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
｜
25
1.5.3
均值回归
在均值回归策略中，假设金融工具当前已远离某个平均水平或趋势水平，则该金融
工具会恢复到该水平。例如，假设某股票在其
200
天
SMA
水平为
100
的情况下交
易
10
美元，那么，预计股价很快就会恢复到其
SMA
水平。
1.5.4
机器学习和深度学习
借助机器学习和深度学习算法，通常可以采用更黑盒的方法来预测市场动向。为了
简化和方便重现，本书中的示例主要依赖于历史收益观察作为训练机器学习和深度
学习算法来预测股市走势的特征。
本书没有系统地介绍算法交易。由于重点在于在这个引人入胜的领域中
应用
Python
，因此不熟悉算法交易的读者应咨询该主题的专用资源，本
章及其后各章中引用了其中的一些内容。但是请注意以下事实：算法交
易世界总体上是秘密的，几乎每个成功的人自然都不愿分享自己的秘密，
以保护他们的成功之源（即他们的投资收益）。
1.6
小结
总体而言，
Python
已经应用在金融领域里了，并且正逐渐成为算法交易的主力军。
使用
Python
进行算法交易有很多充分的理由，其中包括强大的软件包生态系统，可
以进行有效的数据分析或现代
API
的处理。学习
Python
进行算法交易还有很多充分
的理由，其中一个重要的事实是，一些最大的买方和卖方机构在交易操作中大量使
用
Python
，并不断寻找经验丰富的
Python
专业人士。
本书着重于将
Python
应用于算法交易的不同学科，例如回测交易策略或与在线交易
平台的交互。总的来说，它并不能代替对
Python
本身和交易的全面介绍。但是，它
系统地结合了这两个引人入胜的领域，为当今竞争激烈的金融和加密货币市场中的 ...
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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.