Transaction Cost Analysis with QuestDB and Polars: VWAP, Slippage and Markout

QuestDB is an open-source time-series database designed for high-performance workloads, such as those on trading floors, offering ultra-low latency, high ingestion throughput, and a multi-tier storage engine. It natively supports Parquet and SQL, allowing for data portability and AI-readiness without vendor lock-in. The text outlines a process for building a transaction cost analysis (TCA) pipeline using QuestDB, ConnectorX, and Polars, capturing live crypto market data to simulate and analyze the costs of a TWAP execution. QuestDB handles time-series data queries, ConnectorX efficiently transfers query results to Python, and Polars processes the data to generate actionable insights, such as comparing the average fill price against the market's volume-weighted average price (VWAP). The analysis highlights the impact of trading strategies on execution costs, emphasizing the importance of understanding market dynamics and adverse selection. The pipeline can be adapted for various real-world applications, including execution scorecards and backtesting, demonstrating the flexibility and power of open-source tools in financial data analysis.

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