Winter-Soren/edelweiss-hackathon

Images: http://bit.ly/team-team-edlws23-imgs, PPT: http://bit.ly/team-team-edlws23-ppt, YouTube: https://youtu.be/AreBDHiYldE

AnyChains

Made with ❤️ in ** TypeScript, ReactJS, Socket.io, NodeJS, MySQL, Docker, Tensorflow **

PPT: https://drive.google.com/drive/folders/1XymQctoBSM9G-tAW6uogpTuV6vzV0oyp?usp=sharing Video: https://youtu.be/VaWrNPhS0YQ

Run Locally

Clone the project

  git clone https://github.com/HarshalHDave/Edelweiss

Ensure that you are on main branch. Instructions are mentioned in all the respective directories.

• ai: Machine Learning to predict price of an option.
• backend: NodeJS interfaces with the TCP data stream, Socket.io communicates with the client app.
• data_server: java server streaming data.
• frontend: ReactJs webapp rendering live data.

Checkmarks

Status	Features
✅	Highlight the "in the money" options and "out of money" options differently as shown in above example.
✅	There must be a selection of underlying and different expiries.
✅	The options chain should work in real-time. As the market data changes, the fields should be recalculated and refreshed on screen without having to reload on the browser.
✅	Implied Volatility
✨	Graphs (candlesticks)
✨	Graphs OI
✨	5 + Greek metrics
✨	Risk Management
✨	Responsive PWA
✨	Price predictor AI
✨	Fail safe measures (data is persisted in a DB)

Screenshots

Functional and elastic system, real time rendering data without reload. 5+ statistics essential for traders also in real time.

Trends and graphs representing of stocks options.

Detailed view of options. Risk coupling module reccomending loss reducing options based on high/low risk or hedge startegy.

Responsive PWA

✍️ Acknowledgements

• Aditya Pai : Frontend integration and Data Management.
• Gautam Vishwakarma : Backend, Data Management.
• Harshal Dave : Frontend, UI Data Management, Domain Knowledge, Product Vision.
• Hussain Pettiwala : Frontend, UI, Backend.
• Soham Bhoir : Frontend, AI