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Professional-grade market data for quantitative backtesting and algorithmic trading.

Norgate Data is a premier provider of historical and end-of-day market data specifically engineered for rigorous quantitative analysis. Unlike standard retail data feeds, Norgate's architecture focuses on the removal of survivorship bias by providing comprehensive access to delisted securities and historical index constituents. By 2026, Norgate has solidified its position in the 'Quant-Stack' by offering a seamless bridge between high-quality normalized data and Python-based machine learning environments. The tool utilizes the Norgate Data Updater (NDU), a localized database management system that synchronizes cloud-hosted data to a local machine, allowing for ultra-fast, low-latency access during backtesting without the overhead of REST API calls. Its technical superiority lies in its granular treatment of corporate actions—such as splits, dividends, and spin-offs—offering users the choice between total return or price-only adjustments. This makes it an essential utility for institutional-level backtesting on platforms like AmiBroker, Wealth-Lab, and specialized Python libraries where data integrity is the primary determinant of model alpha.
Norgate Data is a premier provider of historical and end-of-day market data specifically engineered for rigorous quantitative analysis.
Explore all tools that specialize in market regime analysis. This domain focus ensures Norgate Data delivers optimized results for this specific requirement.
Maintains a database of every stock that ever traded on major exchanges, allowing users to test strategies on stocks that eventually went bankrupt or were merged.
Tracks exact dates of index entry and exit for major indices like S&P 500, Russell 2000, and Nasdaq 100.
Allows real-time toggling between Adjusted (Back-adjusted for splits/dividends) and Unadjusted data.
Synchronizes cloud data to a local high-performance binary storage format.
Comprehensive tracking of ticker changes, CUSIP changes, and defunct companies.
Native Python library that converts local binary data directly into Pandas DataFrames or NumPy arrays.
Links price data with time-stamped fundamental data like P/E ratios, Market Cap, and Dividend Yield.
Download and install the Norgate Data Updater (NDU) application on a Windows environment.
Authenticate using your subscription credentials to initialize the local database schema.
Select desired markets (e.g., US Equities, ASX, TSX) and historical depth.
Execute the 'Full Synchronization' to build the local historical binary files.
(For Python Users) Install the 'norgatedata' package via pip.
(For AmiBroker Users) Run the NDU AmiBroker Plugin to map local data to the charting engine.
Configure 'Surviving Ticker' settings to include or exclude delisted symbols in scans.
Set adjustment preferences for corporate actions (Proportional vs. Absolute).
Establish a scheduled task for daily post-market close updates.
Validate data integrity using the built-in diagnostic tools to ensure no gaps exist in local storage.
All Set
Ready to go
Verified feedback from other users.
"Highly praised for data cleanliness and reliability among serious quantitative traders, though criticized for its Windows-only local updater requirement."
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