Daniel Szemerey 3084f5e271 Refractor(Main Pipeline): Refractored the two main steps and the data processing. (#156) ...

* refr: Took out main primary and secondary loops and data processing.

* feat: Tidied the code up.

* feat: Saving models and results now works in a type safe way.

* fix: There was error in the saving function.

* chore: Took out some remaining comments.

* fix: Fixed the previous data checking process.

* feat: Fixed model selection method. I will continue the inference after we merged.

Co-authored-by: Daniel Szemerey <szemereydaniel@gmail.com>

2022-01-12 23:10:18 +01:00

..

glassnode

feat(Data): added daily_glassnode DataCollection (#99)

2022-01-03 13:57:36 +01:00

encapsulation.py

Refractor(Main Pipeline): Refractored the two main steps and the data processing. (#156)

2022-01-12 23:10:18 +01:00

evaluate.py

feat(Evaluation): adjusted transaction costs to be more realistic 0.3% (#150)

2022-01-11 12:41:02 +01:00

hashing.py

feat(DataLoader): caching MVP, added ability to use standard scaling for exogenous data, scaling is now also done before feature selection (#105)

2022-01-04 11:44:35 +01:00

helpers.py

feat(Reporting): added robustness / correlation test (#138)

2022-01-09 20:00:03 +01:00

metrics.py

feat(Metrics): added probabilistic sharpe ratio (#82)

2021-12-23 17:06:22 +01:00

scaler.py

refactor(WalkForward): separate train / test functions to help with inference later (#158)

2022-01-12 14:42:16 +01:00

sktime.py

feat(Models): added a basic sktime model and missing USD crypto currency pairs (#7)

2021-11-17 22:28:34 +01:00

technical_indicators.py

feat(Data): added new derived features + asset pairs for crypto tickers (#6)

2021-11-17 12:07:49 +01:00

types.py

feat(DataLoader): caching MVP, added ability to use standard scaling for exogenous data, scaling is now also done before feature selection (#105)

2022-01-04 11:44:35 +01:00

visualize.py

feat(Model): now successfully training the basic LSTM model

2021-11-11 18:29:05 +01:00