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Interview With NaturalStep ($NSC)

We had the pleasure to interview NaturalStep, the trader of DARWIN $NSC.

Migrated to Darwinex in February 2018, $NSC has had a D-score > 70 ever since June 2017. A fourfold DarwinIA winner (March, June, September and November 2018) $NSC is currently included in the Good Scores, Return > 50%, On Fire and Under the radar filters!

NaturalStep, tell us a little about yourself. How did you get started and how long have you been trading for?

My interest in stock trading dates back to my college days.

After saving my stipendum for three years, I made my first investment in 2003. I started trading Hungarian stocks first, then foreign stocks as well, after which my focus moved to FX trading exclusively in 2008, manually trading all the way.

It was during these years that – thanks to some severe fallbacks – I started to develop a cognitive model based on patterns existing in nature itself which eventually lead to a series of successful, profit-earning periods. I felt I had a good reason to assume that my system actually works. It was making reliable profit.

After the birth of my son and due to the demands of my parental responsibilities, I’ve decided to create a robot. It’s the one doing the job ever since. 🙂

Your DARWIN NSC has obtained a good return after its migration to Darwinex however it has also had a more volatile behaviour than before migration. Could you explain what’s the reason for this?

The most fundamental stage of development focusing on long-term profitability was finished by May 2017.
Before that, I was going through a period of live trading on a several-10k USD account. I’ve experienced what it’s like to “go into battle” alongside an infallible machine 24 hours a day, 5 days a week which is doing exactly what it’s been told to do, all the time. It’s been a valuable learning period of facing tough dilemmas and earning good experience.

I eventually succeeded to create a logic based on tests which is now capable of achieving constant profit over any 6 month period based on every accessible dataset back to 2007. Including the period when my live accounts where facing losses.

The reason for the inconsistency was the difference between trading manually and by a robot. If my current robot would’ve been running from the beginning with the most recent settings, I wouldn’t have had to bear the same losses and who knows where the returns would be by now? 🙂
All is going well ever since and I’ve much more time to spend with my family now.

You only trade the EURUSD. What does this asset offer you that don’t offer other assets? Have you thought about introducing other instruments into NSC?

My algorithm is following large-scale fractal-based patterns found in nature. For this reason it requires the same large scale of input parameters.
In the context of the market this means the trading volume and volatility of the asset. Several currency pairs comply with these requirements but among all of those I have found EURUSD has the best yield with the lowest risk, based on both tests and live trading. It has a really good profit/loss ratio.

We’ve observed that the beginning of the week is usually not positive for NSC. What do you think is the reason for this?
I think it is irrelevant in short terms. Tests based in 10+ years of historical data show in the long term it’s best to keep trading.
In spite of having 36% of profitable trades, your DARWIN has obtained a profit of almost 50% due to the fact that you let winning positions run longer than losing ones – which is why you have such a good Loss Aversion score. Is it difficult to bear 64% of losing trades? Has this been a characteristic of your trading from the beginning?

It’s an old rule, “let winning positions run their course and keep your losses in bay”.
I am merely following it and the time spent in a trade clearly shows this. There is always a target and a stop. We simply can not decide, which one will be hit and when.

It takes patience to realize that you can earn nice profit even with a 36% success rate, if the system is sound.

It was always clear what the robot is capable of in a good trading environment. Tests clearly showed that after several trades with losses it was always able to earn it back several-fold with a few good trades. It is an attribute of it, quite similar to many phenomena of nature.

Having a clearly winning strategy, it surprises us that you’ve only $ 700 invested in it. What’s the reason for this? Don’t you think you could attract more investor capital by incrementing the equity on your account?

In my opinion profitability and statistics of a system provide just enough information for any investor. It is all anyone might need to make an informed decision. I’ve created this Darwin in order to let others make their interests too.

We’ve observed that your monthly VaR has decreased from 80% to around 35-40% where it seems to have stabilized. What’s the reason for this decrease? Have you found your ideal VaR at this level?

Trading environment has simply changed over the time, which in turn helps the algorithm make a better job, as VaR clearly shows it.

But it isn’t quite a relevant factor for us in a long (3+ years) term. It was one of the reasons for making a strategic decision of closing two of the three Darwins (NSA, NSB) and only keep NSC, since this was the one with best overall performance, which is evidently attracting more investments.

As an investor, which DARWINs would you always have in your portfolio? And if you couldn’t choose from your own DARWINs?

Good question 🙂 I think they would be FSK, SKJ, TMB, ZXW.

Any books you like to recommend to fellow traders?

Of course, there were several writers who – through their work – have significantly influenced the process of creating the system. I would rather give you a list of names of those who made a good influence.

  • John von Neumann (Neumann János)
  • Laszlo Mero (Mérő László)
  • Fritjof Capra
  • James Gleick
  • Mihály Csíkszentmihályi
  • and, of course Douglas Adams 🙂

Any specific questions you would like to ask NaturalStep? Leave them as comments and we’ll try to get you the answer!

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