专栏名称: 机器学习研究会

机器学习研究会是北京大学大数据与机器学习创新中心旗下的学生组织，旨在构建一个机器学习从事者交流的平台。除了及时分享领域资讯外，协会还会举办各种业界巨头/学术神牛讲座、学术大牛沙龙分享会、real data 创新竞赛等活动。

【学习】金融Python：算法交易

机器学习研究会 · 公众号 · AI · 2017-06-04 19:32

正文

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摘要

转自：网路冷眼

技术已经成为金融的一个财富：金融机构现在正在发展成为技术公司，而不仅仅是在金融方面的财产：除了技术带来创新速度，有助于获得竞争优势的事实，高速和高频的金融交易以及大量数据，使金融机构对技术的关注多年来一直在增加，而且技术事实上已成为金融的主要推动者。

在金融最热门的编程语言中，您会发现R和Python以及C ++，C#和Java等语言。在本教程中，您将了解如何开始使用Python进行金融计算。

Technology has become an asset in finance: financial institutions are now evolving to technology companies rather than just staying occupied with just the financial aspect: besides the fact that technology brings about innovation the speeds and can help to gain a competitive advantage, the speed and frequency of financial transactions, together with the large data volumes, makes that financial institutions’ attention for technology has increased over the years and that technology has indeed become a main enabler in finance.

Among the hottest programming languages for finance, you’ll find R and Python, alongside languages such as C++, C# and Java. In this tutorial, you’ll learn how to get started with Python for finance. The tutorial will cover the following:

The basics that you need to get started: for those who are new to finance, you’ll first learn more about the stocks and trading strategies, what time series data is and what you need to set up your workspace.
An introduction to time series data and some of the most common financial analyses, such as moving windows, volatility calculation, … with the Python package Pandas.
The development of a simple momentum strategy: you’ll first go through the development process step-by-step and start off by formulating and coding up a simple algorithmic trading strategy.
Next, you’ll backtest the formulated trading strategy with Pandas, zipline and Quantopian.
Afterwards, you’ll see how you can do optimizations to your strategy to make it perform better and you’ll eventually evaluate your strategy’s performance and robustness.