / 1 flat day
Day-level win rate: 0.0%
Gross profit: +0 yen
Gross loss: -1,578 yen
Payoff ratio: N/A
Max reported single-trade loss: -602 yen
■ Total -3,490 yen
Record: 7 positive bot-days / 12 negative bot-days / 1 flat bot-day
Day-level win rate: 36.8% excluding flat result
Gross profit: +539 yen
Gross loss: -4,029 yen
Payoff ratio: 0.23
Max reported daily loss: -712 yen
Today’s theme: exits beat win rate
The main theme this time is not portfolio diversification. It is exit quality. A bot can filter entries, avoid bad setups, and still lose if the exit logic lets one bad position grow beyond the size of many normal wins.
GateGrid AI is the clearest example. Its design is built around not entering weak conditions: CatBoost checks the gate first, then Ollama can return defensive decisions such as AI_SKIP(sess=NY gate=0.50 base_thr=0.54 adj_thr=0.55) or OLLAMA_HOLD. That kind of log is useful because it tells me the machine is not blindly firing orders. But the five-day result says the harder problem sits after the entry: once a position or basket survives the filters, the loss needs to be cut before it becomes the whole story. Bot design notes describe GateGrid AI as a CatBoost + Ollama multi-gate system, while BoundSniper mainly relays TradingView signals to MT5 and LLMBridgeTrader asks AI to output OPEN/HOLD/CLOSE/REVERSE style position actions.
GateGrid AI
GateGrid AI ended at -1,367 yen. The raw daily path was +67, -703, -712, -155, +136 yen. The last day recovered a little, but the middle of the week had already done the damage.
The frustrating part is that the bot is not reckless by design. It is supposed to block weak entries with CatBoost and then ask Ollama to judge the environment with spread, ATR, higher-timeframe trend, session, recent win rate, and recent P/L. That is a good structure on paper. Still, the result looked like a classic small-win, large-loss pattern. The entry gate may be doing something useful, but the basket exit is probably still too forgiving. I do not have full certainty yet, but that is where my eyes go first.
A payoff ratio of 0.19 on the day-level summary is a warning sign. I know this is not the exact trade-level payoff ratio, but the shape is hard to ignore. If the average losing day is five times the average winning day, a high internal win rate becomes less comforting very quickly.
BoundSniper
BoundSniper finished at +271 yen, and it did it with the least dramatic architecture. This bot is basically an execution bridge for TradingView signals on USDJPY. It does not try to be clever about the market itself.
That simplicity helped. The daily path was +182, +3, -32, +20, +98 yen. No huge win, no heroic AI judgment, no long explanation needed. The largest negative day was only -32 yen, which almost feels boring, but boring was valuable this week.
The payoff ratio came out at 2.37 on a day-result basis. That is the only bot where the loss side did not dominate the week. I would not overpraise it from five days of data, but in this window it behaved like the adult in the room.
LLMBridgeTrader
LLMBridgeTrader ended at -816 yen. The daily line was +33, around -261, -466, -92, -30 yen. Not pretty, but the loss profile is different from GateGrid AI.
This bot matters because it asks AI to manage more than direction. It can choose OPEN, HOLD, CLOSE, REVERSE, or NONE, and it also produces confidence, setup type, SL pips, TP pips, entry reason, and exit reason. In theory, that gives it a better chance to escape bad positions by switching from holding to closing. In this five-day block, the result still landed negative, but the last two days were relatively contained at -92 and -30 yen. That does not prove the exit logic works, though it hints that the damage may be more controlled than the headline win rate suggests.
I would keep watching the CLOSE and REVERSE decisions. If this bot is going to become useful, the edge will probably come less from calling direction perfectly and more from admitting the trade is no longer worth holding.
MLScore GF-T4
MLScore GF-T4 was the heaviest drag after GateGrid AI, finishing at -1,578 yen. The reported path was 0, -487, -405, about -234, and -452 yen. There was no positive day in the period.
The entry-blocking function seems to be doing part of its job, but the trades that do get through carry too much downside. The note that June 19 had one losing trade around -602 yen is the kind of number that changes the feel of the whole bot. I saw that and thought, not again with the wide stop.
This bot may not need more intelligence first. It may need a smaller permission space. Fewer trades are not enough if the approved trades can still hit a loss size that the rest of the portfolio cannot absorb.
Summary
The week ended negative, but the useful finding is clear: the best-looking AI structure did not automatically create the best risk structure. GateGrid AI had smart filters and still lost badly. LLMBridgeTrader had richer decision language and still could not climb out. MLScore GF-T4 blocked some entries but let too much loss through when it acted.
BoundSniper, the simple rule-based execution bot, was the only one that left the week positive. I do not think that means “AI failed” in some grand way. It means the experiment has moved from entry quality to exit discipline. The next improvement should probably be less about asking the model to be smarter, and more about making it harder for any one trade or basket to become the whole week.
