RSI-divergence-detector
intelligent-trading-bot
| RSI-divergence-detector | intelligent-trading-bot | |
|---|---|---|
| 1 | 25 | |
| 71 | 745 | |
| - | - | |
| 0.0 | 8.5 | |
| 11 months ago | about 1 month ago | |
| Python | Python | |
| MIT License | MIT License |
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RSI-divergence-detector
intelligent-trading-bot
-
TimeGPT-1
I agree that the conventional (numeric) forecasting can hardly benefit from the newest approaches like transformers and LLMs. I made such a conclusion while working on the intelligent trading bot [0] by experimenting with many ML algorithms. Yet, there exist some cases where transformers might provide significant advantages. They could be useful where the (numeric) forecasting is augmented with discrete event analysis and where sequences of events are important. Another use case is where certain patterns are important like those detected in technical analysis. Yet, for these cases much more data is needed.
[0] https://github.com/asavinov/intelligent-trading-bot Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
- intelligent-trading-bot: NEW Other Models - star count:567.0
- intelligent-trading-bot: NEW Other Models - star count:494.0
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