Developing Trading Robots

A very modern programming language used by more and more quantitative trading firms is R. It actually proves the opportunity to work and display very interesting concepts for traders and investors.


It is possible to do own calculations according to personal wishes and preferences. It is also possible to scale, analyse and calculate data with a lot of information and then send signals to the broker. In between there can be specific trading models for performance, risk and modeling.


There are some packages (there are more than 30.000 pre developed packages for this programming language R) even for daily trading (day-trading, per se similar to high frequency trading), when decision makers want to make their allocation decision daily on an more advanced basis, rather than a simple buy and hold strategy.


Check this out:


https://cran.r-project.org/web/packages/highfrequency/highfrequency.pdf


Description Provide functionality to manage, clean and match highfrequency trades and quotes data, calculate various liquidity measures, estimate and forecast volatility, detect price jumps and investigate microstructure noise and intraday periodicity.


https://github.com/algoquant/HighFreq


Package ‘TTR’ allows almost all typical indicator variations in broker platforms available, only that if you can do R, you can make customized solutions and fine tune it.

September 1, 2020 Type Package Title Technical Trading Rules Version 0.24.2 Author of this package: Joshua Ulrich Suggests

Description A collection of over 50 technical indicators for creating technical trading rules. The pack- age also provides fast implementations of common rolling-window functions, and several volatility calculations. URL https://github.com/joshuaulrich/TTR


ATR; ADX over Volatility, TRIX, Moving Averages ect. all possible within this environment.

Ansonsten ist das TTR Package ganz nützlich für technische Signale, PerformanceAnalytics für alle Art von Performancerechnung.


Erwähnenswert sind auch quanttools und quantstrat:


https://quanttools.bitbucket.io/_site/index.html

Enhanced Quantitative Trading Modelling

QuantTools is all in one R package designed to enhance quantitative trading modelling. It allows you to download and organize historical market data from multiple sources like Yahoo, Google Finam and IQFeed. Code your trading algorithms in modern c++11 with powerful event driven tick processing API including trading costs and exchange communication latency and transform detailed data seamlessly into R. In just few lines of code you will be able to visualize every step of your trading model from tick data to multi dimensional heat maps.




Transaction-oriented infrastructure for constructing trading systems and simulation. https://github.com/braverock/quantstrat


Provides support for multi-asset class and multi-currency portfolios for backtesting and other financial research.



Overview

quantstrat provides a generic infrastructure to model and backtest signal-based quantitative strategies. It is a high-level abstraction layer (built on xts, FinancialInstrument, blotter, etc.) that allows you to build and test strategies in very few lines of code. quantstrat is still under heavy development but is being used every day on real portfolios. We encourage you to send contributions and test cases via the appropriate GitHub mediums (Pull requests and Issue tracker).


Mit Yahoo Daten kann man sich mit der API die Kursdaten der börsengelisteten Wertpapier in die Software Entwicklungsumgebung einladen.

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