Conclusion

The combined closed result was +528 yen, so the day ended positive. Still, the clean number hides the part I kept staring at: the largest single loss was -414 yen on BoundSniper. A day can finish green and still leave a clear warning mark.

LLMBridgeTrader was the strongest performer, with six closed winners and no losing trade. GateGrid AI also ended positive, but its payoff ratio was only 0.31, which tells a different story from the surface result. MLScore GF-T4 GB slipped into a realized loss and still had one open GBPJPY short carrying a floating loss at the report cut-off. The theme today was not “how many trades won.” It was whether each bot knew when to stop holding.

Bot-by-Bot Results

■ GateGrid AI +307 yenRecord: 13W / 3L / 1 flatWin rate: 81.3%Gross profit: +1,210 yenGross loss: -903 yenPayoff ratio: 0.31Max loss: -364 yen

■ LLMBridgeTrader +710 yenRecord: 6W / 0LWin rate: 100.0%Gross profit: +710 yenGross loss: 0 yenPayoff ratio: N/AMax loss: 0 yen

■ MLScore GF-T4 GB -303 yenRecord: 1W / 2LWin rate: 33.3%Gross profit: +200 yenGross loss: -503 yenPayoff ratio: 0.80Max loss: -252 yenOpen position: -94 yen floating loss

■ BoundSniper -186 yenRecord: 3W / 1LWin rate: 75.0%Gross profit: +228 yenGross loss: -414 yenPayoff ratio: 0.18Max loss: -414 yen

■ Total +528 yenRecord: 23W / 6L / 1 flatWin rate: 79.3%Gross profit: +2,348 yenGross loss: -1,820 yenPayoff ratio: 0.34Max loss: -414 yenOpen position: -94 yen floating loss

Today’s Theme: The Exit Was Louder Than the Entry

Today was one of those sessions where the final P/L looks fine, but the structure feels uneven. The total closed result was positive, yet the payoff ratio for the whole group was only 0.34. That means the average winning trade was much smaller than the average losing trade. I do not want to overreact to one day, but that number is low enough to make me slow down.

The LLM-based bots are not only entry machines in this experiment. Especially for LLMBridgeTrader and GateGrid AI, I am watching whether the model or the surrounding logic can decide when to stop holding, when to close, and when to reverse. Today, the entry side was not the main concern. The exit layer was where the personality of each bot showed up.

GateGrid AI

GateGrid AI finished at +307 yen, which is a decent outcome on paper. But the path was not as comfortable as the headline result. The bot had 13 winning exits, 3 losing exits, and 1 flat exit, yet the payoff ratio stayed at 0.31. That usually means the system is collecting small pieces and occasionally giving back a large chunk. The -364 yen loss made me pause, because this pattern can look stable right until it is not.

There was also a useful detail inside the loss structure. The large losing legs were partly offset by companion winners in the same grid cycle. For example, a -360 yen leg was softened by +203 yen and +155 yen exits, and later a -364 yen leg was offset by +214 yen and +158 yen. So the grid did not break; it absorbed. Still, absorption is not the same as control. The next improvement probably sits around how quickly the weak leg is cut, or whether the cluster should be closed earlier when one side starts dragging the whole basket.

For a CatBoost plus Ollama design, this is exactly the kind of day worth logging. The model did enough to stay positive, but the exit rules were forced to carry the risk. I would not call it a bad day. I would call it a warning wrapped in a profit.

LLMBridgeTrader

LLMBridgeTrader was the cleanest bot today: +710 yen, six closed winners, no losing trade. The interesting part is that several exits were tagged as stop-related closes, but they ended in profit. That suggests the exit layer was not just cutting damage; it was locking in movement after the position had gone the right way.

Because this bot gives the LLM a wider role, I care less about a single BUY or SELL call and more about the full plan: OPEN, HOLD, CLOSE, REVERSE, confidence, setup type, SL, TP, and the stated reason. Today, the realized result says the plan worked. I am still careful with that conclusion because there was no losing trade in the sample. A bot that never had to take a hit has not shown how it behaves under stress.

Still, among the four bots, this one gave the least messy result. It did not need a huge move, and it did not need rescue trades. It simply kept taking profit. That is rare enough that I do not want to dress it up too much.

MLScore GF-T4 GB

MLScore GF-T4 GB ended with -303 yen realized, plus an open GBPJPY short carrying -94 yen of floating loss. This bot had one +200 yen winner and two losses around -250 yen each. The payoff ratio was 0.80, which is not terrible by itself, but with a 1W / 2L record it was not enough.

The shape is simple and a bit frustrating. The winner was smaller than the combined damage, and the open position was not helping at the cut-off. The losses at -251 yen and -252 yen were almost identical, so this looks more like a fixed-risk structure than a chaotic failure. That can be improved, but only if the entry filter or exit timing earns enough winners to justify the stop size.

My guess is that the issue is not only signal quality. The exit width may be too neat for the market it is facing. I am not fully sure yet, but the open short at the end made the day feel unfinished.

BoundSniper

BoundSniper is the most useful warning today. It closed three winners and one loser, yet still ended at -186 yen. The reason is blunt: the losing trade was -414 yen, while the three winners added only +228 yen together. When I saw that -414 yen cut, the first reaction was not dramatic; it was more like, “again, this shape.”

This bot is not trying to predict the market by itself. It carries TradingView signals into MT5, so the key question is whether the execution and exit handling preserve the edge of the original strategy. Today, they did not. The winning trades were too small to pay for the one large loss.

BoundSniper does not need a philosophical rewrite from this one day. It needs a sharper answer to one practical question: when a USDJPY move goes wrong, how long should the position be allowed to stay wrong? Until that is cleaner, even a good-looking sequence of trades can remain fragile.

Summary

The day ended positive, but the important lesson came from the red side of the ledger. LLMBridgeTrader was clean, GateGrid AI survived through basket behavior, MLScore needs a better balance between stop size and signal quality, and BoundSniper showed how one exit can outweigh several correct calls.

I am keeping the focus on maximum loss and payoff ratio for the next run. Profit is nice, but the bot that teaches the most is often the one that makes the account feel slightly uncomfortable.

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