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Мой живой онлайн мониторинг торговли с помощью моделей Синергии, на реальном счёте пропа США на 60 000$:
https://gog.su/veMr
Мой сигнал MQL5:
https://www.mql5.com/ru/signals/2235168?source=Site+Profile
Один из отчетов тестов роботов:
https://goo.su/YWBdvA
Мой ПАММ счет Робофорекс:
https://www.copyfx.com/ratings/rating-all/show/221809/tab/profit/period/week/
Мой ПАММ Финама (Автоследование:
https://www.comon.ru/strategies/118977/
Мой YouTube:
https://youtube.com/@shtenco?si=bhJ3GhyMaU-9_GRH
Онлайн трансляция торговли моих роботов с пропа США:
https://www.youtube.com/watch?v=_wGidU559-o
Мой Телеграмм канал в формате личного блога про экономику, рынок, трейдинг и алготрейдинг:
https://t.me/shtenncoeconomy
In this article, we will create a random forest model in Python, train the model, and save it as an ONNX pipeline with data preprocessing. After that we will use the model in the MetaTrader 5 terminal.
Here is a quantitative analysis indicator for any market. Its essence is simple - it calculates the magnitude of the waves of price movement from top to bottom, and gives the median value of the magnitude of the non-recoil trend. If the current value of the movement has exceeded this threshold by more than 10% (110% of the indicator indicator), you can enter a trade against the trend and work with a large margin of action based on ATR. Transactions are obtained with a high risk-reward ratio and
Here is a quantitative analysis indicator for any market. Its essence is simple - it calculates the magnitude of the waves of price movement from top to bottom, and gives the median value of the magnitude of the non-recoil trend. If the current value of the movement has exceeded this threshold by more than 10% (110% of the indicator indicator), you can enter a trade against the trend and work with a large margin of action based on ATR. Transactions are obtained with a high risk-reward ratio and