ImperialCollegeLondon / ImperialCollegeLondon/ReCoDE-DecodingMarketSignals
Add logistic regressor and apply it to the candlestick signals
Open
- Dominant language
- Jupyter Notebook
- Stars
- 2
- Forks
- 1
- PR merge metrics
- No merged PRs in 30d
Description
As title implies
Contributor guide
No contributing guide indexed for this repository
Research direction
Start by locating the notebook cells that generate candlestick signals and the existing workflow for predicting future stock returns. Determine the intended regression inputs, target labels, training and evaluation method, then consider the work complete when the logistic regressor is applied and its results are evaluated against the existing signals.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100