Trading Algorithm Performance Over a Year of Tracking

https://www.youtube.com/watch?v=fsMJxx22Fs0

I’ve been documenting the power of algorithmic trading and tracking all of its performance in a series for you guys, and quite frankly, everyone has enjoyed it. In fact, it’s our most popular series yet. If you haven’t watched it, here it is up above. But in this video, I’m actually not going over my software. In this video, I’m going over the CEO Jeff Sekinger’s algorithmic trading software and tracking his performance. He gave me his MyFXBook link, which is a third-party verifier that tracks all of the data. Without further ado, let’s get straight to it!

Welcome! If you’re new to the channel, my name is Matt Jimenez. I’m an entrepreneur who has worked with the greatest minds in finance, and I’m here to share with you everything they’ve shared with me. In this video, we’re going to go over something extremely interesting in comparison to what I have been doing.

As I said at the beginning of this video, I’ve been documenting a journey of $50,000 in an account that trades utilizing the FED bot software. In this video, I’m not covering my account; I’m covering the CEO’s account. This is his MyFXBook link, and we will be going over all the data. The important thing to note is that, unlike my account, where I haven’t adjusted any of the risk settings and have kept them below the standard risk level, the CEO has been adjusting his risk settings as his account grows. This helps offset the amount he should be earning relative to his account size.

None of this is financial advice; these are our own financial decisions. It’s never recommended advice. With all that being said, let’s see what happens when you take full ownership over the risk management of your software and make the necessary adjustments as your account grows.

Okay, here we go. We have the FED Bot. As you can see, his leverage is a little different than mine. His is 1:200, while mine is 1:500. This account was started on December 27, 2022, and today’s date is May 13, 2024. In that time period, this account has achieved a 42% gain. That is insane! I actually don’t know another asset that performed that well. His average monthly gain is 10.22%. The biggest drawdown he experienced was 21%, and his daily gain is 0.33%. The balance when he started the account was $4,940, and he’s already withdrawn the initial $225,000. Right now, he’s basically playing with house money, but his total profit is $88,200.

So far this year, he’s done 10.3%, this week 0.04%, and for the month so far 1.3%. This year, he has achieved 16.91%, almost 17%, which is a profit of $2,738 using this software.

Now let’s scroll down to see more detailed data. Since he started this account in December, it has completed 11,294 trades. Imagine trying to be an investor or a manual trader over a 2-year period, executing 11,000 trades—that would be a full-time job plus overtime just pressing buttons, let alone finding the trades. His profitability is 75%, meaning he wins 75% of the time and loses 25%. He has won 8,495 trades and lost 2,700 trades. The average pip win is 19.8. His worst trade in dollar terms was -$270, and his best trade was $2,251. The average loss was 58 pips.

The profit factor, which is extremely important, is 1.87. This means he gains 1.87 for every one he risks. In trader lingo, this is known as the risk-to-reward ratio (RR).

Let’s scroll down to 2022. In December, he did 2.37%. Now let’s check out the performance for 2023, which is really exciting because that 42% gain was likely made during 2023, the only full 12-month span of letting the bot run. Clearly, 2022 was only one month, and 2024 is still in Q2.

Monthly Performance for 2023:

  • January: 27.84%
  • February: 12.64%
  • March: 26.2%
  • April: 16.78%
  • May: 8%
  • June: 11.8%
  • July: 19.26%
  • August: 4.34%
  • September: 6.68%
  • October: 9.13%
  • November: 5.92%
  • December: 8.79%

Now let’s check the current year, 2024. It started slower than last year, with January being the biggest month yet at 27%.

  • January: 3.56%
  • February: 2.27%
  • March: 2.21%
  • April: 6.79%
  • May: 1.13% so far (as of May 13th)

The most interesting thing is that every single month saw a profit; there was not a single losing month. I don’t know of any asset on Earth that doesn’t have a losing month, which is more shocking than anything else. I cannot believe how well this has performed.

If you found value in this, maybe I’ll start tracking his account alongside my own, with more caution on the risk side, of course. Clearly, he knows what he’s doing. Leave a comment if you would love to watch the performance of this software alongside my other one. If you’re interested in potentially licensing something like this, hit the link down below to ask questions and see if it’s a good fit for you. If not, at least give me a like and/or subscribe. I’d greatly appreciate it. As always, my friends, peace.

Please visit Trading Algorithm Performance Over a Year of Tracking to watch the video on YouTube!

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Matthew Jimenez
Matthew Jimenez | Algorithmic Trading Content by Nurp

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Greg Doscher was a CFO for many years who built out many quantitative strategies and investment tools to manage and enhance risk adjusted returns in the company’s pension plan. Prior to joining Nurp, he consolidated his skills in coding and discretionary trading to develop a comprehensive and fully automated algorithmic trading system deployed across 200+ futures markets and cryptocurrencies that encompassed all of the trading strategies he had honed over the last 22 years in finance

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Abhayjit Anand

Abhay has worked with Nurp since 2022. As a Product Strategist, he focuses on building, refining, and commercializing algorithmic trading strategies. He brings seven years of experience in financial trading – combining macro research, technical analysis, quantitative strategy development, and market psychology. Alongside his work at Nurp, Abhay also serves as an Investment Analyst at Orca Capital. Before entering financial markets professionally, he spent eight years at IBM, including three years in the AI & data division as a Delivery Lead managing complex implementation projects.