Course Information
Course Overview
Interactive Brokers (IBKR) for Algorithmic Trading & Portfolio Investing | Stock Market Analysis, ETF Trading & Theory
Welcome to the most comprehensive and complete course on (automated) Stock Trading and Equity Investing!
This course covers
Automated Stock Trading for Income Generation (Algo Trading, Day Trading & more)
Automated ETF & Equity Portfolio Investing for long-term Wealth Accumulation (passive, semi-active, and active Investing)
with Python and Interactive Brokers (IBKR).
At the end of the course, you´ll have mastered all four aspects required for long-term success:
Theory (Finance & Investing 101): What you really need to know before you trade/invest in stocks.
Data: Successful Investment and Trading Strategies are data-driven.
API Trading with Interactive Brokers: Automated Paper Trading and Live Trading with low Spreads and Commissions (no inactivity fees)
Python: The right tool that integrates Theory, Data, and API Trading. This course explains the code and covers everything you need to know in a Python Crash Course (for beginners).
Some Highlights:
Load and analyze Stock Market Data (historical prices, financial statements, ratios, valuation multiples) for thousands of stocks
Trade stocks on various exchanges and from various world regions (North America, Europe, India, Australia, etc.)
Fundamental Analysis, Equity Valuation Methods, Technical Indicators, and Optimization Techniques explained.
Trading Strategies with multiple Tickers/Instruments at once
Test and improve your skills in various Keystone Projects (new concept)
What else should you know about me and the course?
The course shows how to do things right. But equally important, it highlights the most commonly made mistakes in Trading & Investing. There is hardly any other business where beginners make so many mistakes. Why is that? A lack of skills, expertise, and experience. And: Overconfidence and overreliance on intuition. As a finance professional with an extensive academic background (MSc in Finance, CFA) my clear message is: For Trading and Investing, intuition and common sense are not your best friends. Very often, the most intuitive solution is not the correct solution!
This course is "not only" a Stock trading and Equity investing course but also an in-depth Python Course that goes beyond what you can typically see in other courses. Create hands-on Applications with Python and use it for your Trading & Investing Business!
What are you waiting for? Join now!
Thanks and looking forward to seeing you in the Course!
Course Content
- 38 section(s)
- 460 lecture(s)
- Section 1 Getting started
- Section 2 PART 1: Basics and Prerequisites
- Section 3 Equity Markets and Stock Trading/Investing
- Section 4 Installing Python and Jupyter Notebooks
- Section 5 Equity Analysis with Python (Part 1)
- Section 6 Excursus: How to avoid and debug Coding Errors (don´t skip!)
- Section 7 Equity Analysis with Python (Part 2)
- Section 8 Keystone Project - Loading Data and Stock Analysis
- Section 9 Introduction to Interactive Brokers (IKBR) and API Trading
- Section 10 Keystone Project - Algorithmic Trading with IBKR
- Section 11 Financial Data Analysis and Performance Evaluation
- Section 12 Keystone Project: Stock Performance Analysis & Comparison
- Section 13 PART 2: ETF Trading & Equity Portfolio Investing with Python and IBKR
- Section 14 How to build and analyze a Stock Index
- Section 15 ETF Investing and Index Replication / Tracking
- Section 16 Keystone Project - Creating and Implementing a customized Investment Strategy
- Section 17 Equity Portfolio Optimization and Analysis
- Section 18 Portfolio Optimization: Theory and practical Pitfalls
- Section 19 Reverse Optimization and the Black-Litterman model
- Section 20 Asset Pricing (CAPM) - Theory and practical Implications
- Section 21 Keystone Project: Portfolio Optimization, CAPM & Black-Litterman
- Section 22 PART 3: Algorithmic Stock Trading with Python and IKBR
- Section 23 Trading Strategies - Overview
- Section 24 Backtesting multiple Tickers Strategies (Momentum/Contrarian)
- Section 25 Technical Analysis with Python - Introduction
- Section 26 Stock trading with Technical Indicators - Backtesting
- Section 27 Keystone Project - Technical Trading with IBKR
- Section 28 PART 4: Advanced VIP Topics
- Section 29 Equity Valuation Concepts
- Section 30 Advanced Data Sources - EOD Historical Data
- Section 31 Data Streaming & Algorithmic Day Trading with IBKR
- Section 32 APPENDIX: Python Crash Course
- Section 33 Appendix 1: Python (& Finance) Basics
- Section 34 Appendix 2: User-defined Functions
- Section 35 Appendix 3: Numpy, Pandas, Matplotlib and Seaborn Crash Course
- Section 36 Appendix 4: Advanced Pandas Time Series Topics
- Section 37 Appendix 5: Object Oriented Programming (OOP)
- Section 38 What´s next? (outlook and additional resources)
What You’ll Learn
- Algorithmic Stock Trading with Python and the Interactive Brokers (IBKR) API, Automated ETF & Equity Portfolio Investing, Passive (ETF), Semi-Active and Active Investing, Stock Trading Strategies with multiple Tickers, Equity Portfolio Optimization, Management & Rebalancing, Backtesting and Implementation of Trading & Investment Strategies, Technical Analysis and Indicators, Equity Valuation Methods (DDM and Multiples), Fundamental Analysis, Stock Indices and Index Tracking/Replication, How to measure, benchmark & improve the Performance of your Equity Portfolio, Loading and analysing Stock Data from (free) Web Sources, API Trading with Interactive Brokers, Python Basics & Numpy, Pandas, Matplotlib, Truly Data-driven Trading and Investing, Asset-Pricing Models (CAPM), Black-Litterman Model
Skills covered in this course
Reviews
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RRafael Ángel Campos Vargas
Excelente curso para el interesando en el Trading Algorítmico. Se encuentra orientado a evitar que el estudiante no cometa toda clase de falacias y errores a los que se expone si no analiza los problemas adecuadamente. No es apropiado para principiantes y deberá complementarse con otros cursos. Sin embargo, es importante que el estudiante no pierda dinero con métodos que no sirven y que podrían funcionar en un análisis superficial. Además, debe tener la capacidad de adaptarse al mercado cambiante. Por eso, si te interesa el Trading Algorítmico deberías llevar este curso o alguno equivalente.
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OOlalekan Solomon Awoyemi
Superb, and detailed.
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KKM Lee
You really should split the code into separate lessons instead of dumping everything into one file. This is crazy, honestly.
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AAjit Bhalchandra Joshi
Happy that I chose this course