Lazy Trading Part 4: Trade Control with Reinforcement Learn

"This is about a Robot that can control Robots!"

About the Lazy Trading Courses:
This series of courses is designed to to combine fascinating experience of Algorithmic Trading and at the same time to learn Computer and Data Science! Particular focus is made on building Decision Support System that can help to automate a lot of boring processes related to Trading and also learn Data Science. Several algorithms will be built by performing basic data cycle 'data input-data manipulation - analysis -output'. Provided examples throughout all 7 courses will show how to build very comprehensive system capable to automatically evolve without much manual input.

About this Course: Set up Automated Risk Management Software
The fourth part of this series will enable automatic risk management of multiple Algorithmic Trading Systems. Algorithm will be capable to identify best and worse Trading Systems. This will allow to automate decision to start or stop Trading Robots. Course is featuring several methods of achieving this goal, provides functions allowing to apply or adapt this method for any situation including outside of trading.

We will learn these Data and Computer Science concepts:

• Use R program to perform data analysis and generating output result

  • Import data from files

  • Clean and select data

  • Writing and using functions in R

  • 'for' loops

  • Data manipulation using 'pipe' operator and 'dplyr' package in R

  • Write data to files

• Calculate Profit Factor in R

• Using Reinforcement Learning in R

  • Reinforcement Learning Example

  • Creating Adaptive Reinforcement Learning system

• Automating and Scheduling any R code

"What is that ONE thing very special about this course?"

-- Application of Reinforcement Learning algorithm that is learning from very first observation!

This project is containing several courses focused to help you managing Automated Trading Systems:

1. Set up your Home Trading Environment

2. Set up your Trading Strategy Robot

3. Set up your automated Trading Journal

4. Statistical Automated Trading Control

5. Reading News and Sentiment Analysis

6. Using Artificial Intelligence to detect market status

7. Building an AI trading system

Dedicated R package 'lazytrade' is now published on CRAN to facilitate code sharing and improve code documentation

IMPORTANT: all courses are very practical focusing to one specific topic with only essential theoretical explanations. These courses will help to focus on developing strategies by automating boring but important processes for a trader.

What will you learn apart of trading:

While completing these courses you will learn much more rather than just trading by using provided examples:

• Learn and practice to use Decision Support System

• Be organized and systematic using Version Control and Automated Statistical Analysis

• Learn using R to read, manipulate data and perform Machine Learning including Deep Learning

• Learn and practice Data Visualization

• Learn sentiment analysis and web scrapping

• Learn Shiny to deploy any data project in hours

• Get productivity hacks

• Learn to automate R programs and scheduling them

• Get expandable examples of MQL4 and R code

What these courses are not:

• 'Holy grail' or Automatic Trading Black Box

• These courses will not teach and explain specific programming concepts in details

• These courses are not meant to teach basics of Data Science or Trading

• There is no guarantee on bug free programming

Disclaimer:

Trading is a risk. This course must not be intended as a financial advice or service. Past performance results are not guarantee for the future.