Build a desktop algorithm transaction research environment using Python in Ubuntu

This article will discuss how to use the Python programming language in Ubuntu to build a powerful, efficient, and interactive algorithm trading policy research environment. Our subsequent algorithm transaction articles will use this environment.

To build this environment, you must install the following software, which are both open-source and free to download:

• Oracle VirtualBox-for Virtual Operating Systems
• Ubuntu Desktop Linux-as our Virtual Operating System
• Python-core programming environment
• NumPy/SciPy-fast and efficient array and matrix operations
• IPython-Visual Interactive Development for Python
• Matplotlib-graphical visualization for Data
• Pandas-used for data "Conflict" and time series analysis
• Scikit-learn-used for machine learning and AI Algorithms

These tools (combined with the appropriate securities master database) will enable us to create a fast and interactive policy research environment. Pandas is designed for data "Conflict" and can efficiently import and clean time series data. NumPy/SciPy runs at the underlying layer, making the system well optimized. IPython/matplotlib (and qtconsole, see the following section) to visualize the interaction and fast iteration of the results. Scikit-learn allows us to apply machine learning technology to our policies to further improve performance.

Please note that I am writing this tutorial to build this environment for windows or Mac OSX users who cannot or are unwilling to directly install ubuntu through VirtualBox. VirtualBox allows us to create a virtual machine in the master operating system to simulate the guest operating system without affecting the master operating system. Therefore, we can practice the Ubuntu and Python tools before installing Ubuntu. If you have already installed the Ubuntu Desktop System, go to the "Install Python research environment package under Ubuntu" section.

Install VirtualBoX and Ubuntu Linux

The VirtualBox installation section on the Mac OSX operating system has been written. Here we will simply move it to the Windows environment. Once the VirtualBox of various master operating systems is installed, other processes will be the same.

Before installation, We need to download Ubuntu and VirtualBox.

Download Ubuntu Desktop disk image

Open a Web browser, navigate to the Ubuntu Desktop homepage, and select Ubuntu 13.04:

Download Ubuntu13.04 (64-bit (if applicable ))

You will be asked if you are willing to donate some money, but this is optional. Go to the download page and select Ubuntu 13.04. You need to select whether to download the 32-bit or 64-bit version. It is very likely that you are a 64-bit system, but if you have any questions, select 32-bit. On Mac OSX, the Ubuntu Desktop ISO disk image is saved to the Downloads directory. We will use VirtualBox after it is installed.

Download and install VirtualBox

Now that we have downloaded Ubuntu, we need to obtain the VirtualBox software of the latest version of Oracle. Click here to access the website and select the version of your specific host (Mac OSX version is required in this tutorial)

Oracle VirtualBox Download Page

Once the file is downloaded, click the installation package icon to run it (Windows may be a little different, but similar ):

Double-click the installation package icon to install VirtualBox

For more details, please continue to read the highlights on the next page:

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Python details: click here
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