What is a Remington Sutton How to Write an Algorithmic Trading Program for Cheap?
This course teaches you to write multiple live, trading strategies and employ them on the live market. If you have ever wanted to do the kind of market trading like the “quants” on Wall Street, or use a computerized model for trading, you should take this course. You will learn the basic principles and tools for creating your own algorithms for trading markets right from your computer.
The course is structured in 12 video lectures/lessons in four sections for a total of an intensive 10 hours of lecture and demonstrations. You can expect to spend at least another 10 hours practicing the programming techniques.
What You’ll Learn In How to Write an Algorithmic Trading Program?
- Over 24 lectures and 5.5 hours of content!
- Write a historical data trading algorithm
- Find and manage historical data
- Write multiple live, trading strategies and employ them on the live market
Who is How to Write an Algorithmic Trading Program for?
- People with an analytical mind
- People with some introductory knowledge of programming
What are the requirements?
- Students need a laptop, internet access and I will walk through every step of the process of program selection and downloading
Remington Sutton How to Write an Algorithmic Trading Program Index:
📁 01 Introduction to Trading Strategies
📄 001 What is an automated trading strategy and how is it developed.mp4 (57.54 MB)
📄 002 Setting up environment and setting up data.mp4 (20.20 MB)
📁 02 Data Essentials
📄 001 Lecture 3.1 Basics of coding environment and how to set it up.mp4 (47.68 MB)
📄 002 Lecture 3.2.mp4 (49.81 MB)
📄 003 Lecture 3.3.mp4 (43.47 MB)
📄 004 Lecture 4.1 Processing and cleaning historical market data.mp4 (38.54 MB)
📄 005 Lecture 4.2.mp4 (36.85 MB)
📄 006 Lecture 5.1 Feeding in the historical data.mp4 (28.07 MB)
📄 007 Lecture 5.2.mp4 (29.26 MB)
📁 03 Building the Model
📄 001 Lecture 6.1 Setting up the models.mp4 (31.97 MB)
📄 002 Lecture 6.2.mp4 (23.33 MB)
📄 003 Lecture 7 Overview of 4 types of models that we will build.mp4 (16.17 MB)
📄 004 Lecture 8.1 Build a Momentum model.mp4 (42.68 MB)
📄 005 Lecture 8.2.mp4 (44.77 MB)
📄 006 Lecture 8.3.mp4 (54.28 MB)
📄 007 Lecture 9 Build a Mean Convergence Model.mp4 (26.17 MB)
📄 008 Lecture 10.1 Build a Correlation Model.mp4 (36.89 MB)
📄 009 Lecture 10.2.mp4 (36.62 MB)
📄 010 Lecture 11.1 Build a Pattern Recognition Model.mp4 (55.39 MB)
📄 011 Lecture 11.2.mp4 (61.57 MB)
📄 012 Lecture 11.3.mp4 (53.29 MB)
📁 04 Make Your Model Live
📄 001 Lecture 12.1 Select the optimized models and make them live.mp4 (50.49 MB)
📄 002 Lecture 12.2.mp4 (59.94 MB)
📄 003 Lecture 12.3.mp4 (55.64 MB)
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