Automated post: generated and posted by my trading pipeline's scripts. Every figure is computed from the trade log; the commentary is written by a local AI model and checked against those figures before posting.

2026-10-30 - 5 trades, +0.09% on the account

Five trades, all long, three of them in before ten. The day closed at plus 0.094 percent of the account, which on paper looks fine, but the average trade return was minus 0.264 percent and I only won two out of five. The profit factor of 1.522 is doing the heavy lifting here, propped up by one good hit.

TTWO was the trade I want to remember: plus 2.629 percent, a BB_REV25@5 setup, clean. SNDK was the one that stung: minus 4.037 percent, and it came out of the MTF_DIVT@5 structure, which across its two trades today averaged minus 2.051 percent. That setup is where the day's edge went to die.

The week is three days in at minus 0.174 percent, profit factor 0.67. Five days since I started this journal, twenty-nine trades, and the number I actually have to sit with is minus 0.826 percent on the account, profit factor 0.46, win rate 44.8 percent. The model's walkforward expectation was a 1.244 profit factor and a 62.1 percent win rate. I'm not there. One day at plus 0.094 percent doesn't change that, and I don't want it to. The sample is still small, but the direction of the cumulative number is the thing to watch, not any single green day.

The day

 

Code

Trades 5 Result +0.09% of the account Win rate 40.0% Profit factor 1.52 Avg trade -0.26% on the position Avg winner / loser +1.55% / -1.47% Best / worst trade +2.63% / -4.04% Longs 5 trades, +0.09% of the account, win 40.0% Model expected (this build) +0.13% of the account a day, +0.11% a trade its walk-forward average since 2017-07-06, after a trading cost measured from NinjaTrader's own fills (1 cent a share + 1.75 bps each way)

Today vs the model (build 20261029_120312)

Model = the build's walk-forward average day since 2017-07-06, on the live list. One day is a small sample; the running comparison below matters more.

 

Code

Model Today Difference --------------------------- ------ ------ ---------- Trades 8.8 5 -3.8 Win rate 62.1% 40.0% -22.1 pts Avg trade (on its position) +0.11% -0.26% -0.37 pts Result (on the account) +0.13% +0.09% -0.03 pts Profit factor 1.24 1.52 +0.28

Trades

Return = the trade's result on its own position.

 

Code

Time Symbol Side Setup Entry Exit Exit by Return -------- ------ ---- ---------- ------- ------- ------- ------ 09:45:09 TTWO LONG BB_REV25@5 186.77 191.68 TGT +2.63% 14:35:07 VRT LONG IBS_X@5 227.10 228.15 TGT +0.46% 09:45:09 JPM LONG MTF_DIVT@5 338.56 338.34 TGT -0.07% 10:10:08 SNOW LONG IBS_X@5 305.52 304.58 TGT -0.31% 09:45:09 SNDK LONG MTF_DIVT@5 1217.55 1168.40 STOP -4.04%

Live performance

Counted from the journal's first day, 2026-10-21, a simulated account (SimDx). Result and per day: % of the account; per trade: % on the position. SPY: bought at the close before each period and held.

 

Code

Period Days Trades Result SPY Per day Per trade Win PF ------------------------------------ ---- ------ ------ ------ ------- --------- ----- ---- Today 1 5 +0.09% -1.79% +0.094% -0.264% 40.0% 1.52 Week to date 3 10 -0.17% -0.56% -0.058% -0.390% 40.0% 0.67 Since journal start (= Month / Year) 5 29 -0.83% -1.73% -0.165% -0.473% 44.8% 0.46

Since the start: live -0.83% of the account against +1.08% the trading builds expected and -1.73% for SPY bought and held (8 sessions). The expectation for 10-21 (build 20261021_023233), 10-23 (build ), 10-27 (build ), 10-29 (build ) is estimated from the nearest build's, because that build's record was not kept.



The model - walk-forward record on the account (build 20261029_120312)

Out of sample since 2017-07-06: every half-year traded by a model trained only on what came before. Simulated, after a trading cost measured from NinjaTrader's own fills (1 cent a share + 1.75 bps each way). Shown at SPY's risk (2.53x the book): each period's profit over the book at that size - the pipeline's own measure, as its Returns view shows it; SPY bought and held. Over the full years 2018-2025 the strategy averaged +47.0% a year against SPY's +13.8%; worst drawdown -24.9% of the account against SPY's -34.2%; Sharpe 2.31 against 0.77. The pipeline sizes the book toward SPY-level risk - currently 2.53x: above it the book is cut at once, below it raised only as live results confirm the walk-forward. Positions are intraday and flat by the close, so the leverage is never held overnight.

 

Code

Year Strategy SPY Difference Strategy DD SPY DD ---- -------- ------ ---------- ----------- ------ 2021 +76.9% +27.0% +49.9% -11.8% -5.4% 2022 +36.4% -19.5% +55.9% -14.9% -25.4% 2023 +34.0% +24.3% +9.7% -4.2% -10.3% 2024 +32.2% +23.3% +8.9% -9.0% -8.4% 2025 +95.5% +16.4% +79.1% -9.8% -19.0% 2026 +73.6% +13.3% +60.3% -6.4% -9.1%

The model - last six months (walk-forward, on the account)

 

Code

Month Strategy SPY ------- -------- ----- 2026-05 +14.7% +5.3% 2026-06 +10.8% -1.3% 2026-07 +16.5% +0.1% 2026-08 -1.4% +2.7% 2026-09 +1.1% -0.6% 2026-10 +4.2% +1.3%

Automated post: generated and posted by my trading pipeline's scripts. Every figure is computed from the trade log; the commentary is written by a local AI model and checked against those figures before posting.

2026-11-02 - no trades: unknown - NinjaTrader's logs for the day were cleared before they were read

No trades this session: unknown - NinjaTrader's logs for the day were cleared before they were read.

Since the start: live -0.83% of the account against +1.21% the trading builds expected, counting 4 market days without trades at 0%.

Automated post: generated and posted by my trading pipeline's scripts. Every figure is computed from the trade log; the commentary is written by a local AI model and checked against those figures before posting.

2026-11-03 - 1 trades, +0.24% on the account

The day was simple: one trade, one symbol, a short on SNDK off the IBS_X@5 setup, entered before ten. The network flagged it, NinjaTrader executed, and it closed at +1.642% on the position, adding 0.235% to the account. No losers, no second entry, nothing to second-guess. Best and worst are the same trade because there was only one.

Week and month both sit at that single 0.235% gain, one day in each. The year-to-date picture is where the weight actually lands: six trading days, thirty trades, net -0.591%, a 46.7% win rate, and a profit factor of 0.62. The model's walkforward expectation was a 1.24 profit factor and a 62.1% win rate, so the realized numbers are running well below what the backtest suggested. Today's 1.642% trade return also exceeded the model's expected 0.103% per trade, but one data point is one data point.

The honest read: a green day on a red stretch doesn't change the trajectory. Thirty trades at a 46.7% win rate and a 0.62 profit factor is the number I keep coming back to, not the single SNDK short. One day is noise; the year is the signal, and right now it's telling me the blend is underperforming its walkforward benchmark.

The day

 

Code

Trades 1 Result +0.24% of the account Win rate 100.0% Profit factor - Avg trade +1.64% on the position Avg winner / loser +1.64% / - Best / worst trade +1.64% / +1.64% Shorts 1 trades, +0.24% of the account, win 100.0% Model expected (this build) +0.17% of the account a day, +0.10% a trade its walk-forward average since 2017-07-06, after a trading cost measured from NinjaTrader's own fills (1 cent a share + 1.75 bps each way)

Today vs the model (build 20261101_214018)

Model = the build's walk-forward average day since 2017-07-06, on the live list. One day is a small sample; the running comparison below matters more.

 

Code

Model Today Difference --------------------------- ------ ------ ---------- Trades 11.1 1 -10.1 Win rate 62.1% 100.0% +37.9 pts Avg trade (on its position) +0.10% +1.64% +1.54 pts Result (on the account) +0.17% +0.24% +0.06 pts Profit factor 1.24 - -

Trades

Return = the trade's result on its own position.

 

Code

Time Symbol Side Setup Entry Exit Exit by Return -------- ------ ----- ------- ------- ------- ------- ------ 09:44:54 SNDK SHORT IBS_X@5 1147.26 1128.42 TGT +1.64%

Live performance

Counted from the journal's first day, 2026-10-21, a simulated account (SimDx). Result and per day: % of the account; per trade: % on the position. SPY: bought at the close before each period and held.

 

Code

Period Days Trades Result SPY Per day Per trade Win PF ---------------------------- ---- ------ ------ ------ ------- --------- ------ ---- Today 1 1 +0.23% +0.30% +0.235% +1.642% 100.0% - Week to date 1 1 +0.23% -0.17% +0.235% +1.642% 100.0% - Month to date 1 1 +0.23% -0.17% +0.235% +1.642% 100.0% - Since journal start (= Year) 6 30 -0.59% -1.90% -0.099% -0.402% 46.7% 0.62

Since the start: live -0.59% of the account against +1.38% the trading builds expected and -1.90% for SPY bought and held (10 sessions). The expectation for 10-21 (build 20261021_023233), 10-23 (build ), 10-27 (build ), 10-29 (build ), 11-02 (build ) is estimated from the nearest build's, because that build's record was not kept.



The model - walk-forward record on the account (build 20261101_214018)

Out of sample since 2017-07-06: every half-year traded by a model trained only on what came before. Simulated, after a trading cost measured from NinjaTrader's own fills (1 cent a share + 1.75 bps each way). Shown at SPY's risk (3.00x the book): each period's profit over the book at that size - the pipeline's own measure, as its Returns view shows it; SPY bought and held. Over the full years 2018-2025 the strategy averaged +49.9% a year against SPY's +13.8%; worst drawdown -21.1% of the account against SPY's -34.2%; Sharpe 2.26 against 0.76. The pipeline sizes the book toward SPY-level risk - currently 3.00x: above it the book is cut at once, below it raised only as live results confirm the walk-forward. Positions are intraday and flat by the close, so the leverage is never held overnight.

 

Code

Year Strategy SPY Difference Strategy DD SPY DD ---- -------- ------ ---------- ----------- ------ 2021 +75.1% +27.0% +48.1% -15.3% -5.4% 2022 +22.2% -19.5% +41.7% -17.8% -25.4% 2023 +39.5% +24.3% +15.2% -7.9% -10.3% 2024 +46.3% +23.3% +23.0% -8.6% -8.4% 2025 +94.4% +16.4% +78.0% -8.3% -19.0% 2026 +66.1% +10.8% +55.2% -7.5% -9.1%

The model - last six months (walk-forward, on the account)

 

Code

Month Strategy SPY ------- -------- ----- 2026-05 +10.9% +5.3% 2026-06 +17.2% -1.3% 2026-07 +13.5% +0.1% 2026-08 +3.1% +2.7% 2026-09 +1.9% -0.6% 2026-10 -4.6% -0.9%

the 1% trim is the right test, most people never run it. one thing I'd watch: if the scoring and the training target were changed after looking at the walk-forward, that walk-forward isn't really out of sample anymore for those choices. do you have a slice you haven't looked at yet?

Automated post: generated and posted by my trading pipeline's scripts. Every figure is computed from the trade log; the commentary is written by a local AI model and checked against those figures before posting.

2026-11-04 - 1 trades, -0.04% on the account

November 4th was a one-trade day. The network flagged a short on MELI through the IBS_X@5 structure, entry before ten. The position closed at a 0.287% loss on the trade, costing 0.042% of the account. Zero winners, a 0.0 profit factor, one red line.

It is the only trade, so it is both the best and the worst. The setup fired, the trade went the wrong way, and the account impact was 0.042%. Not much to dissect.

Stepping back, the week and the month are the same two-day, two-trade sample: up 0.193% net, 50% win rate, 5.64 profit factor. Decent, but two days is two days.

The number that weighs on me is the year. Seven days, thirty-one trades, down 0.633% on the account, 45.2% win rate, 0.6 profit factor. The model's walkforward expectation was a 1.24 profit factor and a 62.1% win rate, and the live figures sit well below both. One losing trade today doesn't move that picture, and neither does a single winning day. The year-to-date is the honest read, and right now it says the system is running behind its own expectations. I keep writing the journal and let the sample grow.

The day

 

Code

Trades 1 Result -0.04% of the account Win rate 0.0% Profit factor 0.00 Avg trade -0.29% on the position Avg winner / loser - / -0.29% Best / worst trade -0.29% / -0.29% Shorts 1 trades, -0.04% of the account, win 0.0% Model expected (this build) +0.17% of the account a day, +0.10% a trade its walk-forward average since 2017-07-06, after a trading cost measured from NinjaTrader's own fills (1 cent a share + 1.75 bps each way)

Today vs the model (build 20261101_214018)

Model = the build's walk-forward average day since 2017-07-06, on the live list. One day is a small sample; the running comparison below matters more.

 

Code

Model Today Difference --------------------------- ------ ------ ---------- Trades 11.1 1 -10.1 Win rate 62.1% 0.0% -62.1 pts Avg trade (on its position) +0.10% -0.29% -0.39 pts Result (on the account) +0.17% -0.04% -0.21 pts Profit factor 1.24 0.00 -1.24

Trades

Return = the trade's result on its own position.

 

Code

Time Symbol Side Setup Entry Exit Exit by Return -------- ------ ----- ------- ------- ------- ------- ------ 09:52:10 MELI SHORT IBS_X@5 1744.06 1749.07 TGT -0.29%

Live performance

Counted from the journal's first day, 2026-10-21, a simulated account (SimDx). Result and per day: % of the account; per trade: % on the position. SPY: bought at the close before each period and held.

 

Code

Period Days Trades Result SPY Per day Per trade Win PF ---------------------------- ---- ------ ------ ------ ------- --------- ----- ---- Today 1 1 -0.04% +1.63% -0.042% -0.287% 0.0% 0.00 Week to date 2 2 +0.19% +1.46% +0.097% +0.677% 50.0% 5.64 Month to date 2 2 +0.19% +1.46% +0.097% +0.677% 50.0% 5.64 Since journal start (= Year) 7 31 -0.63% -0.30% -0.090% -0.399% 45.2% 0.60

Since the start: live -0.63% of the account against +1.55% the trading builds expected and -0.30% for SPY bought and held (11 sessions). The expectation for 10-21 (build 20261021_023233), 10-23 (build ), 10-27 (build ), 10-29 (build ), 11-02 (build ) is estimated from the nearest build's, because that build's record was not kept.



The model - walk-forward record on the account (build 20261101_214018)

Out of sample since 2017-07-06: every half-year traded by a model trained only on what came before. Simulated, after a trading cost measured from NinjaTrader's own fills (1 cent a share + 1.75 bps each way). Shown at SPY's risk (3.00x the book): each period's profit over the book at that size - the pipeline's own measure, as its Returns view shows it; SPY bought and held. Over the full years 2018-2025 the strategy averaged +49.9% a year against SPY's +13.8%; worst drawdown -21.1% of the account against SPY's -34.2%; Sharpe 2.26 against 0.76. The pipeline sizes the book toward SPY-level risk - currently 3.00x: above it the book is cut at once, below it raised only as live results confirm the walk-forward. Positions are intraday and flat by the close, so the leverage is never held overnight.

 

Code

Year Strategy SPY Difference Strategy DD SPY DD ---- -------- ------ ---------- ----------- ------ 2021 +75.1% +27.0% +48.1% -15.3% -5.4% 2022 +22.2% -19.5% +41.7% -17.8% -25.4% 2023 +39.5% +24.3% +15.2% -7.9% -10.3% 2024 +46.3% +23.3% +23.0% -8.6% -8.4% 2025 +94.4% +16.4% +78.0% -8.3% -19.0% 2026 +66.1% +10.8% +55.2% -7.5% -9.1%

The model - last six months (walk-forward, on the account)

 

Code

Month Strategy SPY ------- -------- ----- 2026-05 +10.9% +5.3% 2026-06 +17.2% -1.3% 2026-07 +13.5% +0.1% 2026-08 +3.1% +2.7% 2026-09 +1.9% -0.6% 2026-10 -4.6% -0.9%

Same thing happened to me. When I ran textbook AMT rules on two months of ES ticks it looked fine until I took out the single best day, then it was basically zero. Scoring on typical days with the tails cut off is the right fix, I wish I'd done that from the start. Curious whether the trend pullback family holds up on its own once the crash days are gone, that's where most of mine died.

Automated post: generated and posted by my trading pipeline's scripts. Every figure is computed from the trade log; the commentary is written by a local AI model and checked against those figures before posting.

2026-11-05 - no trades: the price feed was down for 347 minutes of the session

No trades this session: the price feed was down for 347 minutes of the session.

Since the start: live -0.63% of the account against +1.73% the trading builds expected, counting 5 market days without trades at 0%.

Automated post: generated and posted by my trading pipeline's scripts. Every figure is computed from the trade log; the commentary is written by a local AI model and checked against those figures before posting.

2026-11-06 - no trades: the price feed was down for 260 minutes of the session

No trades this session: the price feed was down for 260 minutes of the session.

Since the start: live -0.63% of the account against +1.90% the trading builds expected, counting 6 market days without trades at 0%.

Automated post: generated and posted by my trading pipeline's scripts. Every figure is computed from the trade log; the commentary is written by a local AI model and checked against those figures before posting.

2026-11-09 - no trades: the price feed was down for 313 minutes of the session

No trades this session: the price feed was down for 313 minutes of the session.

Since the start: live -0.63% of the account against +2.07% the trading builds expected, counting 7 market days without trades at 0%.

Automated post: generated and posted by my trading pipeline's scripts. Every figure is computed from the trade log; the commentary is written by a local AI model and checked against those figures before posting.

2026-11-10 - no trades: the price feed - 1 entries the model chose were skipped, mostly for stale quotes (up to 99 s old)

No trades this session: the price feed - 1 entries the model chose were skipped, mostly for stale quotes (up to 99 s old).

Since the start: live -0.63% of the account against +2.24% the trading builds expected, counting 8 market days without trades at 0%.