Quant teams should be testing ideas, building models, and analysing execution. Too often, they are still cleaning feeds, resolving symbology, applying corporate actions, checking timestamps, and waiting for infrastructure before research can begin.
Raw market data is rarely ready for research. It arrives fragmented across venues, with inconsistent formats, mismatched symbology, gaps in history, and timestamps that do not always align. Before a backtest or model can be trusted, that data has to be cleaned, mapped, adjusted, validated, and made query-ready.
That recurring preparation burden is the Data Tax.
This ebook explains where that tax shows up, what it costs, and how OneTick Market Data helps research teams reduce the work between raw market data and usable analysis.
What you’ll learn:
- Why market data preparation slows quant research before the first query runs
- Where the Data Tax appears across onboarding, symbology, corporate actions, timestamp alignment, replay, and infrastructure upkeep
- How in-house market data builds become long-term engineering and operations commitments
- What research-ready market data needs to provide: access, trust, scale, and ownership
- How OneTick Market Data gives teams prepared, query-ready market data across 250+ global markets and venues
- How teams can start through OneTick Cloud, deploy into their own environment, or use KDB-X for deeper control
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