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Udemy

Algorithmic Stock Trading and Equity Investing with Python

via Udemy

Overview

Interactive Brokers (IBKR) for Algorithmic Trading & Portfolio Investing | Stock Market Analysis, ETF Trading & Theory

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

Welcome to the most comprehensive and complete course on (automated) Stock Trading and EquityInvesting!

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:

  1. Theory (Finance & Investing 101): What you really need to know before you trade/invest in stocks.

  2. Data: Successful Investment and Trading Strategies are data-driven.

  3. API Trading with Interactive Brokers: AutomatedPaper Trading and Live Trading with low Spreads and Commissions (no inactivity fees)

  4. Python: The right tool that integrates Theory, Data, and APITrading. 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!

Syllabus

  • Getting started
  • PART 1: Basics and Prerequisites
  • Equity Markets and Stock Trading/Investing
  • Installing Python and Jupyter Notebooks
  • Equity Analysis with Python (Part 1)
  • Excursus: How to avoid and debug Coding Errors (don´t skip!)
  • Equity Analysis with Python (Part 2)
  • Keystone Project - Loading Data and Stock Analysis
  • Introduction to Interactive Brokers (IKBR) and API Trading
  • Keystone Project - Algorithmic Trading with IBKR
  • Financial Data Analysis and Performance Evaluation
  • Keystone Project: Stock Performance Analysis & Comparison
  • PART 2: ETF Trading & Equity Portfolio Investing with Python and IBKR
  • How to build and analyze a Stock Index
  • ETF Investing and Index Replication / Tracking
  • Keystone Project - Creating and Implementing a customized Investment Strategy
  • Equity Portfolio Optimization and Analysis
  • Portfolio Optimization: Theory and practical Pitfalls
  • Reverse Optimization and the Black-Litterman model
  • Asset Pricing (CAPM) - Theory and practical Implications
  • Keystone Project: Portfolio Optimization, CAPM & Black-Litterman
  • PART 3: Algorithmic Stock Trading with Python and IKBR
  • Trading Strategies - Overview
  • Backtesting multiple Tickers Strategies (Momentum/Contrarian)
  • Technical Analysis with Python - Introduction
  • Stock trading with Technical Indicators - Backtesting
  • Keystone Project - Technical Trading with IBKR
  • PART 4: Advanced VIP Topics
  • Equity Valuation Concepts
  • Advanced Data Sources - EOD Historical Data
  • Data Streaming & Algorithmic Day Trading with IBKR
  • APPENDIX: Python Crash Course
  • Appendix 1: Python (& Finance) Basics
  • Appendix 2: User-defined Functions
  • Appendix 3: Numpy, Pandas, Matplotlib and Seaborn Crash Course
  • Appendix 4: Advanced Pandas Time Series Topics
  • Appendix 5: Object Oriented Programming (OOP)
  • What´s next? (outlook and additional resources)

Taught by

Alexander Hagmann

Reviews

4.3 rating at Udemy based on 454 ratings

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