I’ve also added an algorithm to check how effective the predictions are. For BTC, the success rate is currently around 75%.
Some coins have a 0% success rate, while others are at 90-99%.
That's interesting. How many simulations have you done? What's the biggest factor that determines this success rate? 90% sounds too high even if your model is really good. It's just hard to believe based on my experience.
As for a GPU VPS server — it could definitely make things easier, but I’d really prefer not to publish the code on external platforms.
The issue isn’t even the code itself, since all the ML models are public, but rather the specific AI configuration.
Are you afraid that the VPS/host will record your source code? Can't you package or encrypt it before running it on other computers?
Approximately 150 predictions for each of the 18 cryptocurrencies over the past month. Half of the coins fit into ideal statistics due to non-volatile predictions of 2%-5%, which were easily fulfilled over time.
Right now, I'm experimenting with different coins and just keeping those that show good statistics, while removing the others. Tracking down the reason why some assets are predictable while others aren’t remains a mystery to me.
Here’s how a good forecast and an anomalous one look:
https://i.ibb.co/Vt4X0bw/photo-2024-11-11-14-43-47.jpghttps://i.ibb.co/19m71jS/photo-2024-11-11-14-44-48.jpgYes, it’s possible to encrypt the code, but I prefer a security approach based on the black box principle.
