How do Fincanva and Coding Wand ensure data quality?

Fincanva, powered by Coding Wand, goes beyond simply sourcing data — it rigorously processes, validates, and enhances data to ensure accuracy and reliability. This commitment helps users create trustworthy simulations and make data-driven decisions without falling into common analytical traps.

• No Look-Ahead Bias: Fincanva timestamps all data based on the actual release date, not the reporting period. This ensures simulations only use information that would have been available at the time, mirroring real investment conditions.

• Delisted Assets Included: To avoid survivorship bias, Fincanva includes data for companies that were delisted, went bankrupt, or merged. This provides a realistic view of historical market dynamics.

• Revision-Aware Macroeconomic Data: For datasets like GDP or inflation, only the values publicly available at each specific point in time are used in simulations. Later revisions are ignored, maintaining historical authenticity.

• Systematic Selection Only: Users build portfolios through screeners or predefined asset lists — not by manually selecting "winners." This approach supports unbiased strategy testing.

• Data-Driven Filters: All filters used in Fincanva screeners and simulations are based on the same cleaned and validated datasets, ensuring consistency across every tool and analysis.

Through these robust practices, Fincanva and Coding Wand uphold a gold standard in data integrity, giving you the confidence to explore and trust your investment strategies.