Algorithmic Trading A-Z with Python and Machine Learning

Algorithmic Trading A-Z with Python and Machine Learning

Build your own truly Data-driven Day Trading Bot | Learn how to create, test, implement & automate unique Strategies.

What you’ll learn

  • Create powerful and unique Trading Strategies based on Technical Indicators and Machine Learning.
  • Rigorous Testing of Strategies: Backtesting, Forward Testing and live Testing with play money.
  • Truly Data-driven Trading and Investing.
  • Python Coding and Object Oriented Programming (OOP) in a way that everybody understands it.
  • Coding with Numpy, Pandas, Matplotlib and scikit-learn.
  • Understand Day Trading A-Z: Spread, Pips, Margin, Leverage, Bid and Ask Price, Order Types, Charts & more.
  • Day Trading with Brokers OANDA & FXCM.
  • Stream high-frequency real-time Data.
  • Understand, analyze, control and limit Trading Costs.
  • Use powerful Broker APIs and connect with Python.

Requirements

  • A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
  • An internet connection capable of streaming HD videos.
  • You should have worked with Python before (recommended but not required). This course provides a Python Crash Course.
  • Some high school level math skills would be great (not mandatory, but it helps)
  • In some countries (Japan, Russian Federation, South Korea, Turkey) CFD/FOREX Trading is not permitted and residents cannot create an account on OANDA or FXCM (Online Brokers). Please keep in mind that approx. 20% of the Course (Trading and Implementation) won´t work for you! Thanks a lot for your understanding!

Description

Welcome to the most comprehensive Algorithmic Trading Course. It´s the first 100% Data-driven Trading Course!

In this rigorous but yet practical Course, we will leave nothing to chance, hope, vagueness, or hocus-pocus!

Did you know that 75% of retail Traders lose money with Day Trading? (some sources say >95%)

For me as a Data Scientist and experienced Finance Professional this is not a surprise. Day Traders typically do not know/follow the five fundamental rules of (Day) Trading. This Course covers them all in detail!

1. Know and understand the Day Trading Business

Don´t start Trading if you are not familiar with terms like Bid-Ask Spread, Pips, Leverage, Margin Requirement, Half-Spread Costs, etc.

Part 1 of this course is all about Day Trading A-Z with the Brokers Oanda and FXCM. It deeply explains the mechanics, terms, and rules of Day Trading (covering Forex, Stocks, Indices, Commodities, Baskets, and more).

2. Use powerful and unique Trading Strategies

You need to have a Trading Strategy. Intuition or gut feeling is not a successful strategy in the long run (at least in 99.9% of all cases). Relying on simple Technical Rules doesn´t work either because everyone uses them.

You will learn how to develop more complex and unique Trading Strategies with Python. We will combine simple and also more complex Technical Indicators and we will also create Machine Learning-powered Strategies. The course covers all required coding skills (Python, Numpy, Pandas, Matplotlib, scikit-learn) from scratch in a very practical manner.

 

3. Test your Strategies before you invest real money (Backtesting / Forward Testing)

Is your Trading Strategy profitable? You should rigorously test your strategy before ‘going live’.

This course is the most comprehensive and most rigorous Backtesting / Forward Testing course that you can find.

You will learn how to apply Vectorized Backtesting techniques, Iterative Backtesting techniques (event-driven), live Testing with play money, and more. And I will explain the difference between Backtesting and Forward Testing and show you what to use when. The backtesting techniques and frameworks covered in the course can be applied to long-term investment strategies as well!

4. Take into account Trading Costs – it´s all about Trading Costs!

“Trading with zero commissions? Great!” … Well, there is still the Bid-Ask-Spread and even if 2 Pips seem to be very low, it isn´t!

The course demonstrates that finding profitable Trading Strategies before Trading Costs is simple. It´s way more challenging to find profitable Strategies after Trading Costs! Learn how to include Trading Costs into your Strategy and into Strategy Backtesting / Forward Testing. And most important: Learn how you can control and reduce Trading Costs.

 

5. Automate your Trades

Manual Trading is error-prone, time-consuming, and leaves room for emotional decision-making.

This course teaches how to implement and automate your Trading Strategies with Python and powerful Broker APIs. Create your own Trading Bot!

Finally… this is more than just a course on automated Day Trading:

  • the techniques and frameworks covered can be applied to long-term investing as well.
  • it’s an in-depth Python Course that goes beyond what you can typically see in other courses. Create Software with Python and run it in real-time!
  • we will feed Machine Learning Algorithms with real-time data and take ML-based actions in real-time!

What are you waiting for? Join now. As always, there is no risk for you as I provide a 30-Days-Money-Back Guarantee!

Thanks and looking forward to seeing you in the Course!

+++ IMPORTANT NOTICE +++

In some countries (Japan, Russian Federation, South Korea, Turkey) CFD/FOREX Trading is not permitted and residents cannot create an account on OANDA or FXCM (Online Brokers). For the heart of this course (Coding, Creating Strategies, Backtesting & Forward Testing Strategies) you don´t need a Broker account. Therefore, this course is a great choice even without a Broker account. But please keep in mind that some parts (Trading and Implementation) won´t work for you! Thanks a lot for your understanding!

Who this course is for:

  • (Day) Traders and Investors who want to professionalize and automate their Business.
  • (Day) Traders and Investors tired of relying on simple strategies, chance and hope.
  • Finance & Investment Professionals who want to step into Data-driven and AI-driven Finance.
  • Data Scientists and Machine Learning Professionals.

Course content

31 sections • 360 lectures • 31h 39m total length
  • Getting Started
  • +++ PART 1: Day Trading, Online Brokers and APIs +++
  • Day Trading with OANDA A-Z: a Deep Dive
  • FOREX Day Trading with FXCM
  • Installing Python and Jupyter Notebooks
  • Trading with Python and OANDA/FXCM – an Introduction
  • Conclusion and Outlook
  • +++ PART 2: Pandas for Financial Data Analysis and Introduction to OOP +++
  • Introduction to Time Series Data in Pandas
  • Financial Data Analysis with Pandas – an Introduction
  • Advanced Topics
  • Object Oriented Programming (OOP): Creating a Financial Instrument Class
  • +++ PART 3: Defining and Testing Trading Strategies +++
  • Defining and Backtesting SMA Strategies
  • Defining and Backtesting simple Momentum/Contrarian Strategies
  • Defining and Backtesting Mean-Reversion Strategies (Bollinger)
  • Trading Strategies powered by Machine Learning – Regression
  • Trading Strategies powered by Machine Learning – Classification
  • Advanced Backtesting Techniques
  • +++ PART 4: Real-time Implementation and Automation of Strategies +++
  • Implementation and Automation with OANDA
  • Implementation and Automation with FXCM
  • +++ PART 5: Expert Tips & Tricks, Case Studies and more +++
  • Trading Hours, Spreads and Granularity – control and limit Trading Costs!
  • Working with two or many Strategies (Combination)
  • A Machine Learning-powered Strategy A-Z (DNN)
  • +++ APPENDIX: Python Crash Course +++
  • Appendix 1: Python (& Finance) Basics
  • Appendix 2: User-defined Functions (required for OOP)
  • Appendix 3: Numpy, Pandas, Matplotlib and Seaborn Crash Course
  • What´s next?

Created by: Alexander Hagmann, (Data Scientist | Finance Professional | Entrepreneur)

Last updated 12/2020
English

English [Auto]
9.9 GB (Direct Download Available)

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Rating: 4.6 out of 5
(100 ratings)
1,680 students
https://www.udemy.com/course/algorithmic-trading-with-python-and-machine-learning/

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