AT101 – Fundamentals of Algorithmic Trading

Course overview
The major focus of the Fundamentals of Algorithmic Trading AT101 course is on the design ideas behind Trading Robots. Years of industrial practice have resulted in these theories and expertise. This course teaches more than just programming. Programming is just the instrument which is used to put our thoughts into action. At the conclusion of the day, you will be able to conceive a trade concept, code it (within 1 hour), test it, identify its strengths and defects, improve it, and ultimately execute it.
Course outline
The Fundamentals of Algorithmic Trading AT101 course includes everything you need to know about trading, including:
Here’s What You Are In For!
What is an Algo Trading Robot, its key traits and code structure
What makes a successful Algo Trader
How to set up and navigate your infrastructure/coding software
Programming Basics 1: Variables and Conditional
Basics of our coding language (MQL4)
Syntax, Variables, Operations and Conditional Expressions
Robot 1: Adeline – Our First Robot!
Background to Forex markets, chart reading, basic indicators
Coding Adeline together
Testing Adeline using past data
Brief look at modeling quality
Uncommon Common Sense. Design Effective And Logical Robots
Overview of our Strategy Development Guide
Preliminary Research
Backtesting
Optimisation
Live Execution
Pros and Cons of an Algo Trading Robot
Mathematical Expectations of our robots’ performance
Garbage In, Garbage Out. Understanding Data
Data Sources and Storage
A look at the importance of data cleanliness
Cleaning data (basic)
Bad ticks, inaccurate testing and market tricksters
Programming Basics 2: Loops
Learning how to code loops
Practice Exercises for Loops
Robot 2: Belinda – Utilizing Volatility!
Our first measure of volatility (ATR)
Introducing Belinda, the improved version of Adeline
Coding and testing Belinda
To Buy Big or Small? Position Sizing and Money Management
Understanding trade/bet size (how much to trade per position) using a coin flip game
Designing a bet sizing algorithm based on account size
Coding our bet sizing algorithm
Robot 2A: Belinda Upgraded (No Gambler’s Ruin for Me!)
Implementing our bet sizing algorithm in Belinda
Where To Start? Idea Generation and Expectations
Setting expectations for our robots based on our resources, personality, skill set, lifestyle and goals
Understand the essence of a trading idea – Proxies and Relationships
Sources of trading ideas
A look at the different types of strategies
Grading ideas – Introducing our framework for vetting ideas
How to fight against big hedge funds
Programming Basics 3: Functions, Time and Self-Learning
Learn to learn programming
Code errors and debugging
Coding Functions
Practice Exercises for Functions
Relevant Statistics 101!
Statistical significance and Law of Large numbers and their role in robot testing
Deriving suitable minimum sample size for our backtests
Understanding Robot Behavior and Robustness: Backtesting!
Ensuring code accuracy
Types of market condition
Testing for Robustness
Period Robustness
Timeframe Robustness
Seasonal Robustness
Instrument Robustness
Testing our robots through intended and unintended periods
Stress testing our robots through black swans
The butterfly Effect – Backtest bias via start point selection
Grading the performance of our robots
Programming Basics 4: Arrays And Indicators
A look at our mentality towards Indicators
Math behind Indicators
Coding Arrays and Indicators
Robot 3: Clarissa – Playing with Time
Understanding the Datetime data type
Coding rules revolving date and time manipulation
Introducing and coding Clarissa – our robot that uses time entries
What A Mess – Managing Trades, Orders and Positions
Order limitations by your brokers
Coding our customized order function
Multiple order management
Modeling transaction cost, spreads and slippage
Robot 4: Desiree – Trade like the Turtles
The history of the Turtle Traders
Introducing and coding a simplified turtle strategy
Design Theories IN – Improving Robots By Manipulating Time, Entries and Exits
Profitability in different timeframes
Deriving optimal stop loss levels
Comparing the importance of entries vs exits
Analyzing asymmetrical long and short rules
Add A Twist To Your Orders – Advanced Order Management
Breakeven and trailing stops
Hiding from your broker – Creating virtual stops and take profit orders
Robot 5: Desiree 2.0
Buff Up Your Robot Responsibly – Optimisation Without Curve Fitting
Objective Functions, Robustness and Curve Fitting
10 Ways to minimize curve fitting (overfitting)
Degrees of Freedom
Parameter Robustness
In and out-of-sample testing
Optimisation Evaluation
Perfect Your Bet Sizing – Advanced Position Sizing Methods
Relationship between sizing and trading frequency
Gearing up and down with volatility
Impossible Trinity of Sizing – Relationship between Leverage, % Risked and Stop Loss
First Principles of sizing – Building customized sizing algorithms
Other types of sizing – Kelly Criterion, Martingales and Anti-Martingales
Robot 6: Elizabeth
Programming Basics 5: Clean Up Your Codes! Simple Is Fast!
Clean and robust coding
MT4 Global Variables
MQL4 Libraries
Garbage In, Garbage Out Again. Advanced Data Cleaning (Part 1)
Creating custom timeframes
Clean data, biased output
Excel VBA – Using Excel Magic to Improve our Trading
Excel trading game
Syntax
Conditional statements
Loops
Garbage In, Garbage Out Again. Advanced Data Cleaning (Part 2)
Data time zone manipulation
Defining “clean enough” data
Scanning for errors
Advanced data cleaning methodologies
I Like Colors And Shapes – Adding Graphics
Creating a Dashboard: Graphics and Labels
Creating trend lines and levels
Ring Ring! Notify Yourself When Something Goes Wrong (Or Right)
Coding smartphone notifications
Notify yourself during trade or price events
Robot 7: Faye – Semi-Automated Trading
Connect with the outside world – Importing and Exporting Data out of our Trading Platform
Read and write information to Excel
Build a spread logger
Programming Basics 6: Trading Platform Nuances
Perfecting the little coding details
Understanding trading and backtesting nuances
Design Theories II – The “Secret Sauce”
Prudence-Behavioral Framework
Alpha 1: Data
Alpha 2: Global Macro
Alpha 3: High-Frequency Trading
Alpha 4: Market Microstructure
Hybrid Model – Semi-Algorithmic Trading
5 Realities of Algorithmic Trading
Crowd Behavior – Outwitting the Masses
Walking Forward – Advanced Optimisation
Walk Forward Optimisation
Performance patterns, consistency and seasonality
3D Parameter space evaluation
Trading CFDs
Looking Outwards – Trading On External Info and Alternative Data
Trading using volume
Feeding external data into MT4
Trade on external events
Robot 8: Gwen
Cash Is King! – Running Robots With Real Money
Paper versus Live trading
Minimum Capital Determination
Broker Selection
Virtual Private Servers
Downtime Prevention Protocol
Hedging issues
Strategy Monitor – Updating our robots regularly
Live walk-forward optimisation
Investor Marketplace
Watch Her Well – Monitoring Your Robot(s)
Operational Risk Management
Monitoring our robots
When to manually intervene
Reviewing performance
Understanding Trading Psychology – Emotions during drawdowns
What will you learn?
During the Fundamentals of Algorithmic Trading AT101 course, you will be shown precisely how to do trading, including:
Better understanding in the fundamentals of trading strategy design, testing and execution
Using a coin flip game to learn about trade/bet size (how much to trade each position).
Recognize the essence of a trade concept – Proxies and Relationships
Grading ideas and getting to know the trading concept evaluation.
The use of statistical significance and the Law of Large Numbers in robot testing
Backtest bias through start point selection – The Butterfly Effect
Who is this course for?
The Fundamentals of Algorithmic Trading AT101 course is tailored for:
Those who want to learn more about trading and programming
Those who want to be more multitask in trading to be more independent in trading
Those who want to approach the advanced aspects of trading