- From www.coursera.org
Computational Investing, Part I
Course
en
English
96 h
This content is rated 0 out of 5
- Self-paced
- Free Access
- Fee-based Certificate
- 8 Sequences
- Introductive Level
Course details
Syllabus
- Week 1 - Portfolio Management and Market Mechanics
In this module, you will understand the course content from a portfolio manager's viewpoint, the incentives for portfolio managers, types of hedge fund, and how to assess fund performance; Also, you will gain insight into market orders, the basic infrastructur... - Week 2 - Company Worth, Capital Assets Pricing Model and QSTK Software Overview
In this module, you will learn how to value a company, and an overview of the theory Capital Assets Pricing Model (CAPM), its assumptions, implications and how you can apply it in fund management. Finally, you will learn to install QSTK Software. - Week 3 - Manipulating Data in Python and QSTK
In this module, you will learn how to work with financial data, create a portfolio and optimize a portfolio using Python with Numpy library as well as QSTK and the Pandas library. - Week 4 - Efficient Markets Hypothesis and Event Studies, Portfolio Optimization and the Efficient Frontier
In this module, you will learn about information may affect equity prices and company value, understand efficient market hypothesis and how event studies work; Also, you will learn about the inputs and outputs of a portfolio optimizer, correlation and covarian... - Week 5 - Digging into Data
We will go into more detail in this module about how to read an event study. We will also talk about the differences between actual and adjusted historical price data, and how to detect and fix wrong data. - Week 6 - The Fundamental Law, CAPM for Portfolios
In this module, you will learn the fundamental law of active portfolio management. We will recap CAPM, and extend it for portfolios. Finally, we're going to look at ways that we can leverage the capital assets pricing model to manage, maybe even reduce market... - Week 7 - Information Feeds and Technical Analysis
In this module, we will dive deeper into a few examples of information feeds, and learn about technical analysis, and look at a few example technical indicators. Finally, we are going to learn about Bollinger Bands. - Week 8 - Jensen's Alpha, Back Testing and Machine Learning
In this module, we're going to learn about another measure of a fund performance called Jensen's Alpha, and dig deeper into back testing. We will also take a sneak peek at machine learning.
Prerequisite
None.
Instructors
Dr. Tucker Balch
Associate Professor
School of Interactive Computing
Editor
The Georgia Institute of Technology, also known as Georgia Tech or GT, is a co-educational public research university located in Atlanta, Georgia, USA. It is part of the wider University System of Georgia network. Georgia Tech has offices in Savannah (Georgia, USA), Metz (France), Athlone (Ireland), Shanghai (China), and Singapore.
Georgia Tech's reputation is built on its engineering and computer science programmes, which are among the best in the world5,6. The range of courses on offer is complemented by programmes in the sciences, architecture, humanities and management.
Platform
Coursera is a digital company offering massive open online course founded by computer teachers Andrew Ng and Daphne Koller Stanford University, located in Mountain View, California.
Coursera works with top universities and organizations to make some of their courses available online, and offers courses in many subjects, including: physics, engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science, digital marketing, data science, and other subjects.
This content is rated 4.5 out of 5
(no review)This content is rated 4.5 out of 5
(no review)Complete this resource to write a review