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This article introduces the relevant knowledge of "what are the advantages and disadvantages of R, Python, MATLAB and Octave". In the operation of actual cases, many people will encounter such a dilemma, so let the editor lead you to learn how to deal with these situations. I hope you can read it carefully and be able to achieve something!

R language

R is a language and environment for statistical calculations and diagrams. It is a GNU project, similar to the S language and environment developed by John Chambers of Bell Labs and his colleagues. R can be regarded as a different implementation of S. There are some important differences between the two, but much of the code written in S does not need to be modified when running under R. More about machine learning

Advantages:

End-to-end development to execution (some brokers package allow execution, IB)

Fast development (60% less code than Python)

There are many open source packages

Mature quantitative transaction packages (quantstrat, quantmod, performanceanalyitics, xts)

The largest community

Using rcpp, you can integrate R and CZG.

Disadvantages:

Slower than Python, especially in iterative loops and non-vectorized functions

Worse than Matlab drawing, it is difficult to realize interactive chart.

Limited ability to create stand-alone applications more machine learning related content

Python

Python is an interpretive high-level programming language for general programming, created by Guido van Rossum and first released in 1991. Python is designed to emphasize the readability of the code, using a large number of spaces. Its structure makes it clear in both large-scale and small-scale programming.

Advantages:

End-to-end development to execution (some brokers package allow execution, IB)

Open source packages (Pandas, Numpy, scipy)

Deal package (zipline, pybacktest, pyalgotrade)

Most suitable for general programming and application development

A "glue" language that connects R, C++ and other languages

The overall speed is the fastest, especially in iterative loops

More about machine learning

Disadvantages:

There are some immature bags, especially trading bags.

Some packages are incompatible with or contain overlap with other packages

The community in the financial field is smaller than R

The same operation requires more code than R or Matlab

Tracking silent errors (silent error) can take a long time (even using a visual debugger / IDE)

MATLAB

MATLAB (matrix laboratory) is a multi-norm numerical computing environment. As a specialized programming language developed by MathWorks, MATLAB allows matrix operations, function and data mapping, algorithm implementation, user interface creation, and interaction with programs written in other languages, including C, C++, C #, Java, Fortran, Python.

Although MATLAB was originally designed for numerical computation, the optional toolkit uses MuPAD symbolic engine and has symbolic computing capabilities. The additional package Simulink adds graphical multidomain simulation and model-based design for dynamic and embedded systems.

Advantages:

The fastest mathematical and computing platform, especially vector operations / linear matrix algebra.

Suitable for commercial-grade software in all areas of mathematics and trading.

The script is short, but highly integrated with all packages.

Have the best visualization of diagrams and interactive charts

Have good testing and support.

Easy to manage multithreading support and garbage collection

The best debugger

Disadvantages:

More about machine learning

Cannot be executed and must be converted to another language.

Expensive: about $1000 per license, and an additional $50 + for each additional package.

Cannot integrate well with other languages.

It is difficult to detect deviations in the trading system (which is built for mathematical and engineering simulations), so extensive testing may be required.

Poor iterative loop performance.

Unable to develop separate applications.

Octave

Octave can be seen as the GNU version of the business language MATLAB, a scripting matrix language (scripting matrix language) whose syntax is about 95% compatible with MATLAB. Octave is designed by engineers, so it is preloaded with programs commonly used by engineers, many of which are the same as MATLAB language for time series analysis, statistics, file commands, and drawing commands.

Advantages:

First of all, there is currently no robust Octave compiler available, and it is not necessary because the software can be installed for free.

Octave and Matlab have the same language elements, except for a few cases, such as nested functions. Octave is still in a state of active development, and every deviation from Matlab syntax is considered a bug or at least an unsolved problem.

Octave has many toolkits available, and as long as the program does not require diagram output, running with Octave is about the same as running with Matlab without making a lot of changes.

Graphical capabilities are an advantage of Matlab. The latest version of Matlab includes the GUI designer, which contains a number of great visualization features.

Octave uses GNU Plot or JHandles as the diagram package, and JHandles is closer to the diagram package in Matlab. However, Octave does not have components similar to GUI designers, and its visualization mechanism is limited and not compatible with Matlab.

The same is true for the integrated development environment: Octave has a QTOctave project, but it is still in its early stages.

The collaboration of the Octave community is likely to help the software provide better, more compatible graphics and GUI capabilities soon.

Disadvantages:

It is only a free and open source version of MATLAB and cannot bring anything new to users.

This is the end of the introduction of "what are the advantages and disadvantages of R, Python, MATLAB and Octave". Thank you for reading. If you want to know more about the industry, you can follow the website, the editor will output more high-quality practical articles for you!

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