ForexBot's Journey from Inspiration to Implementation

The initial spark was lit in 2013. That year, I came across an old but wisdom-filled book by DiNapoli. I wasn’t a trader yet — I was a researcher, a programmer, a restless mind. I was fascinated by the idea that beneath the market’s uncertainty there might be a hidden structure — a “rhythm” that could be decoded.

I began turning those ideas into algorithms. I wrote code nonstop, testing rules, trying to explain why the market moved the way it did. But my first backtests were disappointing. The system didn’t perform. It wasn’t ready — and perhaps neither was I.

And yet... I didn’t quit. I set the project aside — not because it failed, but because it hadn’t matured yet. The idea didn’t die — it went into hibernation. Something deeper had been planted: the need to understand.

Almost five years had gone by. In 2018, I returned to that same book — but with new eyes. I had matured — not only as a programmer, but also as a person. I had already experienced failures, doubts, and change. And that’s when it hit me: I was no longer searching for the “perfect system.” The truth lay elsewhere.

I began observing market behavior without bias. Not “what RSI or MACD says,” but how people react when news comes out, when uncertainty hits, when fear and greed take over. The market was a mirror of the crowd — and the crowd, a predictable organism.

That was the turning point. I wasn’t looking for signals anymore — I was searching for reaction patterns. The goal was no longer to predict the future — but to understand the dynamics of the present. My coding became simpler, cleaner. One step closer to the “language” of the market.

In 2019, after a long period of observation and coding adjustments, I decided to test my idea in "live-like" conditions for the first time. I opened a demo account — not with profit in mind, but to see whether my algorithms could react, adapt, and “communicate” with the market.

The first results were impressive. Not because they were consistently profitable — but because the bot’s behavior was consistent. It focused on moments of tension, not trying to follow a “trend,” but rather to engage with the market’s emotional movement.

After years of testing and internal maturation, the time came for the next step: the first real-money account. It was a period of doubt, excitement, and control. I had fully automated the system and decided to observe how it would perform in a real-money environment.

December 2023 was the first month where everything "clicked". I had already executed 200+ trades, maintained consistent discipline, and — most importantly — witnessed a strong convergence between the backtest and the live results. There were no surprises, no chaos. It felt like the strategy had developed a personality of its own.

What was born then wasn’t just a bot. It was the outcome of a decade of observation, coding, and psychological conditioning. A system that doesn’t predict — but observes and reacts.

When it came time to evolve the system, I didn’t change the logic. I simply diversified the way it was applied. I created two core versions of the same system: one focused on maximum return with high drawdown (v13.10), and one that preserved the core but limited the risk (v13.13).

It was a critical decision, because by then I was thinking not just as a trader — but as a capital manager. The goal was no longer to "make the most," but to implement systems with different levels of risk tolerance.

The logic remained the same: the market reacts. But the way I observed it adapted — to speak to different profiles of people. And in that way, ForexBot stopped being a personal experiment and became a tool for real capital.

By 2025, everything had changed — and yet, nothing had. The strategy kept functioning with consistency. I didn't add new rules or make “improvements.” On the contrary, I learned to step back from the obsession with perfection — and simply observe.

My role is no longer that of a creator, but of an observer. The system is now autonomous, with predictable behavior, calibrated risk, and performance aligned with its statistics. It doesn’t need “inspiration” — it needs discipline, periodic review, and silence.

I realized that true “optimization” is not in the code — it's in the human behind it. The more I removed from the system, the more clearly it worked. And the less I interfered, the wiser it behaved.

💲 We trade our time for money.
❤️ We trade our time for love.
🔥 We trade our time for passion.
🌍 We trade our time for travel.
⚡ We trade our time for adrenaline.

But there are a few — just a few — who make that trade consciously. Who don’t waste time, but invest it. Not only in money, but in relationships, experiences, and life itself.

ForexBot is the result of such a trade. It doesn’t promise profits. It doesn’t predict the future. It observes the present — and acts only when it must.

🎯 Just as a person should.