MQL5 PROJECTS: Code the Black Swan Trading Strategy in MQL5

Name: MQL5 PROJECTS: Code the Black Swan Trading Strategy in MQL5
Rating: 4.8 (16 reviews)

A complete guide to coding the Black Swan EA using MQL5

Created byDaria Sabas Mark, Latvian Trading Solutions, Joy D Moyo

Last updated 10/2025

English

English [Auto],

What you'll learn

How to trade with the Black Swan trading system
How to translate a trading strategy into code.
How to implement Time zone filters into EAs
How to implement Daily Profit and Loss Targets into EAs

Course content

3 sections • 16 lectures • 2h 31m total length

The Black Swan Strategy9:36
Introduces the flex one expert advisor for the black swan strategy: trade with moving-average signals, double loss recovery, 30-pip targets, and euro and New York session momentum filters.

Setting the calculation interval6:45
Build the black swan expert advisor template with initialization routines, a new bar detector, and on-tick logic that updates only on new hourly bars to save memory and improve testing.
Changing the chart appearance7:43
Learn how to customize MT5 chart visuals for the Black Swan trading strategy by disabling the grid, configuring candlesticks, colors, and volumes to improve signal visualization.
Setting general parameters5:25
Set general parameters for an MQL5 expert advisor by grouping inputs, fixing symbol and period traded, and initializing global digits and point using symbol info.
Getting Indicator values6:36
Learn to obtain indicator values using a moving average: create a moving average handle, store data in a double buffer, and copy the latest four values into Ma buffer.
Preparation for trade entry8:17
Include the trade class and initialize objects for trade, position info, and delete info to prepare for entry, and set the expert magic number.
Setting risk parameters7:36
Set up a risk group of inputs to govern lot size based on account balance. Create a lot size function that scales with balance and enforces min and max limits.
Generating entry signals8:55
Generate buy and sell entry signals by comparing the previous close from the loss function to a moving average buffer, and count active trades by symbol and type.
Entering the First Trades13:18
Enter your first trades by configuring trade distance, converting pips to points and price, and setting stop loss and take profit for buys and sells using a trade class.
Counting consecutive losses12:05
Learn to implement a loss count function in MQL5 that scans trade history, filters by expert advisor and symbol, counts consecutive losses, and resets on a win to guide reversals.
Entering reversal trades20:18
Enter reversal trades by doubling the next trade lot and track the last trade type to guide buy or sell entries, with take profit and stop loss calculations.
Coding a Timezone Filter19:33
Code a timezone filter in an MQL5 expert advisor to constrain trades to specific sessions, using start and end times, time zone inputs, and session checks for target windows.
Daily Profit and Loss Targets14:49
Learn to reduce risk and greed by enforcing daily profit targets and maximum losses, tracking daily balance, and stopping trading after hitting thresholds or a new day.
Testing the EA6:38
Test the ea using visual mode and 2020–2023 backtests on hourly data to reveal profitable trades, risks, and a 2400 profit with a 48% max return amid black swan events.

Requirements

A basic foundation in the MQL5 language

Description

For most retail traders, the main objective of trading any financial instrument is to earn a profit, and there is nothing more tempting than an almost guaranteed system that ensures that you earn it.

Have you ever wondered what it would be like to have a system that ensures that you consistently make profits as long as the markets move. Imagine having a system that ensures that you wont ever have to worry about making the wrong market analysis or losing a trade in the market. Imagine entering a trade with a very high degree of certainty that even though you might lose it, in the end, you will have more money than you previously did.

At the centerpiece of this course is the Black Swan trading strategy, which offers a unique approach to managing trades. The strategy ensures that when we are wrong about the market direction, we close our trades at a loss, then recover that loss with a high probability of certainty that eventually we shall make our money back as we trade in the prevailing market direction. If we are correct about the market direction, we capitalize on our winning trades and continue trading in that direction.

To increase our chances of success, we shall build a trading sessions filter that will ensure that we only trade during specific time intervals where high momentum and activity is expected.

We shall also code daily profit and loss limit functions to control how much we are willing to make or lose per day to ensure that we minimize our exposure to black swan events that can limit the success of the strategy.

Throughout this course, we will guide you through the main protocols of the strategy and teach you how to code using the MQL5 language. We will conduct thorough testing to explore its strengths and weaknesses, enabling us to exploit its ideas effectively.

if you're an algorithmic trader seeking new ideas for managing your open trades, then this course is definitely tailored for you. By the end of this course, you'll be enriched with fresh concepts for your own algorithmic trading projects. Lets embark on this exciting journey together. Hit hard on that enroll button now and join us in this incredible journey of coding the Black Swan trading system.

Who this course is for:

Anyone willing to learn a new trading system.
Anyone willing to learn how to translate a trading system into MQL5 code.
Anyone willing to learn how to learn how to create a Daily Profit and Loss limit functions
Anyone willing to learn how to create a Time zone filter function

MQL5 PROJECTS: Code the Black Swan Trading Strategy in MQL5

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 10min

Coding the trading system13 lectures • 2hr 18min

Conclusion2 lectures • 4min

Requirements

Description

Who this course is for: