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Data Sources

Support lookup, provider families, .SIM methodology, and drift interpretation.

Use This Page

This page now handles both the exact-support lookup and the deeper methodology reference.

  • Do you already support this ticker or workflow?
  • Should I use live data, a .SIM ticker, a generated input, a Research Ticker, or an uploaded series?
  • If a .SIM ticker exists, how was it built and how close is it to the live ETF overlap?

SIM Catalog

.SIM tickers use the naming convention TICKER.SIM (e.g. VLV.SIM, TLT.SIM, UPRO.SIM) and provide extended histories for asset classes that didn't exist as ETFs in earlier decades. Each .SIM ticker maps to a real ETF and uses academic or government data sources to reconstruct returns before the ETF existed. Post-inception, the synthetic model is stitched with actual ETF data so you get real market prices where available.

Ticker Lookup

Add tickers one at a time to inspect support, type, and timeline. You can also paste a comma-separated list.

SPY

Inspect a .SIM ticker

Select a .SIM ticker to view its generation methodology, data sources, and model accuracy since ETF inception. The drift chart is the fastest way to see whether a model is close enough for your use case.

Provider Families

ArthaPilot uses several data sources, each serving a specific role:

  • InsightSentry: primary source for daily price data on US equities and ETFs.
  • FRED (Federal Reserve Economic Data): macroeconomic time series including Treasury yields, CPI, and interest rates.
  • Coin Metrics Community: public crypto market data for supported digital assets.
  • Fama-French: academic factor data from Ken French's Data Library, including size, value, and daily portfolio returns back to 1926.
  • Shiller: Robert Shiller's long-history dataset for the S&P 500, including total return index and CPI going back to 1871.