@soapia_27: Saw this trend and IMMEDIATELY thought of them #satosugu#gojo#jjk#anime#fyp

🇦🇲🤍Soap🖤🇦🇲
🇦🇲🤍Soap🖤🇦🇲
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Region: US
Sunday 11 October 2026 17:24:06 GMT
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unicornglitterdust__
liv 🧚🏽‍♀️💫🦄 :
“yet the world is still spinning” vs “ yet, the world is still spinning.”
2026-10-11 18:40:43
23485
housofpsychoticvacillatr
london’s saviour :
OTHER WAY
2026-10-11 19:35:40
1647
kimuzda
Kimuzda :
sky after my cat passed away
2026-10-11 18:49:46
1859
totalltko
Jay :
you better start running
2026-10-11 18:20:25
2375
ruesune
ruesune :
It started to rain like a damn anime death scene after my best friend died 💔💔 bro
2026-10-11 18:38:43
1871
trubonzaii
trubonzaii :
i love how these can be for either of them too
2026-10-11 17:28:51
13470
sugurul4ver
suguruluvr :
Bc Suguru found himself truly in his found family and Gojo was still boiled down to just a weapon 💔
2026-10-11 18:48:49
143
tesssyyluvs79
𝐓𝐞𝐬𝐬⁷⁹ :
it all depends on your point of view
2026-10-12 13:26:04
0
moliver2112
Mags🤍 :
what is your deaaaal
2026-10-12 14:36:48
0
suneater_505
Yeager bomb :
You should of switched the comments, since the comment with the pink pfp guy has “two souls in one body” in his display name for geto
2026-10-11 20:41:24
41
alienzarecoolxd
🛹𖤐ᴀʟᴇx🎸🦇#1 inuokko enjoyer :
You did not
2026-10-11 18:07:25
526
clementine_sunset_
Montserrat🫝 :
all roads lead to them
2026-10-11 18:23:21
91
ney_avxl
neyy :
I remember waking up to the prettiest sunrise coming in through the window and birds singing louder than they ever had the day after my father took his own life. It never mattered because all I could think of was getting to him, because I thought it was just a nightmare. It wasn’t.
2026-10-11 19:06:50
341
pinkdealerxo
🂱 :
OH YOU DID NOT
2026-10-12 16:46:36
0
hearteyez34
🫩 :
Oh I’m sick to my stomach 😭💔
2026-10-11 17:36:53
221
kittykatty_1928
yanii :
right after I got blocked by my bsf
2026-10-11 18:59:16
27
vampirebabygirlprincess
jaz :
PERSPECTIVESSS
2026-10-12 16:38:03
0
ace_nomore
cea :
How fast can you dodge a bullet?
2026-10-12 09:56:56
0
deelovestoedit_8
Dee🌷 :
Damm this made me sad apologize
2026-10-11 21:19:13
5
cattylinnnn
cattylinnnn :
how fast can you run.
2026-10-11 18:26:26
91
hiraeth_no.2
Hecate_theHalting :
Literally us
2026-10-11 19:12:50
49
liilvsmartin
isa :
after my dog died the day was disgustingly sunny, the day we got his ashes, literally the moment he entered to the house, it started heavily raining for like 3 minutes and then suddenly the fucking sunlight hit straight to my face, I felt mocked
2026-10-11 20:09:37
26
aroace_dragon_the7th
AROACE_SHINJI_IKARI :
Chuuya mentioned 🤤
2026-10-11 23:10:22
5
mar_bear000
Mntc :
It’s trying to make your day better
2026-10-11 20:30:15
35
_get0scum.sl_t
Geto's Cum Jar :
Geto is so mid 💔
2026-10-11 21:54:22
32
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Other Videos

A backtest by itself means almost nothing. You can make an equity curve look incredible if you optimize enough s*** on the same historical data. The real question is: does the strategy survive when you statistically try to break it? That’s what we did with ORB. We used walk-forward optimization: optimize in-sample, lock the parameters, then test them on the next unseen out-of-sample period. Then roll everything forward and repeat. And before some empiricist comes in here screaming “DATA MINING BIAS” 😂 Yes, we thought about that too. This isn’t a strategy with 47 indicators and 100 parameters that we tortured until something worked. The ORB framework is intentionally simple with relatively few degrees of freedom. More importantly, we weren’t searching for one magical parameter combination. We wanted stability across neighboring configurations and different walk-forward windows. And that’s what we found. The strategy passed across the entire OOS% / walk-forward-run grid tested rather than surviving in one lucky pocket. The majority of rolling OOS windows were profitable, and no single period generated more than half of the total profit. That helps us attack: Curve fitting → repeatedly test unseen data. Look-ahead → lock parameters before the next chronological OOS period. Data mining → limit degrees of freedom and look for broad stability instead of one perfect result. Lucky-period dependence → make sure one abnormal period isn't responsible for the strategy. Then comes the test no statistical validation can replace: Run the d*** thing live. Because none of this guarantees future profitability. We eventually deployed these systems ourselves, have successfully received prop-firm payouts with them, and have had members receive payouts as well. That’s the entire point. If you want to see the multiple ORB variations and the data behind them - visit the link in our bio! #daytrading #futures #orb #propfirmstrategy #automatedtrading
A backtest by itself means almost nothing. You can make an equity curve look incredible if you optimize enough s*** on the same historical data. The real question is: does the strategy survive when you statistically try to break it? That’s what we did with ORB. We used walk-forward optimization: optimize in-sample, lock the parameters, then test them on the next unseen out-of-sample period. Then roll everything forward and repeat. And before some empiricist comes in here screaming “DATA MINING BIAS” 😂 Yes, we thought about that too. This isn’t a strategy with 47 indicators and 100 parameters that we tortured until something worked. The ORB framework is intentionally simple with relatively few degrees of freedom. More importantly, we weren’t searching for one magical parameter combination. We wanted stability across neighboring configurations and different walk-forward windows. And that’s what we found. The strategy passed across the entire OOS% / walk-forward-run grid tested rather than surviving in one lucky pocket. The majority of rolling OOS windows were profitable, and no single period generated more than half of the total profit. That helps us attack: Curve fitting → repeatedly test unseen data. Look-ahead → lock parameters before the next chronological OOS period. Data mining → limit degrees of freedom and look for broad stability instead of one perfect result. Lucky-period dependence → make sure one abnormal period isn't responsible for the strategy. Then comes the test no statistical validation can replace: Run the d*** thing live. Because none of this guarantees future profitability. We eventually deployed these systems ourselves, have successfully received prop-firm payouts with them, and have had members receive payouts as well. That’s the entire point. If you want to see the multiple ORB variations and the data behind them - visit the link in our bio! #daytrading #futures #orb #propfirmstrategy #automatedtrading

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