Principles of Valuation: Risk and Return

Principles of Valuation: Risk and Return

课程
en
英语
60 时
此内容评级为 0/5
来源
  • 来自www.coursera.org
状况
  • 自定进度
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更多信息
  • 6 序列
  • 等级 中级

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课程详情

教学大纲

  • Week 1 - Overview of Specialization & Course
    This module contains detailed videos and syllabi of both the Specialization and this course. This specialization has been designed to enable you to learn and apply the powerful tools of modern finance to both personal and professional situations. The courses w...
  • Week 1 - Module 1
    Risk and return is best understood in a real context; we will therefore spend the first module on understanding the most common vehicle of investment: bonds.
  • Week 2 - Module 2
    This second module will be spent understanding the features and valuation of stocks.
  • Week 3 - Module 3
    In this module, we will develop a theory of risk based on the intuitive concept of diversification. Since knowledge of Statistics is key to understanding risk, we will introduce some important concepts of applications.
  • Week 4 - Module 4
    In this module, we will introduce one of the most widely known models called CAPM (Capital Asset Pricing Model), which provides a simple and powerful relation between risk and return.
  • Week 5 - Module 5
    This week will be spent on a short wrap video of the course and time for assimilation and review by learners to be prepared to take the final exams. In the past, learners have really valued this time and hence it is built into this on-demand structure as well.
  • Week 6 - Module 6
    This is finals week. Please note that there are two exams and you need to attempt both.

先决条件

没有。

讲师

Gautam Kaul
Professor of Finance & Fred M. Taylor Professor of Business Administration
Ross School of Business

编辑

密歇根大学(UM,UMich 或简称密歇根)是一所公立研究型大学,位于美国密歇根州安阿伯市。该大学成立于 1817 年,是密歇根州历史最悠久、规模最大的大学。

密歇根大学的使命是为密歇根州和全世界人民服务,在创造、交流、保存和应用学术知识、艺术和价值观方面发挥领导作用,培养挑战现在和丰富未来的领导者和公民。

平台

Coursera是一家数字公司,提供由位于加利福尼亚州山景城的计算机教师Andrew Ng和达芙妮科勒斯坦福大学创建的大型开放式在线课程。

Coursera与顶尖大学和组织合作,在线提供一些课程,并提供许多科目的课程,包括:物理,工程,人文,医学,生物学,社会科学,数学,商业,计算机科学,数字营销,数据科学 和其他科目。

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