November 2022
Intermediate to advanced
392 pages
10h 8m
Chinese
Content preview from Python算法交易
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Python
和算法交易
｜
17
实现类和模块，这些类和模块将让任何算法交易项目更加高效。不过，整个过程中
使用的主要软件包是
NumPy
和
pandas
。
图 1-1：从 2013 年初到 2020 年中的美元计价的历史比特币汇率
NumPy
提供了基本的数据结构来存储数值数据并使用它，而
pandas
则
带来了强大的时间序列管理功能。同时
pandas
很好地将其他程序包的
功能包装成了易于使用的
API
。从刚刚描述的比特币示例可以看到，
对
DataFrame
对象的单个方法调用已经足以生成两种金融时间序列数据
的可视化图形。像
NumPy
一样，由于在后台大量使用了编译后的代码，
pandas
可以让即使是相当简洁的矢量化代码也能运行得非常快。
1.2
算法交易
算法交易这个术语没有一个唯一的或是普遍的定义。基本上来说，它指的是基于某
种形式算法进行金融工具交易。算法是按一定顺序为了实现特定目标而进行的一组
操作（数学和技术上的）。例如，存在一些数学算法可以解决魔方的问题。
注
4
这种
注 4： 参见 The Mathematics of the Rubik
’
s Cube （
https://oreil.ly/16pIA
）或 Algorithms for
Solving Rubik
’
s Cube（
https://oreil.ly/XM0ZP
）。
18
｜
第
1
章
算法通常可以完美地通过一步一步地过程来解决手头的问题。另一个例子是如果一
个方程存在根的话，找到这个根的算法。从这个意义上讲，数学算法的目标通常是
明确规定的，并且通常期望得到一个最优解。 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.