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readme
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Miha Kralj
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# QuanTAlib - quantitative technical indicators for Quantower and other C#-based trading platorms
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[](https://sonarcloud.io/summary/overall?id=mihakralj_QuanTAlib)
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[](https://app.codacy.com/gh/mihakralj/QuanTAlib/dashboard)
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[](https://codecov.io/gh/mihakralj/QuanTAlib)
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[](https://sonarcloud.io/summary/new_code?id=mihakralj_QuanTAlib)
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[](https://www.nuget.org/packages/QuanTAlib/)
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[](https://www.nuget.org/packages/QuanTAlib/)
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[](https://github.com/mihakralj/QuanTAlib/watchers)
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[](https://dotnet.microsoft.com/en-us/download/dotnet/7.0)
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[](https://dotnet.microsoft.com/en-us/download/dotnet/6.0)
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[](https://dotnet.microsoft.com/en-us/download/dotnet-framework/net48)
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[](Docs/LICENSE)
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Quantitative TA Library (**QuanTAlib**) is an easy-to-use C# library for quantitative technical analysis with base algorithms, charts, signals and strategies useful for trading securities with [Quantower](https://www.quantower.com/) and other C#-based trading platforms.
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**QuanTAlib** is written with some specific design criteria in mind - this is a list of reasons why there is '_yet another C# TA library_':
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- Written in native C# - no code conversion from TA-LIB or other imported/converted TA libraries
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- No usage of Decimal datatypes, LINQ, interface abstractions, or static classes (all for performance reasons)
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- Supports both **historical data analysis** (working on bulk of historical arrays) and **real-time analysis** (adding one data item at the time without the need to re-calculate the whole history)
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- Separation of calculations (**algos**) and visualizations (**charts**)
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- Handle early data right - no hiding of poor calculations with NaN values (unless explicitly requested), data is as valid as mathematically possible from the first value
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- Preservation of time-value integrity of each data throughout the calculation chain (each data point has a timestamp)
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- Usage of events - each data series is an event publisher, each indicator is a subscriber - this allows seamless data flow between indicators without the need of plumbing (see [MACD example](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/macd_example.ipynb) to understand how events allow chaining of indicators)
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QuanTAlib does not provide OHLCV quotes - but it can easily connect to any data feeds. There are some data feed classess
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available (**RND_Feed** for random OHLCV, **YAHOO_Feed** for Yahoo Finance daily stock data)
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See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/getting_started.ipynb) .NET interactive notebook to get a feel how library works. Developers can use QuanTAlib in .NET interactive or in console apps, but the best
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usage of the library is withing C#-enabled trading platforms - see **QuanTower_Charts** folder for Quantower examples.
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[**List of available and planned indicators**](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/coverage.md). **So. Much. To. Do...**
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# QuanTAlib - quantitative technical indicators for Quantower and other C#-based trading platorms
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[](https://sonarcloud.io/summary/overall?id=mihakralj_QuanTAlib)
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[](https://app.codacy.com/gh/mihakralj/QuanTAlib/dashboard)
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[](https://codecov.io/gh/mihakralj/QuanTAlib)
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[](https://sonarcloud.io/summary/new_code?id=mihakralj_QuanTAlib)
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[](https://www.codefactor.io/repository/github/mihakralj/quantalib/overview/main)
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[](https://www.nuget.org/packages/QuanTAlib/)
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[](https://www.nuget.org/packages/QuanTAlib/)
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[](https://github.com/mihakralj/QuanTAlib/watchers)
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[
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[](Docs/LICENSE)
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Quantitative TA Library (**QuanTAlib**) is an easy-to-use C# library for quantitative technical analysis with base algorithms, charts, signals and strategies useful for trading securities with [Quantower](https://www.quantower.com/) and other C#-based trading platforms.
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**QuanTAlib** is written with some specific design criteria in mind - this is a list of reasons why there is '_yet another C# TA library_':
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- Written in native C# - no code conversion from TA-LIB or other imported/converted TA libraries
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- No usage of Decimal datatypes, LINQ, interface abstractions, or static classes (all for performance reasons)
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- Supports both **historical data analysis** (working on bulk of historical arrays) and **real-time analysis** (adding one data item at the time without the need to re-calculate the whole history)
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- Separation of calculations (**algos**) and visualizations (**charts**)
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- Handle early data right - no hiding of poor calculations with NaN values (unless explicitly requested), data is as valid as mathematically possible from the first value
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- Preservation of time-value integrity of each data throughout the calculation chain (each data point has a timestamp)
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- Usage of events - each data series is an event publisher, each indicator is a subscriber - this allows seamless data flow between indicators without the need of plumbing (see [MACD example](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/macd_example.ipynb) to understand how events allow chaining of indicators)
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QuanTAlib does not provide OHLCV quotes - but it can easily connect to any data feeds. There are some data feed classess
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available (**RND_Feed** for random OHLCV, **YAHOO_Feed** for Yahoo Finance daily stock data)
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See [Getting Started](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/getting_started.ipynb) .NET interactive notebook to get a feel how library works. Developers can use QuanTAlib in .NET interactive or in console apps, but the best
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usage of the library is withing C#-enabled trading platforms - see **QuanTower_Charts** folder for Quantower examples.
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[**List of available and planned indicators**](https://github.com/mihakralj/QuanTAlib/blob/main/Docs/coverage.md). **So. Much. To. Do...**
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@@ -0,0 +1,35 @@
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namespace QuanTAlib;
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using System;
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/* <summary>
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ZL: Zero Lag
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Data is de-lagged by removing the data from “lag” days ago, thus removing
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(or attempting to) the cumulative effect of the moving average.
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Calculation:
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Lag = (Period-1)/2
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ZL = Data + (Data - Data(Lag days ago) )
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Sources:
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https://mudrex.com/blog/zero-lag-ema-trading-strategy/
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</summary> */
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public class ZL_Series : Single_TSeries_Indicator
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{
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public ZL_Series(TSeries source, int period, bool useNaN = false) : base(source, period:period, useNaN:useNaN) {
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if (this._data.Count > 0) { base.Add(this._data); }
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}
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public override void Add((DateTime t, double v) TValue, bool update)
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{
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int _lag = (int)((_p-1) * 0.5);
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_lag = (_data.Count-_lag < 0) ? 0 : _data.Count-_lag;
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double _zl = TValue.v + (TValue.v - _data[_lag].v);
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var ret = (TValue.t, (base.Count==0 && base._NaN) ? double.NaN : _zl );
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base.Add(ret, update);
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}
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}
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@@ -51,11 +51,14 @@
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</PropertyGroup>
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<PropertyGroup>
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<PackageIcon>images\icon.png</PackageIcon>
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<PackageIcon>QuanTAlib2.png</PackageIcon>
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<PackageIconUrl>https://raw.githubusercontent.com/mihakralj/QuanTAlib/main/.github/QuanTAlib2.png</PackageIconUrl>
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<SignAssembly>False</SignAssembly>
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<AssemblyOriginatorKeyFile>C:\Dropbox\SSH keys\Certum\MihaKralj_OpenSource.pem</AssemblyOriginatorKeyFile>
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<DelaySign>True</DelaySign>
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</PropertyGroup>
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<ItemGroup>
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<None Include="..\.github\QuanTAlib2.png" Pack="true" Visible="false" PackagePath="images\icon.png" />
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<None Include="..\.github\QuanTAlib2.png" Pack="true" Visible="false" PackagePath="\" />
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</ItemGroup>
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<ItemGroup>
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