Big data junior high school learns how to build a quantitative trading environment and solve problems.
Big data junior high school learns how to build a quantitative trading environment and how to solve the problem. in view of this problem, this article introduces the corresponding analysis and solutions in detail. I hope it can help more partners who want to solve this problem to find a more simple and feasible method.
Preface
At present, the version of Python has reached 3.8.5, but in actual development, there are not too many users, or many packages and plug-ins do not support it. (I java ape) at present, I am a quantitative beginner, and I don't know much about python ecology. The whole process depends on the ability of the hand-stretching party to play monster and upgrade in the sea of search engines, and the sadness of the upgrade is recorded here today.
Basics
Python3.6 (don't choose too high, I used 3.8.5 from the beginning, basically the same reason as using java14)
PyCharm (coding tool)
Anaconda3 (management tools for packages and their dependencies and environments)
Install Python
Tutorial address: portal
PyCharm installation
This is weird, you have to fight by yourself. Can also choose other strange, do not force.
Anaconda3
Introduction: management tools for packages and their dependencies and environments
Information:
Anaconda official website: https://www.anaconda.com/
Miniconda official website: https://docs.conda.io/en/latest/miniconda.html
Foreign Studies University: https://mirrors.bfsu.edu.cn/help/anaconda/
Https://mirror.tuna.tsinghua.edu.cn/help/anaconda/ of Tsinghua University
Create a quantitative configuration environment Anaconda3 create an environment
Open Anaconda3 Prompt
Create a pydev environment: conda create-n pydev python=3.6
Activate the pydev environment: conda activate pydev
View the existing environment: conda env list
Delete the existing environment: conda romove-n pydev-- all
One of the three oddities of zipline quantification
Introduction: zipline is the transaction library of pythonic algorithm. It is an event-driven backtest system.
Official website address: portal
1. Open Anaconda3 Prompt
2. Conda install-c Quantopian zipline
3. [2] exception. You can choose to install it manually. Open: https://www.lfd.uci.edu/~gohlke/pythonlibs/#zipline
4. Find the corresponding file at the beginning of Zipline to download (download cp36 for python3.6)
5. Absolute path where the pip install file is located + file name
6. Check to see if the command was successfully installed and run: zipline
7. Possible version problem: numexpr is too low (figure 1 below)
8. Upgrade with specified version number: pip install-U numexpr==2.6.2
9. Success is shown in figure 2
Figure 1:
Figure 2:
One of the three oddities of Talib quantification
Introduction: TaLib is a Python financial index processing library. Contains a lot of commonly used parameters in technical analysis.
Official website address: portal
1. Open Anaconda3 Prompt
2. Pip install Ta-Lib
3. [2] exception. You can choose to install it manually. Open: https://www.lfd.uci.edu/~gohlke/pythonlibs/#Ta-Lib
4. Find the corresponding file at the beginning of TA_Lib to download (download cp36 for python3.6)
5. Absolute path where the pip install file is located + file name
One of the three oddities of Pandas quantification
Summary: Pandas incorporates a large number of libraries and some standard data models, providing the tools you need to manipulate large datasets efficiently.
Official website address: portal
1. Open Anaconda3 Prompt
2. Pip install Pandas
3. [2] exception. You can choose to install it manually. Open: https://www.lfd.uci.edu/~gohlke/pythonlibs/#Pandas
4. Find the corresponding file at the beginning of TA_Lib to download (download cp36 for python3.6)
5. Absolute path where the pip install file is located + file name
The answer to the question about big data's beginner quantitative trading environment construction and problem solving is shared here. I hope the above content can be of some help to everyone, if you still have a lot of doubts to be solved. You can follow the industry information channel for more related knowledge.
