@hisytstory: I Got Taller 💀 . #3danimation #animationart #digitalart #hisytstory #creativecontent animationtrends creatorsearchinsig hts

His Story
His Story
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Thursday 08 October 2026 11:27:00 GMT
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zush177
Zush :
Js about to say first but then 66 comments appeared daug
2026-10-08 11:32:24
163
skblizoki
yukii :
why am I feeling dizzy tf
2026-10-08 12:04:14
940
zeckfelmss
Zeck Felms :
im back on tiktok baby
2026-10-08 11:30:10
678
yabab0oe
￴ ￴ ￴ ￴ ￴￴ ￴ ￴ ￴￴ :
I'd be so fucking dizzy in 3 seconds😭
2026-10-08 12:50:34
87
4ng3l.w1ngs0
4ng3l w1ngs :
the coach is the "GIMMIE GIMMIE GIMMIE" guy😭
2026-10-08 12:26:07
124
b0782160
👻-ryker-🎃 :
Here before 1mil
2026-10-08 11:31:54
29
mikoy0613
mikoy :
i believe I can flyyyyy BWHHAHAHAHAHH
2026-10-08 13:25:38
3
vulex_0
Vulex_0 :
His story please follow me im a big fan
2026-10-08 14:57:06
1
lorycasteddu
💎 𝟏𝟓 💎 :
helicopter
2026-10-08 13:25:01
5
thegaminggodsidk
TheGamingGods :
earlyy
2026-10-08 13:07:52
2
nothimbtwlol
Lee :
Early asf
2026-10-08 11:28:38
26
mattx4448
ACCOUNT FOUND :
coach baldwin nasa his story
2026-10-08 12:35:41
0
mobil42
§•Mobil•§ :
holy early
2026-10-08 11:31:23
1
itsme_sham5
◦•●◉✿𝙞𝙩𝙨𝙢𝙚_𝙨𝙝𝙖𝙢✿◉●•◦ :
early
2026-10-08 11:33:05
1
ag1234g0
AG :
earlyyy
2026-10-08 11:29:46
1
lce.clod
Ice clod :
Holy early
2026-10-08 11:45:58
1
__aki_trajkovic__
☦️ :
earlyy
2026-10-08 11:37:59
1
nahldwin75
War man/swat team :
early
2026-10-08 11:32:03
1
pragmatic0007
✝️🇺🇸Pragmatic07🇵🇭✝️ :
what dat? I'm just a bebeh
2026-10-08 11:53:58
2
l_0.172
Liam _0172 :
2026-10-08 11:34:07
1
rigenmucha
Rigenmucha :
Early
2026-10-08 11:30:31
1
johnerrol89
Errol :
early
2026-10-08 11:31:28
1
scarforfree
oh shi theres a ghost😱 :
early
2026-10-08 11:33:54
1
kinglucianpogi
LUCIAN :
early
2026-10-08 11:32:10
1
yummymccookie
Minecraft Cookie • Following :
Bro im literally a
2026-10-08 14:27:57
1
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➡️ Quantitative Finance from Scratch, part 17: the Monte Carlo simulation. The future is uncertain, so a Monte Carlo simulation makes many random assumptions about it. Every run draws another scenario, every scenario becomes a path, and from all the paths you read off what matters: the typical outcome, a good case, a bad case and the chance of a loss. Our example is simulated with assumed numbers: $10,000 over 30 years, an average return of 8% a year and swings of 20% a year, each year's growth drawn from a bell curve. 10,000 runs give 10,000 possible futures: Typical (the median): $60,814 Bad case: 1 in 10 ends below $14,636 Good case: 1 in 10 ends above $246,456 Chance of a loss after 30 years: 5% (500 of 10,000 paths) Average: $111,469, above the median because a few lucky paths pull it up (volatility drag, part 9) More runs give more precise numbers, with the square root rule from part 3: 100 times the runs, 10 times the precision. Where it is used: the Basel market risk rules let supervisors permit bank risk models based on Monte Carlo simulation. It is also used to value complex options and for retirement modeling. Sources: N. Metropolis and S. Ulam,
➡️ Quantitative Finance from Scratch, part 17: the Monte Carlo simulation. The future is uncertain, so a Monte Carlo simulation makes many random assumptions about it. Every run draws another scenario, every scenario becomes a path, and from all the paths you read off what matters: the typical outcome, a good case, a bad case and the chance of a loss. Our example is simulated with assumed numbers: $10,000 over 30 years, an average return of 8% a year and swings of 20% a year, each year's growth drawn from a bell curve. 10,000 runs give 10,000 possible futures: Typical (the median): $60,814 Bad case: 1 in 10 ends below $14,636 Good case: 1 in 10 ends above $246,456 Chance of a loss after 30 years: 5% (500 of 10,000 paths) Average: $111,469, above the median because a few lucky paths pull it up (volatility drag, part 9) More runs give more precise numbers, with the square root rule from part 3: 100 times the runs, 10 times the precision. Where it is used: the Basel market risk rules let supervisors permit bank risk models based on Monte Carlo simulation. It is also used to value complex options and for retirement modeling. Sources: N. Metropolis and S. Ulam, "The Monte Carlo Method", Journal of the American Statistical Association 44(247), pages 335 to 341 (1949). N. Metropolis, "The Beginning of the Monte Carlo Method", Los Alamos Science, Special Issue 1987, pages 125 to 130. This video is for education only, and nothing in it is financial advice. #quantfinance #montecarlo #simulation #finance #python

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