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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/using-r-for-regression-and-machine-learning-in-investment
课程评论：没有评论
课程名称: 使用R进行投资中的回归与机器学习 课程概述: 在本课程中，讲师将讨论回归在投资问题中的多种用途，并将讨论扩展到逻辑回归、Lasso回归和Ridge回归。同时，讲师还将介绍机器学习的各种概念。您可以将此课程视为应用机器学习方法解决投资问题的第一步。课程将涵盖投资分析主题，并通过R编程进行实践。课程的重点是培训您使用各种回归方法进行投资管理，这是您日常工作中可能需要的技能，并为您准备更高级的机器学习主题。 本课程设定了一个前提，即大多数学生已经具备一定的金融经济学和R编程知识。学生们应当了解股票、债券、资产负债表、收益等基本概念，并具备初级统计知识，如均值、中位数、分布、回归等。此外，学生们应当知道讲师的第一门课程《数据驱动投资的基础》。 讲师将详细解释R编程。该课程将是提升您编程技能的绝佳机会，但您必须具备R的基础知识。如果您在R编程方面非常熟练，那么这将为您提供以金融和投资示例再次实践的优秀机会。 课程大纲： 第一部分: 理解算法驱动的投资决策过程及回归方法的回顾 描述: 理解预测模型的特性和投资中的各种数据。 第二部分: 回归及其延伸 描述: 利用回归方法进行各种投资分析目的，通过使用Ridge回归、Lasso回归和逻辑回归改进模型。首先，您将学习如何通过回测来评估投资策略。
Part: 1
Title:Understanding the big picture of the algorithm-driven investment decision-making process using machine learning and review of regression methodology
Description:Understand the characteristics of predictive models and various data in investment
Part: 2
Title:Regression and beyond
Description:Use regression methodology for various investment analysis purpose and improve models by using ridge, lasso, and logistic regression. First of all, you will learn how you can gauge investment strategy using backtesting.
In this course, the instructor will discuss various uses of regression in investment problems, and she will extend the discussion to logistic, Lasso, and Ridge regressions. At the same time, the instructor will introduce various concepts of machine learning. You can consider this course as the first step toward using machine learning methodologies in solving investment problems. The course will cover investment analysis topics, but at the same time, make you practice it using R programming. This course's focus is to train you to use various regression methodologies for investment management that you might need to do in your job every day and make you ready for more advanced topics in machine learning. The course is designed with the assumption that most students already have a little bit of knowledge in financial economics and R programming. Students are expected to have heard about stocks and bonds and balance sheets, earnings, etc., and know the introductory statistics level, such as mean, median, distribution, regression, etc. Students are also expected to know of the instructors' 1st course, 'Fundamental of data-driven investment.' The instructor will explain the detail of R programming. It will be an excellent course for you to improve your programming skills but you must have basic knowledge in R. If you are very good at R programming, it will provide you with an excellent opportunity to practice again with finance and investment examples.
