Alina’s
Source: Notion | Last edited: 2025-03-20 | ID: 1bc2d2dc-3ef...
Technological Uncertainty & Advancement
Section titled “Technological Uncertainty & Advancement”Challenges Encountered
Section titled “Challenges Encountered”In fiscal 2024, I worked on various technological improvements and faced challenges such as:
- Scalability & Performance: Optimizing execution performance and session management.
- Data Integrity & Synchronization: Ensuring accurate real-time balance aggregation from multiple sources.
- Execution Reliability: Addressing failures in execution logging and preventing silent failures in automated session trading.
- Automation & Efficiency: Reducing manual intervention in trading session restarts and improving bulk execution capabilities.
Why Existing Solutions Were Insufficient
Section titled “Why Existing Solutions Were Insufficient”- Publicly available financial APIs (CCXT, Binance API, etc.) did not provide the necessary granularity for accurate historical PnL calculations and session-based execution strategies.
- Existing logging mechanisms did not capture all failure cases, requiring enhancements to track execution issues more effectively.
- Industry-standard portfolio aggregation solutions did not fully support multi-asset trading across multiple accounts, necessitating a custom real-time balance aggregation system.
Key Developments
Section titled “Key Developments”- Developed a backfill script for historical PnL data, computing interval-based averages to improve evaluation.
- Implemented a multi-asset collateral ratio configuration to enhance allocation settings and execution efficiency.
- Created a “Trade All” button to simplify trading across multiple sessions.
- Built a real-time balance aggregation feature, consolidating portfolio values across different asset types.
- Upgraded Serverless Framework to v4, improving deployment processes and compatibility.
Systematic Investigation & Experimental Development
Section titled “Systematic Investigation & Experimental Development”Hypotheses & Evaluation Methods
Section titled “Hypotheses & Evaluation Methods”I systematically tested different approaches to improve trading execution and data accuracy, including:
- PnL Calculation Accuracy: Could historical data be backfilled reliably?
- Session Execution Stability: Would a controlled restart mechanism improve execution reliability?
- Balance Synchronization: Could a unified method improve multi-asset balance calculations?
Iterative Experimentation
Section titled “Iterative Experimentation”Iteration 1: Initial Implementation of Averaged PnL
Section titled “Iteration 1: Initial Implementation of Averaged PnL”- Implemented interval-based PnL calculation.
- Encountered data inconsistencies due to API rate limits.
- Result: Required refinements for better accuracy.
Iteration 2: Enhancing Execution Logging
Section titled “Iteration 2: Enhancing Execution Logging”- Improved execution logging to track failures.
- Identified cases where errors were not properly logged.
- Result: Improved failure detection.
Iteration 3: Real-time Balance Aggregation
Section titled “Iteration 3: Real-time Balance Aggregation”- Developed an improved method to combine balances across different asset types.
- Integrated real-time pricing for more accurate total values.
- Result: Improved accuracy in portfolio value calculations.
Metrics for Improvement
Section titled “Metrics for Improvement”- Execution success rate before and after improved logging and restart automation.
- Accuracy of backfilled PnL compared to real-time calculations.
- Reduction in manual interventions required for session restarts.
Testing Methods
Section titled “Testing Methods”- Execution reliability tested in a simulated environment.
- Balance aggregation logic validated against historical data.
- Performance benchmarks measured API response times and log processing speeds.
Pitfalls Avoided
Section titled “Pitfalls Avoided”✅ Ensured Specificity: Clearly documented the reasons for alternative methods. ✅ Maintained Documentation: Kept records of test results and system changes. ✅ Demonstrated Novelty: Highlighted why in-house solutions were necessary. ✅ Tracked Iterative Refinements: Documented improvements across multiple iterations.
Chronological Time Tracking – SR&ED Work in 2024
Section titled “Chronological Time Tracking – SR&ED Work in 2024”Supporting Other Teams with SR&ED Documentation
Section titled “Supporting Other Teams with SR&ED Documentation”Throughout 2024, I contributed to helping other teams document their SR&ED work, including:
- Providing insights on PnL calculation refinements and backfilled data alignment.
- Assisting in tracking execution improvements and debugging strategies.
- Maintaining logs of experimental failures and solutions.
- Collaborating on multi-asset allocation logic for optimizing trading performance.
Conclusion
Section titled “Conclusion”In 2024, I worked on improving trading execution, balance aggregation, and performance optimization. Through systematic investigation, iterative testing, and enhancements, I contributed to advancing our system capabilities. These efforts align with SR&ED criteria, demonstrating a structured process for overcoming technical challenges.