Black Algo Trading: Build Your Trading Robot
Trading Robots: Insider guide from an Algorithmic Trader. No difficult coding. 100% industry wisdom (MQL4 Algo Trading)
By Lucas Liew
Course Description
**** Course featured on Investopedia ****
— Top Paid Finance Course in Udemy — | — Ranked 1st in Trading in Udemy —
Course last updated on 9th November 2015! Price will rise as more lectures are added. 27th Oct – $49, 15th Nov $99, 15th Dec $199, 31st May 2015 – $299.
More than 200 more lectures to be released over the coming months!
In the last chapter, you will learn how to build a robot that can think – Lynda (our version of Skynet).
Huh? What is a Trading Robot?
A Trading Robot a set of programming codes that analyses and trade the market on its own. Trading Robots allow you to trade the markets without human intervention!
What does this course offer?
This course teaches the insider secrets to designing, testing and coding long term profitable robots. We do NOT promise that you will strike it rich overnight. We do not make ridiculous claims (like those you see in newspapers and online ads) that you will make $3722 every night.
This course WILL, however, offer you the years of experience I have in building Robots. You will understand the pitfalls and keys to success to design great robots. You will avoid the hundreds of mistakes I made in my journey.
This course does not only teach programming. Programming is just the tool we use to execute our ideas. The main essence of the course is the design theories behind the Trading Robots. These theories and knowledge come from years of industry practice.
At the end of the day you will acquire the ability to generate a trading idea, code the idea (within 1hour), test the idea, see the strength and flaws in the idea, improve and finally execute the idea.
Chapters – Full List (These are Sections NOT Lectures!)
- Here’s What You Are In For!
- Programming Basics 1: Variables and Conditional
- Robot 1: Adeline – Our First Robot!
- Uncommon Common Sense. Design Effective And Logical Robots
- Garbage In, Garbage Out. Understanding Data
- Programming Basics 2: Loops
- Robot 2: Belinda – Utilising Volatility!
- To Buy Big or Small? Position Sizing and Money Management
- Robot 2A: Belinda Upgraded (No Gambler’s Ruin for Me!)
- Where To Start? Idea Generation and Expectations
- Programming Basics 3: Functions, Time and Self-Learning
- Relevant Statistics 101!
- Validating Your Robot: Backtesting!
- Programming Basics 4: Arrays And Indicators
- (***WE ARE HERE!!!***) Robot 3: Clarissa
- What A Mess – Managing Trades, Orders and Positions
- Robot 4: Desiree
- Design Theories – Improving Robots By Manipulating Time, Entries and Exits
- Add A Twist To Your Orders – Advanced Order Management
- Robot 5: Desiree 2.0
- Programming Basics 5: Clean Up Your Codes! Simple Is Fast!
- Garbage In, Garbage Out Again. Advanced Data Cleaning
- Robot 6: Elizabeth
- Perfect Your Bet Sizing – Advanced Position Sizing Methods
- Buff Up Your Robots Responsibly – Optimisation Without Curve Fitting
- I Like Colors And Shapes – Adding Graphics
- Robot 7: Faye
- Try And Try Again – Monte Carlo And Applications
- Not Rocket Science – Understanding Market Behaviour
- Breaking It Down – Testing Inefficiencies and Robots Separately
- Robot 8: Grace
- Understanding Performance – High Returns Are Meaningless!
- When Robots Fail – How, Why And Is It My Fault?
- Robot 9: Haley
- Walking Forward – Advanced Optimisation
- Let’s Academise This! – Advanced Statistics And Econometrics
- Robot 10: Iris
- I Want Numbers! – Quantifying Market Behaviors
- Ring Ring! Notify Yourself When Something Goes Wrong (Or Right)
- Robot 10A: Iris 2.0
- Looking To The Future! – Advanced Optimisation 2.0
- Time For Equities, Commodities And Bonds
- Everything is Relative – Relative Value Strategies
- Robot 11: Judy
- Many Robots One System – Running A Portfolio Of Robots
- Robot 12: Kate
- Cash Is King! – Running Robots With Real Money
- Watch Her Well – Monitoring Your Robot(s)
- Buy This Robot, It Makes 100% A Month! – Evaluating Commercial Robots
- Skynet – Robots That Think For Themselves
- Robot 13: Lynda (Skynet)
- Bonus Stuff!
What am I going to get from this course?
- Over 170 lectures and 12 hours of content!
- Understand how Trading Robots are both an art and science
- Build logical long-run money-making Trading Robots
- Code a Trading Robot in less than 1 hour
- Understand why badly planned Trading Robots fail
- Learn how to adapt and survive the financial markets
- Code in MQL4 and easily pick up C++ and JAVA
- Free up plenty of time by automating trading
- Start a side-job that doesn’t interfere with office hours
- Increase your chances of employment in Algorithmic Trading firms
- Understand the human element in automated trading
- Differentiate a logical and profitable robot from a scam
- Be a freelance coder
- Brag about a cool hobby at parties
What is the target audience?
- Those entering the workforce soon and want to explore their options
- Those wanting to endeavour into trading as a side-job
- Those wanting a guide who is on stand-by to assist them
- Those in mid or quarter-life crises
- Young adult and teens looking to trading as a career
- Those looking to switch career and want to get up to date with algorithmic trading
- Those wanting to understand advanced algorithmic trading and are looking for a starting point
- Those looking for an interesting hobby
- Who should not take this course: Those wanting to learn about High Frequency Trading. This course focuses on Low Frequency Trading
- Who should NOT take this course: Those wanting a secret recipe to strike it rich overnight
Instructor Biography
Lucas was an Algorithmic Trader at a proprietary trading firm. He has been designing and building trading robots since 2010. Lucas teaches programming for financial applications to Government of Singapore Investment Corporation (GIC), one of the largest sovereign wealth funds in the world.
Lucas does consulting for algorithmic trading projects. He has over 3 years of experience coaching in MQL4, MATLAB and VBA. He was the Head of the Quantitative Finance Society in Singapore Management University.
In his free time, Lucas mentors undergraduates in the areas of algorithmic trading and programming.
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