gavindiaz/drift
1
0
Fork 0
mirror of https://github.com/webclinic017/drift.git synced 2026-07-28 03:08:01 +00:00
Code Issues Packages Projects Releases Wiki Activity
54 Commits 1 Branch 0 Tags
eea88103f43a0a155cc701b622fa3823d6fade55
T
Clone
Open with VS Code Open with VSCodium Open with Intellij IDEA
Download ZIP Download TAR.GZ Download BUNDLE
Mark Aron Szulyovszky eea88103f4 feat(Metrics): added probabilistic sharpe ratio (#82) 
* feat(Metrics): added probabilistic sharpe ratio

* Apply suggestions from code review
2021-12-23 17:06:22 +01:00
.github/workflows
refactor(Project): move out load_data to utils, rename fetch_data to run_fetch_data, got classifiers to work (#38)
2021-12-17 17:41:50 +01:00
.vscode
feat(Pipeline): save results, train on all assets
2021-12-14 22:59:44 +01:00
archive
refactor(Project): move out load_data to utils, rename fetch_data to run_fetch_data, got classifiers to work (#38)
2021-12-17 17:41:50 +01:00
data
refactor(Project): move out load_data to utils, rename fetch_data to run_fetch_data, got classifiers to work (#38)
2021-12-17 17:41:50 +01:00
feature_extractors
feat(Config): feature extractors are enabled one-by-one with a bool, added previous model to model.fit() (#77)
2021-12-23 10:35:20 +01:00
models
feat(Data): add option to predict 3 classes (#79)
2021-12-23 13:24:56 +01:00
reporting
feat(Config): feature extractors are enabled one-by-one with a bool, added previous model to model.fit() (#77)
2021-12-23 10:35:20 +01:00
tests
feat(Data): add option to predict 3 classes (#79)
2021-12-23 13:24:56 +01:00
training
feat(Data): add option to predict 3 classes (#79)
2021-12-23 13:24:56 +01:00
utils
feat(Metrics): added probabilistic sharpe ratio (#82)
2021-12-23 17:06:22 +01:00
.gitignore
feature: Added Weights and Biases configuration to the repo. (#48)
2021-12-20 14:01:14 +01:00
config.py
feat(Data): add option to predict 3 classes (#79)
2021-12-23 13:24:56 +01:00
conftest.py
feat(Tests): added basic unit tests for walk_forward_train_test() (#22)
2021-12-15 17:54:03 +01:00
environment.yml
feat(Models): added debug_future_lookahead, sped up LogisticRegression & DecisionTreeClassifier (#74)
2021-12-22 16:59:03 +01:00
exploration.ipynb
feat(Models): added model that predicts 10 days ahead
2021-11-12 16:10:55 +01:00
README.md
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)
2021-12-17 14:32:17 +01:00
run_fetch_data.py
refactor(Project): move out load_data to utils, rename fetch_data to run_fetch_data, got classifiers to work (#38)
2021-12-17 17:41:50 +01:00
run_pipeline.py
feat(Metrics): added probabilistic sharpe ratio (#82)
2021-12-23 17:06:22 +01:00
run_sweep.py
Feature: Added sweep functionality (#65)
2021-12-21 17:28:36 +01:00
sweep.yaml
fix(Sweep): config with constants
2021-12-23 14:13:52 +01:00
wandb_setup.py
feature: Added Weights and Biases configuration to the repo. (#48)
2021-12-20 14:01:14 +01:00

README.md

Financial time series prediction models

Installation

Use the conda environment file attached!:)

Reference in New Issue View Git Blame Copy Permalink
S
Description
No description provided
Readme 11 MiB
Languages
Python 85%
Jupyter Notebook 15%