Computational Investing, Part I

Name: Computational Investing, Part I
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Author: Georgia Institute of Technology

课程

英语

96 时

来源

来自www.coursera.org

状况

自定进度
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8 序列
等级介绍

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课程详情

教学大纲

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.

先决条件

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讲师

Dr. Tucker Balch
Associate Professor
School of Interactive Computing

编辑

佐治亚理工学院（Georgia Institute of Technology），又称佐治亚理工学院或 GT，是一所位于美国佐治亚州亚特兰大市的男女同校公立研究型大学。它是佐治亚大学系统网络的一部分。佐治亚理工学院在萨凡纳（美国佐治亚州）、梅斯（法国）、阿斯隆（爱尔兰）、上海（中国）和新加坡设有办事处。

佐治亚理工学院的工程和计算机科学课程在世界上名列前茅5,6 ，声誉卓著。此外，佐治亚理工学院还开设了科学、建筑、人文和管理课程。