How this software beat Bitcoin | MUST WATCH

What if there was a software that you could use to help you be more effective in the crypto markets during all of its cycles?

We all know crypto is very cyclical, with up cycles and down cycles that typically extend over multiple years. During these cycles, you want to ensure you’re making the right decisions so that you’re not, in crypto terms, “fumbling the bag” or left as the “bag holder”—something I’ve, unfortunately, experienced more than once.

This is why I started using a software that executes trades in the cryptocurrency markets, specifically on Bitcoin and Ethereum.

I have my Bitcoin chart up, and this is what I mean by cycles. If I drop a cursor here, showing March of 2024, and another marker at October 2024, this is almost an entire year of a sideways-chop market. Now, we’ve just broken out to new all-time highs, but, of course, this won’t last forever.

For those of you who bought a coin, saw it go up significantly, and now think you’re a crypto genius—chances are, you’re not. We’re simply in an up cycle. Bitcoin is the tide, and as the saying goes, “A rising tide raises all ships.” Bitcoin is that tide.

You’re not necessarily a professional trader—you’re someone who got involved in crypto during an up cycle. In an up cycle, making money is relatively easy, but the truth is, most people won’t actually make money because they never sell. They watch their portfolio fluctuate upwards, thinking they’re making huge gains, but nothing is real until you sell. The same applies to losses—there are unrealized drawdowns, just as there are unrealized profits.

What if there was a tool that allowed you to be effective in any cycle? Let’s continue looking at the chart to examine different periods where the market either moved sideways or trended downward.

Back in 2017, I experienced my first six-figure parabolic portfolio run. I thought this was the ultimate breakthrough—I was rich forever. Unfortunately, like many others, I was left holding the bag, essentially donating everything I had straight back into the market.

If I drop an anchor at the highs of 2017 and another at the point of recovery, there was about a two-to-three-year period of pure accumulation. The market trended downward, bottomed out, and capitulated in a range. It never made new highs, nor did it create significantly new lows.

This is how Bitcoin moves—it operates in cycles. First, an up cycle (which is usually shorter), followed by a prolonged capitulation phase (a sideways-chopping market). Then, another run to the upside, followed by a massive correction—often 70% or more. After hitting a bottom, it capitulates again before restarting the cycle.

We’re all human. Nobody truly has “diamond hands,” as they say in the crypto world. We have emotions, and we struggle to stomach the massive swings in our portfolios. Many investors are too emotional to sell because they believe they’ll continue getting richer, which often leads to them giving everything back.

This is why I recently funded a cryptocurrency trading algorithm called Buterin. Now, I want to show you some data on how well this account has performed, compare it to Bitcoin’s performance since it started, and finally, share my own personal account performance.

The Buterin Algorithm

This algorithm is provided by Nurp. As you can see, this account was initially funded with $250,000. As of today, it has grown to $1.1 million, meaning it has generated $912,000 in profit since its inception in September 2023.

  • Total gain: 363%
  • Monthly average: 99.36%
  • Drawdown: 42%

We all know crypto is extremely volatile. Personally, I can stomach this volatility because I’ve lost a lot of money before, which has desensitized me to some degree.

Since its launch, the algorithm has executed 1,970 trades, with a 60% win rate. That means it has won 1,176 trades and lost 794.

The most important metric I consider for trading algorithms is the profit factor—this determines whether an algorithm is sustainable in the long run. Many algorithms perform well for a period, then underperform, then recover. The key is to take profits as soon as possible.

A profit factor above 1 makes me optimistic because it shows that the algorithm wins more than it loses. The higher the number, the better.

If we look back at 2023, the algorithm started in September. The first month was a 9% loss, but the following months showed strong gains: 12%, 0.3%, and 3%, ending the year positively.

Now, 2024 is the first full year for this algorithm. So far, it has had some incredible months—a 41% month, multiple 20%+ months, and even some months nearing 30%.

When adding up all the months of 2024, the algorithm generated roughly 165% in gains.

Comparing Performance to Bitcoin

If we go back to Bitcoin’s performance in 2024, using my measuring tool from January 1 to December 31, Bitcoin returned 108% for the year.

While 108% is outstanding for financial markets, the Buterin algorithm returned 165%—significantly outperforming Bitcoin’s price movements.

My Personal Buterin Account

Now, let’s take a look at my own Buterin account.

I funded this account on December 24, 2024, and since then, it has generated $112,926 in profit with a total gain of 43%.

Since my account has only been active for one month, the monthly average sits at 36.77%.

  • Total trades: 259
  • Win rate: 62%
  • Loss rate: 38%
  • Profit factor: 2.8

A profit factor of 2.8 means that for every $1 risked, I’m gaining nearly $3. If this performance sustains itself, this could be one of the most interesting trading software solutions of 2024, 2025, and 2026.

Final Thoughts

I just showed you the cryptobot I’m using, my initial deposit, and how well this account has performed historically. Of course, past performance does not guarantee future results, but I’m excited to share this journey with you all.

Whether the market moves into a bear cycle or experiences one more leg to the upside, I will continue holding and accumulating crypto. However, the key difference now is that I’m using software to take profits and capitalize on volatility.

If you’re interested in learning more, hit the link below to speak with the team and see if this is a good fit for your portfolio.

Or, if you just want to watch me risk a bunch of money online, please like, comment, and subscribe.

As always, my friends—peace.

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Matthew Jimenez
Matthew Jimenez | Algorithmic Trading Content by Nurp

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Matthew Jimenez

Matthew Jimenez | Algorithmic Trading Content by Nurp

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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.