Lazy Trading Part 2: Set Up Your Trading Strategy Robot

Learn how Trading Robot Template is working and how to modify it to work with Decision Support System

What you'll learn
Using Automated Trading System in MQL4
Develop methodology to test and analyse Trading Strategy
Using version control to manage complex projects
Learn to set up Automated Decision Support Systems using R Statistical Software
Learn how to adapt Trading System Robot to specific Market Type
Replicate Decision Support System concept on other areas rather than Trading
Requirements
You should have a background knowledge on Trading and it's pitfals
You want to learn Data Science using Trading
PC Windows (min 4CPU 8Gb RAM). This machine should be left ON continuously for several weeks
You will need to use MQL 4
Best with 1 st course of Lazy Trading Series
Description
About this Course: Set up your Trading Strategy RobotThe second part of this series will cover setting up our Expert Advisor or Trading Robot. At the end of this course we will have complete and ready to be used Algorithmic Trading System integrated with our Decision Support System:
Programming environmentSetting up Version Control ProjectOverview of robot functionsHow to customize to target market inefficiencyIntegrate robot with Decision Support System (start/stop trading system from external commands)Customize and record trades resultsRolling Optimization, automatic robot backtestThe same robot template will be used in other courses of the Lazy Trading SeriesAbout 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 foundation of Decision Support System that can help to automate a lot of boring processes related to Trading.This project is containing several short courses focused to help you managing your Automated Trading Systems:Set up your Home Trading EnvironmentSet up your Trading Strategy RobotSet up your automated Trading JournalStatistical Automated Trading ControlReading News and Sentiment AnalysisUsing Artificial Intelligence to detect market statusBuilding an AI trading systemUpdate: dedicated R package 'lazytrade' was created to facilitate code sharing among different coursesIMPORTANT: all courses will be short focusing to one specific topic. You will not get lost in various sections and deep theoretical explanations. These courses will help you 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 SystemBe organized and systematic using Version Control and Automated Statistical AnalysisLearn using R to read, manipulate data and perform Machine Learning including Deep LearningLearn and practice Data VisualizationLearn sentiment analysis and web scrappingLearn Shiny to deploy any data project in hoursGet productivity hacksLearn to automate your tasks and scheduling themGet expandable examples of MQL4 and R codeWhat these courses are not:
These courses will not teach and explain specific programming concepts in detailsThese courses are not meant to teach basics of Data Science or TradingThere is no guarantee on bug free programmingDisclaimer:
Trading is a risk. This course must not be intended as a financial advice or service. Past results are not guaranteed for the future.

Overview

Section 1: Introduction

Lecture 1 Specific Goals for this Course

Lecture 2 Disclaimer

Section 2: Tools and Habits of a Trader and a Programmer

Lecture 3 Goals of This Section

Lecture 4 Get updated and read about the programing language

Lecture 5 Get ideas about Trading Strategies and Resources

Lecture 6 All above seems too complex or complicated? No problem!

Lecture 7 Code to DSS_LT_Bot Community Edition

Section 3: Intruduction to MQL4

Lecture 8 Introduction to this chapter

Lecture 9 Getting to know our Programming Environment MQL4 Editor

Lecture 10 Create new Script in MQL4

Lecture 11 Types of Variables

Lecture 12 Get value from function in MLQ4

Lecture 13 Use Condition [If] statement

Lecture 14 How to make a function

Lecture 15 Create your own functions catalog [Include]

Lecture 16 How to debug in MQL4

Lecture 17 For Loops

Section 4: What is really an Expert Advisor?

Lecture 18 Introduction of this Chapter

Lecture 19 Robot main structure

Lecture 20 External/Internal parameters

Lecture 21 Initialization/Deinitialization functions

Lecture 22 Start function

Lecture 23 User-Defined Functions

Lecture 24 Types of Algorading systems: Rule, Model, Hybrid based

Lecture 25 Rule-based robot FALCON_B

Lecture 26 Hybrid robot Falcon A

Section 5: Adapting Robot Template

Lecture 27 Get the code

Lecture 28 R package 'lazytrade'

Lecture 29 Our Robot Template

Lecture 30 Logging trading results to file

Lecture 31 Reading commands from Decision Support System

Lecture 32 How to understand and modify this robot?

Lecture 33 Adding option to close all positions on Friday evening

Lecture 34 Adding option to close all positions on Friday evening - video

Section 6: Practical Activity

Lecture 35 Optional challenge: Modify this bot

Lecture 36 Deploy to learn!

Lecture 37 Results and preview for Next Course!

Lecture 38 Using MetaTrader Terminal Profiles to manage different setups

Lecture 39 Keeping MT Terminals Profiles under Version Control

Section 7: How to evaluate Trading [Strategy] Robot?

Lecture 40 Goals of this Section

Lecture 41 FALCON_D - simple trading robot

Lecture 42 Why Periodic Optimization?

Lecture 43 Optimization Method P1. Settings overview

Lecture 44 Optimization Method P2. Collecting data during Trades Simulation

Lecture 45 Analyse simulated trades

Lecture 46 Evaluation of results

Lecture 47 Activity to practice

Section 8: Automatic 'Backtest' in MT4

Lecture 48 Goal of this Section

Lecture 49 Prepare configuration files

Lecture 50 Results

Section 9: Conclusion for Part 2

Lecture 51 Summary of this course

Lecture 52 Bonus Lecture: YOUR SPECIAL ENTRY TO NEXT COURSE

Anyone who want to be more productive,Anyone who want to learn Data Science and Trading at the same time,Anyone who want to try Algorithmic Trading but have little time