feat(HPO): added run_hpo script (#237)

* feat(HPO): added `run_hpo` script

* fix(Linter): ran

* feat(HPO): removed any reference to sweep (superseeded by optuna)

* fix(HPO): optimize for sharpe

* fix(Config): removed glassnode data, save trials from hpo

* feat(Labelling): added three-balanced method works again

* fix(BetSizing): set the correct class labels

* fix(HPO): powerset should return what's expected, added two new normalization methods

* fix(Linter): ran

* fix(DataLoader): sort the dataframe when fetching data

* fix(Config): only take z-score of other assets

labeling/labellers/fixed_time_three_class_balanced.py

@@ -1,7 +1,7 @@
 from data_loader.types import ReturnSeries
 from ..types import EventLabeller, EventsDataFrame
 import pandas as pd
-from .utils import create_forward_returns
+from .utils import create_forward_returns, discretize_threeway_threshold
 from typing import Callable
 
 
@@ -58,4 +58,4 @@ class FixedTimeHorionThreeClassBalancedEventLabeller(EventLabeller):
         return [-1, 0, 1]
 
     def get_discretize_function(self) -> Callable:
-        raise NotImplementedError
+        return discretize_threeway_threshold(0.02)