About the Customer
A New York Based Stock Options TraderProblem Statement
Our client wanted to showcase traders' performance by capturing their trading signals on a Discord Channel. The idea was to highlight the quality of traders using their trading signals and then build a leader board of their performance.
Our Approach
We started with the product vision, Defined the project scope, and captured user requirements. Then we created an execution plan based on the Agile software development framework. We divided product feature delivery into multiple sprints. At the end of each sprint, we accommodated user feedback and then rolled out the feature.
Technical Solution Design
System Architecture Overview
The solution consisted of three tightly integrated components:
- Discord Bot (Python-based)
- Deployed within Discord to monitor designated trading channels
- Listened for structured trade signals (e.g., "BUY TSLA 150c @ $2.30")
- Parsed signal content using regex and NLP techniques to extract key metadata (ticker, direction, strike, price)
- Forwarded parsed data to the Django API using async message dispatch
- Deployed within Discord to monitor designated trading channels
- Backend (Django + PostgreSQL + Redis)
- Django REST API received data from the Discord bot and stored it in PostgreSQL
- Redis handled async message queuing and inter-process communication
- Calculated performance metrics (e.g., PnL, win rate, average return) per trader
- Generated and cached real-time leaderboards with Redis for performance
- Django REST API received data from the Discord bot and stored it in PostgreSQL
- Frontend (Django Web App)
- Web-based dashboard displayed:
- Trader profiles
- Signal history
- Real-time leaderboards
- Trader profiles
- Auth system for admin and trader roles
- Analytics view showing trends, consistency, and trade outcomes
- Web-based dashboard displayed:
Core Functionalities
- Real-Time Signal Tracking
- Discord bot instantly captures and forwards trade data
- Traders are automatically tagged and linked to their signals
- Discord bot instantly captures and forwards trade data
- Performance Analytics Engine
- Tracks entry and exit performance against market data
- Aggregates trader stats into a normalized score (for leaderboard ranking)
- Tracks entry and exit performance against market data
- Leaderboard & Reporting
- Displays top traders ranked by:
- Return %
- Accuracy
- Risk-adjusted return (Sharpe-like metric)
- Return %
- Daily, weekly, and monthly filters
- Displays top traders ranked by:
- Web Admin & Audit Logs
- Admin panel for signal moderation and audit trails
- Manual correction or removal of erroneous signals if needed
- Admin panel for signal moderation and audit trails
Deployment
- Discord bot hosted using a persistent Python process
- Django app containerized and deployed on cloud infrastructure (e.g., AWS/GCP)
- PostgreSQL and Redis services managed with high availability
- Used Redis pub/sub channels for real-time updates from bot to backend
Success Factors
bCubex delivered a technically robust and modular system that enabled:
- Live signal ingestion from Discord with near-zero latency
- Transparent trader performance tracking that fosters trust within the community
- An automated reporting framework that eliminated manual data entry or interpretation
- A scalable backend architecture built on Redis and Django, designed to handle growth as the trading community expands
The client now operates a high-engagement trader leaderboard platform, giving users a data-driven way to assess trading credibility and consistency.
