TST
Telecommunication Technical Service Jsc
stock NASDAQ

Are you stacking? I don’t see the point in added complexity to run a tree and a path based model on top of each other. You can just create path based features for the tree model itself. Transformers are historically very poor at reading financial data.
You need to run some form of token model if you want to go the temporal sequence route.
Patch TST, token attention model, or maybe Mamba would be a good place to start.
Classic transformers are just worse than trees.
Retraining frequently isn’t a bad idea in theory but you’re kind of fighting yourself.
You are sampling every 12 hours which is 2 very different market conditions.
You are running a transformer which is data hungry.
You have protections in place to limit short term noise affecting the model.
The problem is you’re wanting the model to learn from the short term week-to-week market regime shifts. But you’re feeding a transformer limited data, you have features in place to limit short term changes. And so in a sense you don’t gain much at all from the trainings.
Unless you are running some like HFT style bot (which is unlikely due to crypto fees) the shift in regimes for more mid-macro doesn’t change enough to even validate a training this often imo

Are you stacking? I don’t see the point in added complexity to run a tree and a path based model on top of each other. You can just create path based features for the tree model itself. Transformers are historically very poor at reading financial data.
You need to run some form of token model if you want to go the temporal sequence route.
Patch TST, token attention model, or maybe Mamba would be a good place to start.
Classic transformers are just worse than trees.
Retraining frequently isn’t a bad idea in theory but you’re kind of fighting yourself.
You are sampling every 12 hours which is 2 very different market conditions.
You are running a transformer which is data hungry.
You have protections in place to limit short term noise affecting the model.
The problem is you’re wanting the model to learn from the short term week-to-week market regime shifts. But you’re feeding a transformer limited data, you have features in place to limit short term changes. And so in a sense you don’t gain much at all from the trainings.
Unless you are running some like HFT style bot (which is unlikely due to crypto fees) the shift in regimes for more mid-macro doesn’t change enough to even validate a training this often imo