feat(Core): ensemble models, correct forward returns calculation, scaling, only train from when asset returns are available, major bug fixed in walk_forward_train_test (#35)

* fix(Core): correct forward returns calculation, classifiers are now working again, only train from when asset returns are available

* feat(Utils): added get_first_valid_return_index()

* feat(Ensemble): return models from `run_whole_pipeline`

* feat(Ensemble): added ensemble step, fixed walk_forward_train_test predictions index confusion,

* chore(Pipeline): remove unnecessary extra ensemble results dataframe

* refactor(Core): removed unnecessary ensemble_train_predict, moved run_single_asset_trainig_pipeline to a separate file

* feat(Training): added scaling on expanding window (the past) to walk_forward_train_test(), now printing out mean sharpe ratio

* feat(CI): added environment.yml file

* chore(Environment): update env.yml

* feat(CI): added testing workflow

* fix(CI): renamed enviroment.yml

* fix(Tests): added missing new parameter to walk_forward_train_test()
This commit is contained in:
Mark Aron Szulyovszky
2021-12-17 14:32:17 +01:00
committed by GitHub
parent 1eaba0c221
commit cc7061b456
12 changed files with 385 additions and 195 deletions
-10
View File
@@ -49,13 +49,3 @@ def get_stock_price_av(symbol: str, start_date: str = None) -> pd.DataFrame:
df = df.rename_axis('time')
return df
# %%
# btc = get_crypto_price_av(symbol = 'BTC', exchange = 'USD', start_date = '2018-01-01')
# btc
# %%
# spy = get_stock_price_av(symbol = 'SPY', start_date = '2018-01-01')
# spy