代码计算部分主要参考Fábio Neves的文章，你可以在他的文章中找到一些细节性的解释(https://towardsdatascience.com/python-markowitz-optimization-b5e1623060f5), 我在此基础之上增加了对雅虎财经API的调用，可以直接使用股票代码计算。Weighs我用的是狄利克雷分布来生成权重而不是默认的均匀分布，这样可以权重之和为1。
The calculation part of the code is mainly based on Fábio Neves' article, where you can find more detailed explanations: (https://towardsdatascience.com/python-markowitz-optimization-b5e1623060f5), to which I added a integrate the Yahoo Finance API, allowing the calculation to be done directly using the stock codes. For weighs I have used the Dirichlet distribution to generate the weights instead of the default uniform distribution so that the sum of the weights is 1.
在项目文件夹中，使用以下命令安装依赖：
In the project folder, install the dependencies using the following command:
pip install -r requirements.txt
- 在portfolio.py中设置以下参数
In the code file portfolio.py, set the following parameters:
- 数据起始日期 / Data start date （start_date）
- 数据结束日期 / Data end date（end_date）
- 股票代码数组 / Stock code array（data_array）
- 在命令行中，执行以下命令运行代码
In the command line, run the code with the following command:：
python portfolio.py
- 修改起始时间
start_date和end_date。需要注意有些公司上市时间可能比较迟，例如B站是在2018年上市，如果你的开始时间是从2015年开始，那么结果可能会不准确。
Modify the start and end dates, start_date and end_date. Please note that some companies may have been listed later, e.g., Bilibili was listed in 2018, so if your start date is 2015, the results may be inaccurate.
- 修改和添加
data_array中的资产代号，数量没有限制，这里使用的是雅虎财经的API，你可以在搜索引擎中以「公司名+雅虎财经（Yahoo Finance）」搜索对应公司代号。例如茅台是「600519.SS」，苹果是「AAPL」，腾讯是「0700.HK」。
Change or add asset codes in the data_array. There is no limit to the number of assets. This code uses the Yahoo Finance API, and you can search for the company code in search engines with "company name + Yahoo Finance". For example, Maotai is "600519.SS", Apple is "AAPL", and Tencent is "0700.HK".
- 如果运算时间过长，你可以尝试降低
sample_num的数值。
If the calculation takes too long, you can try reducing the value of sample_num.
- 计算结果仅供参考。投资有风险，入市需谨慎。
The calculation results are for reference only. Investing carries risks, and you should be cautious when entering the market.
