课程大纲
介绍
演算法交易核心概念
- 什么是演算法交易?
- 市场和交易
- 文本数据和分析
Python、R 和 Stata
- 股票交易
- 债券交易
- Investment 分析
准备开发环境
- 安装 Quandl
- 安装 quantmod
- 安装和设定 Stata
演算法交易和 Python
- 汇入数据
- 使用 Quandl
- 处理财务数据
- 为财务数据创建资料库
演算法交易和 R
- 汇入数据
- 使用 quantmod
- 使用回归
演算法交易和 Stata
- 汇入和清理数据
- 测试策略
- 使用回归
总结和结论
要求
- 使用 R 的经验
- Python 经验
观众
- Business 分析师
客户评论 (5)
使用与我们在项目中使用的数据(光栅格式的卫星图像)更相似的数据进行更多实践练习的事实
Matthieu - CS Group
课程 - Scaling Data Analysis with Python and Dask
机器翻译
Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)
Monika - Procter & Gamble Polska Sp. z o.o.
课程 - Developing APIs with Python and FastAPI
It was a though course as we had to cover a lot in a short time frame. Our trainer knew a lot about the subject and delivered the content to address our requirements. It was lots of content to learn but our trainer was helpful and encouraging. He answered all our questions with good detail and we feel that we learned a lot. Exercises were well prepared and tasks were tailored accordingly to our needs. I enjoyed this course
Bozena Stansfield - New College Durham
课程 - Build REST APIs with Python and Flask
Trainer develops training based on participant's pace
Farris Chua
课程 - Data Analysis in Python using Pandas and Numpy
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.