How I Achieved a 74% Profit Using Michael Harris’s Trading Pattern in Python | Full Backtest

In this video, I walk you through how I achieved a 74% profit using one of Michael Harris’s trading patterns. I’ll show you exactly how I coded the backtest in Python, step-by-step, and applied algorithmic trading logic to both the QQQ (Nasdaq-100) and S&P 500 historical data. You’ll see how I implemented the pattern recognition, set stop-loss and take-profit targets, and verified the results through a full algorithmic backtest. By the end, you’ll have the knowledge and code to replicate this strategy for your own trading experiments.

📘 Book available on Amazon (Algorithmic Trading Hands-On Approach Using Python):

Discount Vouchers for my Algorithmic Trading and Python courses:

Grab the Python code here, and the data files as well:

Good luck Guys! Enjoy coding in Python :)

[Adam.]

You are really nice giving this knowledge away. I just realized you have courses, I am looking to buy them in the future. You are so great. I had no sleep, thought about studying coding rather than just laying on my bed, and now I try out your codes. :)

[lorensaunders]

I love that you test all these ideas out so thoroughly. It always gives me more to add to my own strategies (or not add). Thank you.

[OK-jcsl]

LOVE THE WORK BTW PLEASE KEEP UP THE GOOD VIDEOS

[IndefiniteMark]

Its cool to see so many likeminded busy bees experimenting on our own designs - its whats beautiful about programming, the hard work pay off when you combine and chain ideas together 💡

[SomeoneElsesSomeoneElse]

Love your channel. Thank you for the incredible work.

[micheleMX]

Great video!! actually after watching another of your video, I was looking for an algorithm about the index S&P 500.
Anyway the results looks great, you got a combined 107% return, over almost 8 years time frame. BUT the S&P500 alone, with just buy&hold strategy, achieved 135% and QQQ an astonish 295%.
This is not a critics to you, is just a consideration about active vs passive investments.

[forex.signal.on.youtube]

over 70% win rate is really something. great finding.

[alison]

Very good video, congratulations on the explanation!!!, in this video alone I learned a lot, I urgently need to learn Python lol

[simonescelsa]

Technical analysis Always work over a time frame with the underlying trending in one direction. Even a long short strategy stops working when the market starts trending downwards as the movements tend to be much faster on the way down and TA signals lag.

[tsetsoangelov]

I am so going to look into this using python and algorithms to trade

[the_real_cookiez]

An easier way to share code would be a repo! Thank you for this!

[arnohmoins]

I haven’t done Python in many years. Great job on this work! Personally, I do the same in C# on NT8, focusing on futures markets (ES, NQ, YM), which have been heavily traded by retail traders in recent years thanks to access through prop firms. I haven’t watched all the videos yet. What is your favorite strategy among those you’ve backtested?

[georgeyang]

awesome video! I never lose any episode :)
can you shere the pdf of the book you mentioned in the video?

[stedocli]

Thank you for making such helpful content. In the video, you suggested manually managing trade exits to potentially improve algorithmic trading performance. Would implementing RL be an effective approach to better exit trade exit strategies?

[eitan]

great video - again !
when you use candle patterns' can you also test on different coins of crypto please?
Thank you for sharing your great work !

[naderafshari]

great videos thank you. Question: which one of the strategies you have here you think would be the most profitable for which market?

[nicolasfranz-koltren]

excellent videos! how would you recommend a beginner to start with your videos/courses? For algo trading(Assuming already knows python)

[gvidalcantavella]

Nice video, thank you! I was just wondering why using fixed percentage instead of using the ATR like in different videos.

[leandrogoethals]

do Tom Basso strategy next pleases:

Core Principles:

Entry Doesn't Matter: This strategy disregards traditional entry point analysis, using a coin flip to decide long (buy) or short (sell) positions.
Risk Management is Key: The focus is on managing risk and letting profits run.
Position Sizing: Risk is limited to 1% of the account per trade.
Stop Loss:
Initial stop loss: 3 times the Average True Range (ATR) calculated over the last 10 days (exits the position if price falls below this level).
Trailing stop loss: The stop loss is adjusted upwards (for long positions) or remains unchanged (for short positions) by 3 times the ATR as the price moves favorably. This locks in profits while allowing the position room to breathe.
Discipline: The strategy emphasizes following the rules without emotional interference.

the sl we should optimize by having a range of sl values

[ankitruparel]

its amazing you have given this for free. Wondering if there is a way to verify if my code is running correctly generating the right signals and can be matched with trading view. Not able to find a trading view indicator that can help verify. Normally without that I get less confidence in knowing my code works.