Can this Trading Algorithm Beat the S&P 500, Bitcoin, and Possibly Real Estate?

Will this robot be able to outpace traditional markets in terms of gains in the next 12 months? What is going to be the best-performing asset? Will it be the S&P 500? Will it be Bitcoin, or will it be real estate? And there’s one more competitor that I want to add into the mix, and that is my financial advisor—that’s a robot. And what I mean is just the software that I’ve been utilizing. If you guys have been watching the channel, you know exactly what I’m talking about. And if not, here’s a quick one-two on it.

Nurp has a trading software that you could attach to your brokerage, and it executes trades for you. So what I want to do in this video is compare the robot’s performance to other financial instruments and see where we will be in the next 12 months. In this video, this will be the start of a new playlist where you could see month-to-month on how we are performing in comparison to other markets, such as the ones I stated earlier.

All right, guys, welcome back, and if you’re new to the channel, my name is Matt Jimenez. I am an entrepreneur that has worked with the greatest minds in finance over the last 5 years, and I’m here to pour into you guys everything that they poured into me. Without further ado, let’s get straight to it.

October 27th, I opened up a brokerage account with Fusion markets live, and what I did was attach Nurp’s trading software to see how well we can do in this account. I deposited $50,000 where I gave full access for the software to execute on all the trading decisions. And I want to see from the starting date of when I opened this account how we stack up against the S&P, Real Estate, Bitcoin, and gold, because all of those to me are other asset classes that I’m extremely interested in and have a bit of knowledge in. So let’s jump over to the charts and let’s do the comparison.

Okay, so we are here on myfxbook. This is the account that I have the $50,000 in that I’ve been tracking. And remember, the starting date is October 27th, so this is when the money hit the account and was actively trading since then. We’re up 1.58%. November, we are at 0.99%, so about a percent for this. So overall, since the account has started, we are up 1.58%. Now let’s jump over to TradingView and see how that stacks up in comparison to other markets.

I have the S&P pulled up here on TradingView, one of my favorite tools to use just to give me my quick numbers. Is this icon right over here? It’s a measuring tool. All you do is go over to the candle when you want to measure from. So in this case, we’re starting October 27th, which is this candle, and the close of this candle was right here. So I’m going to go ahead and click down, and then I’m going to go to the current price where we are.

So if I had invested that $50,000 in the S&P on October 27th, I would be up 99.57%, which is absolutely phenomenal. And coincidentally, it’s at a complete low. So as you could see, we have this downtrend happening in the S&P, and ironically, October 27th happened to be at the bottom of an impulse movement. So this is an impulse movement. This is an impulse movement. This is the impulse movement. The ones going to the upside are corrections. So correction one, correction, correction. So we would have bought on this date right here, which was at the end of an impulse movement. So that is the best time to become a buyer in the downtrend, which obviously led to this massive gain of 92%.

So S&P wins this time by a whopping 8%. Let’s check Bitcoin. Bitcoin’s October 27th. If I was to put $50,000 in on that date, where would I be? So this candle right here is the starting date. Let’s grab our tool, start at the close of that, and we are currently right here at live price. Bitcoin from October 27th to today is 7.86%, so they beat us by a good 6%.

Let’s do the dollar for giggles. October 27th, all right, this is going to be funny. From here, you had x amount of dollars in your bank account to right here on the current day. The same amount of dollars in your bank account is now 2% weaker. If you held dollars instead of using software, you would be down 2%. So we beat the dollar, that’s a good sign, guys. Let’s pop over to Gold really quick, let’s grab our tool, find October 27th. All right, right here, this candle. So here’s the close of the candle. All right, wow, so gold is down -1%. So we beat gold too. So…

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Jeff Sekinger
Jeff Sekinger | Wealth Strategies

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AI Quantitative
Researcher

Bingham Zhou

Bingham Zhou, CFA, has over 15 years of experience as a quantitative researcher. His expertise spans systematic equity strategies, CTA trend-following, and interest rate proprietary trading in both U.S. and Asian markets. He holds advanced degrees from MIT, Carnegie Mellon, and Yale.

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Quant–Investment Strategist
Greg doscher

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

Quant–Investment Strategist
Marcin Borratynski

Marcin was Head of Quant IT at the USD 4bn+ CERN Pension Fund, where he spent nearly a decade building quantitative asset allocation systems and implementing algorithmic investment strategies for a multi-asset institutional portfolio.Before joining Nurp Marcin was also Senior Quant Strategist at Evooq, a Swiss-based fund managing four strategies across equities, gold, and equity derivatives.Marcin holds a degree in Computer Science an MBA from the University of Geneva and the Certificate in Quantitative Finance (CQF).

Product Manager

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.