feat(Portfolio): reporting MVP (#108)

* feat(DataLoader): added load_only_returns() method

* feat(Portfolio): load predictions

* feat(Portfolio): normalize weights

* feat(Portfolio): started integrating with portfoliobt

* feat(Portfolio): include fees in the portfolio construction

* feat(Portfolio): demo of pyportfolioopt

* feat(Portfolio): get efficient frontier calculation to work

* feat(Portfolio): add a few strategies to create weights

* chore(Dependencies): remove pyportfolioopt for now

* fix(Dependencies): try to install all dependencies with pip

* fix(Dependencies): indentation

* fix(Dependencies): corrected pytorch module name

* fix(Dependencies): try to have as many modules installed by conda for the sake of sanity?

* fix(Dependencies): put fracdiff into pip modules

* fix(Dependencies): revert to using pip almost exclusively

* feat(Portfolio): added alphalens

* fix(Portfolio): got limited weights working

* feat(Portfolio): trying to get alphalens to work

* feat(Portfolio): alphalens working

* fix(Dependencies): removed vectorbt

* fix(Dependencies): use alphalens-reloaded

* fix(Dependencies): added conda source for alphalens-reloaded

* refactor(Portfolio): removed traces of vectorbt

* feat(Reporting): factor reporting done

* feat(Portfolio): added pyfolio reporting (fails bc alphalens is not working properly lol)

environment.yml

@@ -3,6 +3,7 @@ channels:
   - johnsnowlabs
   - conda-forge
   - defaults
+  - ml4t
 dependencies:
   - python=3.9
   - seaborn
@@ -25,6 +26,8 @@ dependencies:
   - pip
   - pandas-ta
   - xgboost
+  - alphalens-reloaded
+  - pyfolio-reloaded
   - pip:
     - fracdiff
     - ray