Anyone ever did any trade app, terminal, trading related business?
Content Summary
Opinion Analysis
Mainstream opinions focus on the technical and financial challenges of building trading applications. u/Ok_Cauliflower5314 highlights the capital-intensive nature of trading bots and the complexity of parameter optimization. u/Sea_Contest7952 emphasizes critical technical aspects like data latency, risk management architecture, and the importance of backtesting. There's consensus on the need for reliable infrastructure and careful planning. No significant conflicting opinions appear, but different perspectives exist: one commenter focuses on algorithmic strategy implementation, while another stresses system architecture. The debate implicitly centers on balancing financial constraints with technical robustness.
SAAS TOOLS
| SaaS | URL | Category | Features/Notes |
|---|---|---|---|
| Polygon.io | http://Polygon.io | Market Data Vendor | Mentioned as a tried market data vendor |
| Supabase | Database | Mentioned as a tried solution | |
| DreamFactory | API Management | Used to expose MySQL risk tables as REST instantly | |
| Redis Streams | Message Bus | Used for bus in pre-trade risk checks |
USER NEEDS
Pain Points:
- High capital requirements for trading bots
- Complexity in finding optimal parameters (leverage, rebuy quantities)
- Data latency issues in trading apps
- Need for reliable market data vendors
- Importance of pre-trade risk checks
- Compliance challenges
Problems to Solve:
- Building profitable trading bots with limited capital
- Optimizing trading strategies (entry points, liquidation handling)
- Ensuring low latency in trading applications
- Implementing robust risk management systems
- Streamlining API development for risk tables
Potential Solutions:
- Using algorithmic strategies like RSI-based entry points and averaging down
- Employing reliable market data vendors and stress-testing throughput
- Separating order router from UI and using dedicated services for risk checks
- Utilizing tools like Redis Streams for message bus
- Leveraging API management tools (e.g., DreamFactory) to expose databases instantly
- Backtesting in sandbox environments before live deployment
GROWTH FACTORS
Effective Strategies:
- Focusing on core technical challenges like latency and reliability
- Implementing robust risk management systems
- Streamlining development with API management tools
Marketing & Acquisition:
- Not explicitly mentioned in the content
Monetization & Product:
- Potential for tools that simplify trading bot development
- Need for affordable solutions given high capital requirements mentioned
- Value in backtesting and sandbox environments
User Engagement:
- Community sharing of strategies and tools (as seen in the post)
- Providing educational content on risk management and optimization