https://github.com/davidteather/worst-stock-predictor
Predicts the worst stocks to invest in
https://github.com/davidteather/worst-stock-predictor
ai artificial-intelligence deep-learning investment investment-ai machine-learning stock stock-market stocks worst-stock-predictors youtube-video
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Predicts the worst stocks to invest in
- Host: GitHub
- URL: https://github.com/davidteather/worst-stock-predictor
- Owner: davidteather
- License: mit
- Created: 2020-08-16T00:49:22.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2020-08-20T16:12:52.000Z (almost 6 years ago)
- Last Synced: 2025-08-13T04:16:42.545Z (10 months ago)
- Topics: ai, artificial-intelligence, deep-learning, investment, investment-ai, machine-learning, stock, stock-market, stocks, worst-stock-predictors, youtube-video
- Language: Python
- Homepage: https://www.youtube.com/watch?v=OEbb5G4Awwc
- Size: 33.1 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Worst-Stock-Predictor
The training of the model is based on [this](https://www.thepythoncode.com/article/stock-price-prediction-in-python-using-tensorflow-2-and-keras) article and their code. However the evaluation script of all stocks on the NYSE and analysis is written by me.
# Demo
[](https://www.youtube.com/watch?v=OEbb5G4Awwc)
## Installing
Run the following command (tested on python 3.7.3)
```
pip install -r requirements.txt
```
## Training the model
Remove the current pre-trained model in results (or change the stock you want to train it on) and run the following command.
```
python train.py
```
You can change the stock it trains on and a few other options within the train.py file itself.
## Evaluating the model
If you want to only evaluate one stock at a time and show a graph of it run single_eval.py and change the ticker variable near the top of the file.
If you want to evaluate the model as a whole run eval.py and it will end looping over ~6,500 stocks on the NYSE. After this has finished run analysis.py and it'll give you some information about the data stored in the results.json file.
## Disclaimer
I am not responsible for any losses you may experience while using any models trained by the code I have provided. You should not expect to make any money and expect to lose it all, after all that was the primary focus of this project.