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@diyamente:

Mia💎
Mia💎
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Region: FR
Monday 24 August 2026 16:14:20 GMT
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.mahmod.bohade
كل شي ابجويMahmod Bohade :
جميله حبي
2026-08-24 17:46:06
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eagle.3330
Almurisi Reserv :
🌹🌹
2026-08-24 16:40:01
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spartedz
sparte :
🥵🥵🥵🥵🥵🥵
2026-08-24 16:19:38
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qaidsales
Qaidsales :
😭😭😭
2026-08-24 16:24:53
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user96315127634761
salem :
😘😘😘
2026-08-24 16:19:18
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sadakha26
بيننا حكاية :
✌️✌️✌️
2026-08-24 16:24:59
0
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Other Videos

#unterhaltung #meme #humor
#unterhaltung #meme #humor
#capcut #Meme #MemeCut
#capcut #Meme #MemeCut
Phần 117: SUPER SAIYAN #GOKU hình nền #4klivewallpaper động đẹp #dragonball dành cho bạn #dragonballz. The universe bend to my will !!!
Phần 117: SUPER SAIYAN #GOKU hình nền #4klivewallpaper động đẹp #dragonball dành cho bạn #dragonballz. The universe bend to my will !!!
#padahariini
#padahariini
Estimating Prop Firm Challenge Pass Probability and Expected Value via Reshuffling Monte Carlo This 90-second video explains how to estimate the probability of passing a proprietary trading firm challenge and the net expected value of a funded-account attempt, without placing a live trade or purchasing a challenge. The analysis begins with an out-of-sample backtest or historical trade log. Trades are sampled with replacement to generate a large number of possible equity paths. Tens or hundreds of thousands of reshuffling Monte Carlo simulations are then evaluated under the firm’s specific rules, including trailing drawdown limits and consistency requirements. Each simulated path is assigned a balance that incorporates the sunk challenge fee. When a path passes the challenge, the funded stage is simulated, including payout thresholds and any resulting payouts. These amounts are added to the path’s total balance. The estimated pass probability is the proportion of simulated challenge paths that pass. Net expected value is the average final balance across all simulations. The simulations and rule sets are implemented in QuantPad. #quantpad #propfirm #quant #montecarlo
Estimating Prop Firm Challenge Pass Probability and Expected Value via Reshuffling Monte Carlo This 90-second video explains how to estimate the probability of passing a proprietary trading firm challenge and the net expected value of a funded-account attempt, without placing a live trade or purchasing a challenge. The analysis begins with an out-of-sample backtest or historical trade log. Trades are sampled with replacement to generate a large number of possible equity paths. Tens or hundreds of thousands of reshuffling Monte Carlo simulations are then evaluated under the firm’s specific rules, including trailing drawdown limits and consistency requirements. Each simulated path is assigned a balance that incorporates the sunk challenge fee. When a path passes the challenge, the funded stage is simulated, including payout thresholds and any resulting payouts. These amounts are added to the path’s total balance. The estimated pass probability is the proportion of simulated challenge paths that pass. Net expected value is the average final balance across all simulations. The simulations and rule sets are implemented in QuantPad. #quantpad #propfirm #quant #montecarlo


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