Beibo, predict the stock market πΈ
December 30, 2021 Β· View on GitHub
Beibo is a Python library that uses several AI prediction models to predict stocks returns over a defined period of time.
It was firstly introduced in one of my previous package called Empyrial.
Disclaimer: Information is provided 'as is' and solely for informational purposes, not for trading purposes or advice.
How to install π₯
pip install beibo
How to use π»
from beibo import oracle
oracle(
portfolio=["TSLA", "AAPL", "NVDA", "NFLX"], #stocks you want to predict
start_date = "2020-01-01", #date from which it will take data to predict
weights = [0.3, 0.2, 0.3, 0.2], #allocate 30% to TSLA and 20% to AAPL...(equal weighting by default)
prediction_days=30 #number of days you want to predict
)
Output
About Accuracy
| MAPE | Interpretation |
|---|---|
| <10 | Highly accurate forecasting π |
| 10-20 | Good forecasting π |
| 20-50 | Reasonable forecasting π |
| >50 | Inaccurate forecasting π |
Models available
| Models | Availability |
|---|---|
Exponential Smoothing | β |
Facebook Prophet | β |
ARIMA | β |
AutoARIMA | β |
Theta | β |
4 Theta | β |
Fast Fourier Transform (FFT) | β |
Naive Drift | β |
Naive Mean | β |
Naive Seasonal | β |
Stargazers over time
Contribution and Issues
Beibo uses GitHub to host its source code. Learn more about the Github flow.
For larger changes (e.g., new feature request, large refactoring), please open an issue to discuss first.
- If you wish to create a new Issue, then click here to create a new issue.
Smaller improvements (e.g., document improvements, bugfixes) can be handled by the Pull Request process of GitHub: pull requests.
-
To contribute to the code, you will need to do the following:
-
Fork Beibo - Click the Fork button at the upper right corner of this page.
-
Clone your own fork. E.g.,
git clone https://github.com/ssantoshp/Beibo.git
If your fork is out of date, then will you need to manually sync your fork: Synchronization method -
Create a Pull Request using your fork as the
compare head repository.
You contributions will be reviewed, potentially modified, and hopefully merged into Beibo.
Contributions of any kind are welcome!
Acknowledgments
- Unit8 for Darts
- @ranroussi for yfinance
- This random guy on Python's Discord server who helped me
- @devnull10 on Reddit who warned me when I called the package The Oracle
Contact
You are welcome to contact us by email at santoshpassoubady@gmail.com or in Beibo's discussion space
License
MIT