Quant Frameworks for Alpha

Quantitative Frameworks for Scalable Data Modeling and Alpha Extraction

Alternative data has become a proven source of alpha for quantitative investors but extracting its full value requires more than just access to the right datasets. This white paper, written in collaboration between Maiden Century and Consumer Edge, explores why the modeling infrastructure behind the data matters just as much as the data itself and how quants can build smarter, more scalable investment signals from consumer transaction data.

Across three distinct strategy profiles, Consumer Edge signals processed through Maiden Century’s QTIP platform have generated 19-25% annualized market-neutral returns with Sharpe ratios of 2-3x.

Key Takeaways

• Why alternative data challenges traditional quant models and the six core friction points holding funds back
• Consumer Edge is built for quant workflows from consistent entity resolution mapping to standardized accuracy reporting
• QTIP bridges the remaining gaps including ingestion, metric selection, fiscal period alignment, forward forecasting via Precast and benchmarking against street and buyside expectations
• Backtested results across three profiles covering US Daily Signal, Vela & Orion, and CEI Card datasets
• Overcoming limited history with SPIT a synthetic point-in-time methodology for evaluating newer datasets
• Building a truly proprietary signal using MRD tables to customize and go beyond the QTIP baseline

Whether you’re evaluating alternative data for the first time or looking to extract more alpha from datasets you already own, this paper provides a practical, infrastructure-first framework for systematic investors ready to go deeper.