@thudongxu.daily: Áo khoác lông cừu TOKYOLIFE #thudongxudaily #aokhoaclong #tokyolife

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Wednesday 21 October 2026 09:03:23 GMT

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My favorite season to create looks is RIGHT around the corner 🤭🤭🤭🤭🤭🤭

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元プロパーティにロケランぶっ飛ばしてきたwww#荒野行動

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#capcut #capcutpioneer #capcut102 #aifilter #fyp LIMITED-TIME DISCOUNT FOR CAPCUT PRO UP TO 90% OFF. HOW IS THIS KIND OF EFFECT MADE? YOU ONLY NEED TO UPLOAD ONE PHOTO TO GET THE SAME RESULT. THE WHOLE PROCESS IS VERY SIMPLE. NOW I WILL GUIDE YOU STEP BY STEP. FIRST, CLICK ON THE “TEMPLATE” IN THE BOTTOM LEFT CORNER. IF YOU CAN’T FIND IT, CLICK ON MY AVATAR. FIND THIS VIDEO AND TAP TO ENTER IT. LOCATE THIS TEMPLATE. CLICK ON “USE TEMPLATE”. THEN CLICK AGAIN AND SELECT THE PHOTO YOU LIKE. WAIT A FEW SECONDS — THE IMAGE WILL BE GENERATED AUTOMATICALLY. FINALLY, CLICK “EXPORT” AND EVERYTHING WILL BE DONE. COMMENT CRÉER CE TYPE D’EFFET ? IL VOUS SUFFIT DE TÉLÉCHARGER UNE SEULE PHOTO POUR OBTENIR LE MÊME RÉSULTAT. LE PROCESSUS EST TRÈS SIMPLE. JE VAIS MAINTENANT VOUS GUIDER ÉTAPE PAR ÉTAPE. TOUT D’ABORD, CLIQUEZ SUR « TEMPLATE » EN BAS À GAUCHE. SI VOUS NE LE TROUVEZ PAS, CLIQUEZ SUR MON AVATAR. RECHERCHEZ CETTE VIDÉO ET APPUYEZ POUR Y ENTRER. TROUVEZ CE MODÈLE (TEMPLATE). CLIQUEZ SUR « USE TEMPLATE ». PUIS CLIQUEZ À NOUVEAU ET SÉLECTIONNEZ LA PHOTO QUE VOUS AIMEZ. ATTENDEZ QUELQUES SECONDES — L’IMAGE SERA GÉNÉRÉE AUTOMATIQUEMENT. ENFIN, CLIQUEZ SUR « EXPORT » ET TOUT SERA TERMINÉ.

Walk-forward backtest optimization tested on 16 years of E-mini S&P 500 futures data. We optimized three strategies on a rolling 2-year window, then traded the chosen settings blind on the next 6 months, and rolled that forward 28 times each. Donchian breakout, moving average crossover and Connors RSI2. 138 parameter combinations, re-selected at every step. In training the selected settings made $1,458,122. Out of sample the same settings lost $604,740. That is a pooled out-of-sample to in-sample ratio of -0.41, in all three strategy families. The edge did not shrink, it inverted. The part we did not expect: for every fold we also scored a parameter set picked at random from the same grid. Across 84 paired tests the optimized choice lost to the random one by about $5,067 a fold (paired t-test p = 0.027), and lost to the grid median by $5,486 (p = 0.0003). Optimizing did worse than not bothering. Costs were measured, not assumed. 73,737,856 real top-of-book quotes across 16 days spread over 2010 to 2025 give a 0.2606 point average spread and a $13.03 round turn. At double that cost the ratio is -0.44. 7 of 15 years were positive, so this is not one bad year, and buy and hold made $310,148 over the same windows and beat all of it. Validation label: walk-forward out of sample, no evidence of exploitable edge. The 5.6 million minute bars and the 73.7 million quotes behind this are included with QuantPad. No vendor account, no CSV hunting. #QuantPad #backtesting #algotrading #quanttrading #futurestrading

Walk-forward backtest optimization tested on 16 years of E-mini S&P 500 futures data. We optimized three strategies on a rolling 2-year window, then traded the chosen settings blind on the next 6 months, and rolled that forward 28 times each. Donchian breakout, moving average crossover and Connors RSI2. 138 parameter combinations, re-selected at every step. In training the selected settings made $1,458,122. Out of sample the same settings lost $604,740. That is a pooled out-of-sample to in-sample ratio of -0.41, in all three strategy families. The edge did not shrink, it inverted. The part we did not expect: for every fold we also scored a parameter set picked at random from the same grid. Across 84 paired tests the optimized choice lost to the random one by about $5,067 a fold (paired t-test p = 0.027), and lost to the grid median by $5,486 (p = 0.0003). Optimizing did worse than not bothering. Costs were measured, not assumed. 73,737,856 real top-of-book quotes across 16 days spread over 2010 to 2025 give a 0.2606 point average spread and a $13.03 round turn. At double that cost the ratio is -0.44. 7 of 15 years were positive, so this is not one bad year, and buy and hold made $310,148 over the same windows and beat all of it. Validation label: walk-forward out of sample, no evidence of exploitable edge. The 5.6 million minute bars and the 73.7 million quotes behind this are included with QuantPad. No vendor account, no CSV hunting. #QuantPad #backtesting #algotrading #quanttrading #futurestrading

#kedientinhvaotinhyeu #tamtrang #xuhuongtiktok

#kedientinhvaotinhyeu #tamtrang #xuhuongtiktok

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