Hi everyone,
I’ve developed a deep learning AI model designed to predict ETH’s price movement over the next 24 hours on the 15-minute timeframe.
It’s important to note that this model does not directly provide exact entry points for trades. Instead, it indicates the likely direction of the market, meaning you’ll still need basic trading knowledge to apply it effectively.
After testing it over the course of one month, I achieved a success rate of around 90% in my trades when using the model as part of my strategy.
The model was trained using the following features:
Time-related: Hour, DayOfWeek
Price & volume lags: Close_lag_1, Close_lag_2, Close_lag_4, Close_lag_8, Close_lag_12, Volume_lag_1, Volume_lag_2, Volume_lag_4, Volume_lag_8, Volume_lag_12
Moving averages & statistics: MA_4, Std_4, Dist_MA_4, MA_16, Std_16, Dist_MA_16, MA_48, Std_48, Dist_MA_48, MA_96, Std_96, Dist_MA_96
Technical indicators: Return_log, MACD, RSI
Hourly Forecast for the Next 24 Hours
2025-09-18 12:00:00+00:00 4570.725599
2025-09-18 13:00:00+00:00 4558.693652
2025-09-18 14:00:00+00:00 4546.442637
2025-09-18 15:00:00+00:00 4534.256704
2025-09-18 16:00:00+00:00 4522.277544
2025-09-18 17:00:00+00:00 4510.699341
2025-09-18 18:00:00+00:00 4499.536408
2025-09-18 19:00:00+00:00 4488.703938
2025-09-18 20:00:00+00:00 4478.101359
2025-09-18 21:00:00+00:00 4467.636393
2025-09-18 22:00:00+00:00 4457.235836
2025-09-18 23:00:00+00:00 4446.846200
2025-09-19 00:00:00+00:00 4436.441950
2025-09-19 01:00:00+00:00 4427.617370
2025-09-19 02:00:00+00:00 4420.516500
2025-09-19 03:00:00+00:00 4413.416921
2025-09-19 04:00:00+00:00 4405.776459
2025-09-19 05:00:00+00:00 4397.661417
2025-09-19 06:00:00+00:00 4389.237012
2025-09-19 07:00:00+00:00 4380.625582
2025-09-19 08:00:00+00:00 4371.890136
2025-09-19 09:00:00+00:00 4363.069585
2025-09-19 10:00:00+00:00 4354.201563
2025-09-19 11:00:00+00:00 4345.320931
I’ve developed a deep learning AI model designed to predict ETH’s price movement over the next 24 hours on the 15-minute timeframe.
It’s important to note that this model does not directly provide exact entry points for trades. Instead, it indicates the likely direction of the market, meaning you’ll still need basic trading knowledge to apply it effectively.
After testing it over the course of one month, I achieved a success rate of around 90% in my trades when using the model as part of my strategy.
The model was trained using the following features:
Time-related: Hour, DayOfWeek
Price & volume lags: Close_lag_1, Close_lag_2, Close_lag_4, Close_lag_8, Close_lag_12, Volume_lag_1, Volume_lag_2, Volume_lag_4, Volume_lag_8, Volume_lag_12
Moving averages & statistics: MA_4, Std_4, Dist_MA_4, MA_16, Std_16, Dist_MA_16, MA_48, Std_48, Dist_MA_48, MA_96, Std_96, Dist_MA_96
Technical indicators: Return_log, MACD, RSI
Hourly Forecast for the Next 24 Hours
2025-09-18 12:00:00+00:00 4570.725599
2025-09-18 13:00:00+00:00 4558.693652
2025-09-18 14:00:00+00:00 4546.442637
2025-09-18 15:00:00+00:00 4534.256704
2025-09-18 16:00:00+00:00 4522.277544
2025-09-18 17:00:00+00:00 4510.699341
2025-09-18 18:00:00+00:00 4499.536408
2025-09-18 19:00:00+00:00 4488.703938
2025-09-18 20:00:00+00:00 4478.101359
2025-09-18 21:00:00+00:00 4467.636393
2025-09-18 22:00:00+00:00 4457.235836
2025-09-18 23:00:00+00:00 4446.846200
2025-09-19 00:00:00+00:00 4436.441950
2025-09-19 01:00:00+00:00 4427.617370
2025-09-19 02:00:00+00:00 4420.516500
2025-09-19 03:00:00+00:00 4413.416921
2025-09-19 04:00:00+00:00 4405.776459
2025-09-19 05:00:00+00:00 4397.661417
2025-09-19 06:00:00+00:00 4389.237012
2025-09-19 07:00:00+00:00 4380.625582
2025-09-19 08:00:00+00:00 4371.890136
2025-09-19 09:00:00+00:00 4363.069585
2025-09-19 10:00:00+00:00 4354.201563
2025-09-19 11:00:00+00:00 4345.320931
액티브 트레이드
매매 수동청산
I manually closed the position after holding it for more than 24 hours, securing a profit of around 3%.면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.
면책사항
이 정보와 게시물은 TradingView에서 제공하거나 보증하는 금융, 투자, 거래 또는 기타 유형의 조언이나 권고 사항을 의미하거나 구성하지 않습니다. 자세한 내용은 이용 약관을 참고하세요.