HackUTD

GS Challenge

building co-relation between non-traditional fundamentals like social media chatter and activity, industry leader influences, trends/bubbles created by groups of retail investors etc, and their relation to performance of different types of asset classes including digital/crypto.
We would like the participants to develop an investment platform that makes investment recommendations and trading strategy by leveraging data available on historic and current performance of investment products and data available from various outlets on social media activity, sentiment, chatter, influencers etc.
You are encouraged to explore beyond the traditional metrics and research different ways this information could be presented as a critical tool, including possibly assigning ‘Social Ratings/Scores’ and tying this research to preferences that users might have based on their own investment history and risk tolerance.

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
Apple-Twitter-Sentiment-DFE.csv		Apple-Twitter-Sentiment-DFE.csv
Combined_News_DJIA.csv		Combined_News_DJIA.csv
DRL.ipynb		DRL.ipynb
GS_Stock_Prediction.jpg		GS_Stock_Prediction.jpg
HLD.jpeg		HLD.jpeg
HackUTD.ipynb		HackUTD.ipynb
LSTM-HLD-Arch.jpeg		LSTM-HLD-Arch.jpeg
README.md		README.md
RedditNews.csv		RedditNews.csv
autocorrelation_data.txt		autocorrelation_data.txt
drl.ipynb		drl.ipynb
upload_DJIA_table.csv		upload_DJIA_table.csv