@lethicamhuong.1510: Trại em hôm nay có cung cấp sỉ lẻ đầu ốc bươu vàng, mọi người ủng hộ liên hệ em nhe!!!

Cao Phương
Cao Phương
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Region: VN
Sunday 14 September 2025 09:22:01 GMT
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yk.z.l
Định :
xin giá
2025-10-19 02:59:49
0
minhanh363636
🍒 mẹ bé MINH ANH 🍒 :
đầu óc bán giá sao a
2025-09-27 06:44:28
1
nganep98
Tré trộn Ngăn Ép :
Có hàng ko a
2026-09-03 18:06:18
1
3ngonbd
Thực phẩm 3 NGON Bến Cát :
này sỉ bao nhiêu 1kg bạn
2026-07-24 06:33:53
1
anhlong250593
Anhlong :
gia sao
2026-01-22 13:46:44
0
trinh.n.ngoc
Trinh Ẫn Ngoc :
có giao đơn k bạn ơi
2025-11-28 09:02:16
0
user4163304606637
nt :
E xin giá đâu ốc e ở tphcm
2025-11-29 01:35:59
0
nguyenvuong7534
V :
bán hả kinh doanh jư bn
2025-09-14 09:26:32
1
3ngonbd
Thực phẩm 3 NGON Bến Cát :
ốc này bao nhiêu kg bạn. mua sll
2026-07-23 08:27:50
0
trinh.n.ngoc
Trinh Ẫn Ngoc :
giá nhiu bạn oi
2025-11-28 09:02:31
0
be.long.min.ty
Be Long Miền Tây :
có bán ốc bươu vàng nguyên con k anh
2026-04-02 07:38:34
1
soai_ca99
Nhật Anh👑 :
Ship nước ngoài k bạn
2026-01-15 15:23:41
0
To see more videos from user @lethicamhuong.1510, please go to the Tikwm homepage.

Other Videos

➡️ Quantitative Finance From Scratch, Part 20: Backtesting. A backtest tests a trading strategy on historical data, as if you had used it back then, to see whether it would have made money and how much risk it took along the way. Portfolio managers, analysts and quant researchers run backtests before real money goes into an idea. The key idea: split the past in two. You build the rule on the first part (in sample) and then test it on later data it has never seen (out of sample). The out of sample result is the fairer check. Why it matters: if you search the past hard enough, you will find patterns, even in pure noise. Trying rule after rule until one looks good is called data mining, and many of those patterns are just statistical chance. In this video we test 498 simple rules (hold after the price rose or fell over 2 to 250 days) on 10 simulated years of a market with no edge at all. The best rule in the first five years makes +11% in sample. On the next five years, data it has never seen, the same rule loses 28% and drops to rank 460 of 498. The ten best rules in sample lose 18.5% on average out of sample. Even a properly backtested result only describes the past. Markets change, and a pattern that worked for years can stop working. Classic mistakes: look-ahead bias (using information you could not have known at that time), survivorship bias (testing only companies that still exist today) and leaving out trading costs. All numbers come from one simulated run with assumed numbers (seed 20, daily returns with zero average and a 1% daily swing). No real market data, no strategy recommendation. Education only, not financial advice. #quantitativefinance #quant #backtesting #finance #trading
➡️ Quantitative Finance From Scratch, Part 20: Backtesting. A backtest tests a trading strategy on historical data, as if you had used it back then, to see whether it would have made money and how much risk it took along the way. Portfolio managers, analysts and quant researchers run backtests before real money goes into an idea. The key idea: split the past in two. You build the rule on the first part (in sample) and then test it on later data it has never seen (out of sample). The out of sample result is the fairer check. Why it matters: if you search the past hard enough, you will find patterns, even in pure noise. Trying rule after rule until one looks good is called data mining, and many of those patterns are just statistical chance. In this video we test 498 simple rules (hold after the price rose or fell over 2 to 250 days) on 10 simulated years of a market with no edge at all. The best rule in the first five years makes +11% in sample. On the next five years, data it has never seen, the same rule loses 28% and drops to rank 460 of 498. The ten best rules in sample lose 18.5% on average out of sample. Even a properly backtested result only describes the past. Markets change, and a pattern that worked for years can stop working. Classic mistakes: look-ahead bias (using information you could not have known at that time), survivorship bias (testing only companies that still exist today) and leaving out trading costs. All numbers come from one simulated run with assumed numbers (seed 20, daily returns with zero average and a 1% daily swing). No real market data, no strategy recommendation. Education only, not financial advice. #quantitativefinance #quant #backtesting #finance #trading

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