Last updated 6/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.84 GB | Duration: 3h 30m
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 Conditionf statement
Lecture 14 How to make a function
Lecture 15 Create your own functions catalognclude
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
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