y_bt is a good start which uses encoded y_t all the way to y+t+30 data but there are more ways to encode information in soft labels like using a further timeline (like having a list of y_30, y_90, y_180, y* encoded with past and future data ect) the earlier data avaialble, perhaps encoding economic meanings, tax alpha states in a generated DI portfolio, ect, a more infomration-encoded objecive than the current y_bt for 0.1-0.2v. (make sure that feature space does not encode this information on an each lot model treats as iid)
for ex:
$y_{\text{persist},30} = \frac{1}{30} \sum_{s=1}^{30} f^*(x_{t+s})$
$y_{\text{alpha},30} = \frac{1}{30} \sum_{s=1}^{30} \alpha_{\text{tax}}(x_{t+s}) f^*(x_{t+s})$
$y_{\text{max},30} = \max_{1 \leq s \leq 30} \alpha_{\text{tax}}(x_{t+s}) f^*(x_{t+s})$
encodes fairly accurate assumptive behaviors about the stable positions in indicies like the S&P 500 mainly of the fact that high volatility / paradigm shift based price movements are extremely rare while overall trends in a direction over weeks or months is much more common, highest ROI essentailly for the most simplicity.
Each label will have its own leader board of auc/pr scores and such along loss and objective functions towards each label.
y_bt is a good start which uses encoded y_t all the way to y+t+30 data but there are more ways to encode information in soft labels like using a further timeline (like having a list of y_30, y_90, y_180, y* encoded with past and future data ect) the earlier data avaialble, perhaps encoding economic meanings, tax alpha states in a generated DI portfolio, ect, a more infomration-encoded objecive than the current y_bt for 0.1-0.2v. (make sure that feature space does not encode this information on an each lot model treats as iid)
for ex:
encodes fairly accurate assumptive behaviors about the stable positions in indicies like the S&P 500 mainly of the fact that high volatility / paradigm shift based price movements are extremely rare while overall trends in a direction over weeks or months is much more common, highest ROI essentailly for the most simplicity.
Each label will have its own leader board of auc/pr scores and such along loss and objective functions towards each label.