How it actually started
When Bitcoin first hit $1,000, I thought: I can trade this. I can make money here. It seemed obvious at the time.
I was wrong.
I started trading manually. The moment I bought something, I was checking the price every five minutes. It went down. I'd watch it go down, tell myself it would recover, and keep watching. If I wasn't in a position, I was staring at the chart trying to figure out the perfect entry. Nights, weekends, during work. It was always there in the background. It's an exhausting way to live.
Then in 2020, I put everything into a hyped-up altcoin. It lost more than 90% of its value. I lost several months of income. The feeling wasn't panic. It was that specific kind of frustration you feel when you know you should have gotten out, and you didn't.
I made two decisions that day: no more coins without real fundamentals, and no more trading without a system that's been properly tested. If I was going to do this, I was going to do it the only way I know how: automate it and let the data decide.
I'm a DevOps engineer. I automate everything. It was the obvious next step.
The process
- 2021 Started writing Bash shell scripts on Linux to backtest strategies I'd found online. Golden crosses, moving average crossovers, the usual recommendations. None of them worked. Not a single one survived proper testing. Optimized and parallelized the scripts. Got a single backtest down from 10 minutes to 1–2 minutes. Still slow, but the foundation was there.
- 2022 Narrowed the focus to BNB/USDT - the most promising pair across all early tests, and the one showing the strongest potential for a clean, consistent edge.
- 2023 Upgraded to a more powerful machine dedicated solely to running backtests - 24/7, without interruption.
- 2024 Rewrote the backtester in Python and added a web interface. Multithreading brought a single test down to ~1 second, but the web layer introduced new bugs and slowed down development. Scrapped it.
- 2025 Rebuilt the entire engine in C. A single backtest across 8 years of data now runs in 0.005 seconds. Over 30 base strategies and 20+ filters tested, but never stacked blindly. Adding too many filters at once either caused overfitting or simply stopped working. The final configuration uses only 2-3 filters, each earning its place independently.
- 2026 One strategy survived. Profitable in backtesting and out-of-sample validation across every test period. By this point, tens of millions of parameter combinations had been run across those five years - each one a data point, not a guess. That's what powers the edge updates on this site.
The backtester running 1.25M parameter combinations at 512 tests/sec
Why BNB, BTC, and ETH?
I don’t believe in "one-size-fits-all" algorithms. Different markets exhibit different structural behaviors. My primary focus began with BNB/USDT: it is the pair where my engine identified the most stable statistical edge, with a backtested 94.65% Win Rate and a 3.87 Profit Factor. It remains the core of my personal allocation.
The logic has proven its robustness on BTC/USDT as well, though it operates with a distinct mathematical profile. It is highly selective: while it triggers fewer Edge Updates on average, the data shows a 95.56% Win Rate with a higher Profit Factor and a reduced maximum drawdown (-19.2%). This configuration prioritizes a stable equity curve over frequency.
Recently, ETH/USDT has been fully integrated into the live engine after meeting all stability criteria. It follows the same "slow and steady" engineering approach. Looking ahead, SOL/USDT is currently in the deep-testing phase, targeting Q3 2026. The roadmap is strictly data-driven: a new pair is only added if it demonstrates a sustained mathematical edge under stress tests.
I utilize this tool for my own capital management. Providing these Edge Updates in real-time is a logical extension of my workflow. This allows users to access high-precision technical data without the emotional burden of constant market monitoring.
The model is simple: the engine provides the data from the horizon, but the final decision remains with the user. Every backtest result is verified; every live trade is logged publicly. If the system's performance drifts from the data, the numbers will reflect it immediately.
I trade the strategy myself. Sharing the edge updates is almost no additional work, and it turns five years of development into something that pays for itself. Members receive the edge updates in real time. That's the whole model.
Every backtest result on this site is real. Every live trade is logged publicly. If the system stops working, you'll see it in the numbers before I say a word.