Computational Investing, Part I

Computational Investing, Part I

МООК
en
Английский
96 h
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Source
  • From www.coursera.org
Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 8 Sequences
  • Introductive Level

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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

Le Georgia Institute of Technology, connu aussi sous le nom de Georgia Tech ou GT, est une université de recherche mixte publique, et située à Atlanta (Géorgie), aux États-Unis. Elle fait partie du réseau plus large du Système universitaire de Géorgie (en anglais, University System of Georgia). Georgia Tech possède des antennes à Savannah (Géorgie, États-Unis), Metz (France), Athlone (Irlande), Shanghai (Chine), et Singapour.

Georgia Tech a acquis sa réputation grâce à ses programmes d'ingénierie et d'informatique, ceux-ci figurant parmi les meilleurs du monde5,6. L'offre de formation est complétée par des programmes dans les domaines des sciences, de l'architecture, des sciences humaines et du management.

Platform

Coursera - это цифровая компания, предлагающая массовые открытые онлайн-курсы, основанные учителями компьютеров Эндрю Нгом и Стэнфордским университетом Дафни Коллер, расположенные в Маунтин-Вью, штат Калифорния.

Coursera работает с ведущими университетами и организациями, чтобы сделать некоторые из своих курсов доступными в Интернете, и предлагает курсы по многим предметам, включая: физику, инженерию, гуманитарные науки, медицину, биологию, социальные науки, математику, бизнес, информатику, цифровой маркетинг, науку о данных и другие предметы.

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