/QuanTAlib

C# TA library for real-time financial analysis, offering ~100 indicators. Available on NuGet, Quantower compatible. Ensures early validity of calculated data, calculation accuracy tested against four TA libraries.

Primary LanguageC#Apache License 2.0Apache-2.0

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Nuget GitHub last commit Nuget GitHub watchers .NET8.0

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QuanTAlib - quantitative technical indicators for Quantower

Quantitative TA library (QuanTAlib) is a C# library of classess and methods for quantitative technical analysis useful for analyzing quotes with Quantower and other C#-based trading platforms.

Visit documentation pages
List of indicators - implemented and planned

QuanTAlib is a C# library written with some specific design criteria in mind. Here is why there is 'yet another C# TA library':

  • QuanTAlib focuses on real-time data analysis: As new data items arrives, indicators don't have to re-calculate the entire history and can generate a result directly from the last item
  • Allow updates/corrections of the last quote - QuanTAlib is re-calculating the last value as many times as required before continuing to the new bar
  • Calculate early data right - calculated data is as valid as mathematically possible from the first value onwards - no blackout or warming-up periods. All indicators return data from the first bar, alongside with a flag isHot - defining if calculation is already stable.

Installation to Quantower

  • <Quantower_root> is the directory where Quantower is installed - where Start.lnk launcher is. Copy any or all dll files as below:
  • Copy Averages.dll from Releases to <Quantower_root>\Settings\Scripts\Indicators\Averages\Averages.dll
  • Copy Statistics.dll from Releases to <Quantower_root>\Settings\Scripts\Indicators\Statistics\Statistics.dll
  • Copy Volatility.dll from Releases to <Quantower_root>\Settings\Scripts\Indicators\Volatility\Volatility.dll
  • Copy SyntheticVendor.dll from Releases to <Quantower_root>\Settings\Scripts\Vendors\SyntheticVendor\SyntheticVendor.dll

QuanTAlib is intended for developers and users of Quantower, therefore it does not focus on privind sources of OHLCV quotes. There are some very basic data feeds available to use in the learning process: GBM_Feed for Random (Geometric Brownian Motion) data, and SyntheticVendor data generator for Quantower.

Validation

QuanTAlib uses validation tests with four other TA libraries to assure accuracy and validity of results: