Comments (2)
it should be able to produce an expected 'profit' for a given investment, the point is to have this thing show up in the streamlit UI to show users how much they could be making if they use our predictions
from financial_news_sentiments.
the proportion of investment in each stock can be equivalent to the rmse of the model predicting it.
meaning we take the top 30 most buzzing stocks from sentiment, take the 5 top performing models on these stocks, and invest according to their rmse/r^2 rating.
Another direction: maybe the most buzzing stocks are the ones that are most likely to present new anomalous behavior that breaks the model. so in this case, lets test the same process but with the 30 least buzzing stocks
from financial_news_sentiments.
Related Issues (20)
- time is never added HOT 3
- fix documentation in new model.py
- Recreate keys
- move all services to lambda HOT 3
- add volume X sentiment indicators HOT 1
- Move databases to snowflake/mongoDB HOT 1
- open container with the model HOT 1
- convert databases to rds
- move the model library to AWS
- make show shiny looking graphs with the model and stuff
- change efs connectivity
- make interface change width automatically
- add links to articles
- Include forex and bitcoin in stock scrape HOT 1
- create RNN model for long predictions
- show earnings in basic stock data HOT 1
- collect future earnings data
- collect and show the rest balance sheets in stock data
- Add earnings to stock recommendation page
- update graphs in readme
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from financial_news_sentiments.