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@shyacaa: LOVE THIS SKINTINT FOR DAILYY <3

Nashya
Nashya
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Region: ID
Monday 06 July 2026 11:40:11 GMT
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rabiatul_adwiyh28
rayyah🧸ྀི :
cantikkkk
2026-07-07 13:04:59
3
joyhuba
￴￴￴joy :
brushnya pake apa kak
2026-07-09 15:53:37
1
devieraalf_
D :
KAKAK NASH HALLOOOOOO
2026-07-06 11:53:34
0
ddorddora
Sybill :
Masyallah kak cantik sekali🥰 Ka nash kalau abis makeup biasanya Ka nash bersihin makeup sehari hari nya pke apa kak🙏🏻
2026-07-06 17:46:20
0
nsacc._
النساء :
oksidasii gak kak nash?
2026-07-06 11:45:35
0
bbyblue9922
Bbyblue- :
🥰🥰🥰
2026-07-06 11:43:47
0
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Other Videos

## ভুল করে সত্যি কথা পোস্ট করার যে বেপার টা 🤣🤣🤣🙏
## ভুল করে সত্যি কথা পোস্ট করার যে বেপার টা 🤣🤣🤣🙏
Plagiarists are collecting praise across LinkedIn, TikTok, Instagram, and YouTube for a method I built and published in October 2025. They've copied my words, numbers, plots, and even my video thumbnails, and passed them off as their own. The method: model a prop firm account as a structured product and price it with Monte Carlo simulation. You program a specific firm's exact rules into the engine, feed it a real trade log from a strategy, and simulate the challenge phase and the funded phase as two separate problems, because they have different objectives. The challenge is a barrier problem, so you solve for probability of passing. The funded phase is a payout problem, so you solve for money withdrawn across resets and profit splits. The engine returns a full statistical profile for one strategy on one firm: probability of passing, probability of reaching a payout, the distribution of time to payout, expected payout per funded account, and net expected value after challenge fees, failed challenge fees, activation fees, resets, and splits. Because the output is specific to both the strategy and the firm, it answers two questions at once: which risk geometry performs best in the convex environment of a given firm, and which firm gives your strategy the highest net expected value. The core result: you can have positive net expected value on these programs without a positive expected value strategy, because the payoff is convex. Capped, sunk-cost downside (challenge and reset fees) and otherwise unrealized losses, with realized upside (winnings realized in the form of a payout). Nobody on social media had discussed the mathematics of this before I did the research and published it. I built the engine and shipped it into QuantPad on 28 October 2025. I have the commit history. I published the method on TikTok the same day in a video that got over 300k views, and explained further in a long-form YouTube video on 7 March 2026, now past 130k views. Nobody had published anything like this on social media before that. What came after: reposts across LinkedIn, TikTok, Instagram, and YouTube that reused my graphics, lifted my phrasing close to verbatim, and in one case took my exact thumbnail, swapped the title into German, and added the reposter's own face to the middle of it. Others have built websites that attempt to copy the methodology (but miss key details) and sell access to it. People are being praised in the comments for work that is **line for line** mine. #quant #quanttrading #quantfinance
Plagiarists are collecting praise across LinkedIn, TikTok, Instagram, and YouTube for a method I built and published in October 2025. They've copied my words, numbers, plots, and even my video thumbnails, and passed them off as their own. The method: model a prop firm account as a structured product and price it with Monte Carlo simulation. You program a specific firm's exact rules into the engine, feed it a real trade log from a strategy, and simulate the challenge phase and the funded phase as two separate problems, because they have different objectives. The challenge is a barrier problem, so you solve for probability of passing. The funded phase is a payout problem, so you solve for money withdrawn across resets and profit splits. The engine returns a full statistical profile for one strategy on one firm: probability of passing, probability of reaching a payout, the distribution of time to payout, expected payout per funded account, and net expected value after challenge fees, failed challenge fees, activation fees, resets, and splits. Because the output is specific to both the strategy and the firm, it answers two questions at once: which risk geometry performs best in the convex environment of a given firm, and which firm gives your strategy the highest net expected value. The core result: you can have positive net expected value on these programs without a positive expected value strategy, because the payoff is convex. Capped, sunk-cost downside (challenge and reset fees) and otherwise unrealized losses, with realized upside (winnings realized in the form of a payout). Nobody on social media had discussed the mathematics of this before I did the research and published it. I built the engine and shipped it into QuantPad on 28 October 2025. I have the commit history. I published the method on TikTok the same day in a video that got over 300k views, and explained further in a long-form YouTube video on 7 March 2026, now past 130k views. Nobody had published anything like this on social media before that. What came after: reposts across LinkedIn, TikTok, Instagram, and YouTube that reused my graphics, lifted my phrasing close to verbatim, and in one case took my exact thumbnail, swapped the title into German, and added the reposter's own face to the middle of it. Others have built websites that attempt to copy the methodology (but miss key details) and sell access to it. People are being praised in the comments for work that is **line for line** mine. #quant #quanttrading #quantfinance
#223🇲🇱❤️❤️ #creatorsearchinsights #🇸🇳🇲🇷🇬🇳🇬🇲
#223🇲🇱❤️❤️ #creatorsearchinsights #🇸🇳🇲🇷🇬🇳🇬🇲
pal pal jeena mahal🎧😩💔full song repost @𝙃𝙚𝙚𝙧 𝙈𝙪𝙨𝙞𝙘🎧🔥 #foryou #music #foryoupage❤️ #trendingvideo_viral1m #unfreez myaccount music12
pal pal jeena mahal🎧😩💔full song repost @𝙃𝙚𝙚𝙧 𝙈𝙪𝙨𝙞𝙘🎧🔥 #foryou #music #foryoupage❤️ #trendingvideo_viral1m #unfreez myaccount music12
Wes tak ngapurani | Salahmu wingi (aku sing polah) |(Aku ngaku salah) @happyasmara FT @z10.sandi - RAISO NGAPUSI 2 #happyasmara #ziosandi #raisongapusi2
Wes tak ngapurani | Salahmu wingi (aku sing polah) |(Aku ngaku salah) @happyasmara FT @z10.sandi - RAISO NGAPUSI 2 #happyasmara #ziosandi #raisongapusi2
Thank me later #gld #tennischain #tiktokshopsummersale #TikTokShopBackToSchool #tiktokshopcreatorpicks
Thank me later #gld #tennischain #tiktokshopsummersale #TikTokShopBackToSchool #tiktokshopcreatorpicks

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