
Over a two-month period, contributed to the MQSMaster repository by building core trading system capabilities and enhancing portfolio management infrastructure. Developed a positions tracking system and implemented trade execution logic, enabling accurate P&L and inventory management across portfolios. Expanded the backend with a modular backtesting framework supporting multi-portfolio strategies and improved capital distribution. Enhanced live trading reliability through robust data fetching, initialization routines, and data integrity utilities. Leveraged Python, SQL, and Pandas to design scalable, object-oriented components for algorithmic trading, data engineering, and financial modeling. The work established a foundation for reliable live trading and flexible quantitative strategy development.
June 2025 performance snapshot for MQSMaster focusing on reliable live data, robust execution, and scalable backtesting infrastructure. Delivered end-to-end improvements across live data fetch, initialization and PnL handling, plus a modular backtesting framework with multi-portfolio support and refined capital distribution. Implemented portfolio management enhancements and data-quality utilities to improve strategy fidelity and data integrity. These changes enhance operational reliability, enable safer live trading, and support scalable testing for multiple portfolios.
June 2025 performance snapshot for MQSMaster focusing on reliable live data, robust execution, and scalable backtesting infrastructure. Delivered end-to-end improvements across live data fetch, initialization and PnL handling, plus a modular backtesting framework with multi-portfolio support and refined capital distribution. Implemented portfolio management enhancements and data-quality utilities to improve strategy fidelity and data integrity. These changes enhance operational reliability, enable safer live trading, and support scalable testing for multiple portfolios.
March 2025 milestone: Delivered core Trading Core capabilities in MQSMaster with positions tracking and trade execution. Implemented a positions table to track asset quantities per portfolio and ticker; added buy, sell, and liquidate methods in tradeExecutor to manage trades, update cash balances, and log execution details. This enables core trading operations, supports accurate P&L and inventory management, and establishes a foundation for scalable portfolio analytics. Changes tracked under commit bcc75f8d050be3fff84014e921c118b02d1e3894 (message: tradingOps).
March 2025 milestone: Delivered core Trading Core capabilities in MQSMaster with positions tracking and trade execution. Implemented a positions table to track asset quantities per portfolio and ticker; added buy, sell, and liquidate methods in tradeExecutor to manage trades, update cash balances, and log execution details. This enables core trading operations, supports accurate P&L and inventory management, and establishes a foundation for scalable portfolio analytics. Changes tracked under commit bcc75f8d050be3fff84014e921c118b02d1e3894 (message: tradingOps).

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