TA-Lib : Technical Analysis Library

[mimtek]

Using DLL instead of interpreted code allows you to significantly speed up the process of optimization and testing of systems and

not to rewrite codes of functions and systems for different technical analysis programs, and use existing DLLs in all programs that can call external DLLs.

 

Tell me where can I find the source code for the functions of technical analysis in C ++, Delphi, VB, as well as DLLs and examples of writing DLL with these functions?

Under the functions of technical analysis, I mean the functions that are used to analyze time series. For example, parabolic, linear regression, various types of moving averages, RSI, stochastics, finding local extrema, momentum, statistical functions, and so on.

 

 

Multi-Platform Tools for Market Analysis ...

TA-Lib is widely used by trading software developers requiring to perform technical analysis of financial market data.

Includes 200 indicators such as ADX, MACD, RSI, Stochastic, Bollinger Bands etc... (more info)

Candlestick pattern recognition

Open-source API for C/C++, Java, Perl, Python and 100% Managed .NET

Free Open-Source Library

TA-Lib is available under a BSD License allowing it to be integrated in your own open-source or commercial application. (more info)

 

http://www.ta-lib.org/index.html

 

various indicator codes and library suggestions C/C++, Java, Perl, Python .dll net java matlab vs ?

Edited December 10, 2017 by mimtek

[mimtek]

ALGLIB is a cross-platform numerical analysis and data processing library. It supports several programming languages (C++, C#, Delphi) and several operating systems (Windows and POSIX, including Linux). ALGLIB features include:

 

Data analysis (classification/regression, statistics)

Optimization and nonlinear solvers

Interpolation and linear/nonlinear least-squares fitting

Linear algebra (direct algorithms, EVD/SVD), direct and iterative linear solvers

Fast Fourier Transform and many other algorithms

 

ALGLIB Commercial Edition pls help shr

http://www.alglib.net/

[mimtek]

IMSL Numerical Libraries

Battle-tested algorithms from prototype to production

Analyzing data has never been more important — or harder. Getting actionable information from your large and disparate datasets can often determine if your organization meets its goals. Create competitive differentiation and unlock innovation by using the most trusted, tested, and reliable algorithms available. Backed by a team of mathematicians and statisticians, IMSL® Numerical Libraries allow you to address complex problems quickly with a variety of readily-available algorithms. With IMSL you get consistency from prototype to production.

 

C / C++ Numerical Library pls help shr

[mimtek]

but did not you see the full version of this library

www.timeseriesapi.com/ pls help shr

 

Order

QTStalker - http://sourceforge.net/projects/qtstalker

GStalker - http://sourceforge.net/project/?group_id=1001

GeniusTrader - http://www.geniustrader.org/

Market Analysis System - http://eiffel-mas.sourceforge.net/

MaWaTT Trading Toolkit - http://mawatt.berlios.de/

Merchant of Venice - http://mov.sourceforge.net/

XTrader - http://xtrader.sourceforge.net/

Lidgren technical stock analyzer - http://ltsa.sourceforge.net/

ProfitPY - http://profitpy.sourceforge.net/

Robotrader - http://jrobotrader.atspace.com/

Edited December 10, 2017 by mimtek

[mimtek]

Intel® Math Kernel Library (Intel® MKL) optimizes code with minimal effort for future generations of Intel® processors. It is compatible with your choice of compilers, languages, operating systems, and linking and threading models.

Features highly optimized, threaded, and vectorized math functions that maximize performance on each processor family

Uses industry-standard C and Fortran APIs for compatibility with popular BLAS, LAPACK, and FFTW functions—no code changes required

Dispatches optimized code for each processor automatically without the need to branch code

Provides Priority Support that connects you directly to Intel engineers for confidential answers to technical questions

https://software.intel.com/en-us/mkl

[iDov]

Native Python Indicators:

https://github.com/kylejusticemagnuson/pyti

 

Accumulation/Distribution

Aroon

-Aroon Up

-Aroon Down

Average Directional Index

Average True Range

Average True Range Percent

Bollinger Bands

-Upper Bollinger Band

-Middle Bollinger Band

-Lower Bollinger Band

-Bandwidth

-Percent Bandwidth

-Range

-%B

Chaikin Money Flow

Chande Momentum Oscillator

Commodity Channel Index

Detrended Price Oscillator

Double Exponential Moving Average

Double Smoothed Stochastic

Exponential Moving Average

Hull Moving Average

Ichimoku Cloud

-TenkanSen

-KijunSen

-Chiku Span

-Senkou A

-Senkou B

Keltner Bands

-Bandwidth

-Center Band

-Upper Band

-Lower Band

Linear Weighted Moving Average

Momentum

Money Flow

Money Flow Index

Moving Average Convergence Divergence

Moving Average Envelope

-Upper Band

-Center Band

-Lower Band

Negative Directional Index (-DI)

Negative Directional Movement (-DM)

On Balance Volume

Positive Directional Index (+DI)

Positive Directional Movement (+DM)

Price Channels

-Upper Price Channel

-Lower Price Channel

Price Oscillator

Simple Moving Average

Smoothed Moving Average

Standard Deviation

Standard Variance

Stochastic

-%K

-%D

StochRSI

Rate of Change

Relative Strength Index

Triangular Moving Average

Triple Exponential Moving Average

True Range

Typical Price

Ultimate Oscillator

Vertical Horizontal Filter

Volatility

Volume Adjusted Moving Average

Volume Index

-Positive Volume Index

-Negative Volume Index

Volume Oscillator

Weighted Moving Average

Williams %R