How would YOUR money have grown?
Enter a starting amount and pick how aggressive your sizing is. We replay every resolved call in order, compounding the position-sized return on each, to show what a disciplined account would have looked like.
Fraction of the account exposed to each call. 10% is a common disciplined default; 50% is aggressive.
You're not buying a crystal ball, you're buying discipline.
Ezath isn't magic. It's a system designed around consistency over magnitude - high win rate, tightly capped losses, small per-trade outcomes with risk defined before entry. The same playbook institutional quant desks use, stripped down so a retail trader can actually run it. That discipline is the edge — and no edge makes losses impossible.
Every call comes from the same deterministic engine, multiple technical indicators (EMA200, RSI, MACD, ATR, volume) scored against each other. No human emotion, no FOMO, no panic. The same inputs always produce the same output.
Every signal ships with a stop-loss and a take-profit target computed from ATR (volatility). You know exactly how much you can lose before you enter. That's what makes risk manageable.
Every single call the engine has ever made is recorded, winners and losers, across all three timeframes we trade (1-hour, 4-hour and 1-day). Nothing is hidden; this page is the whole dataset.
Most of the time, the answer is WAIT. We only fire a signal when conviction crosses a threshold, typically a few calls per coin per week. Fewer, higher-quality trades beat dozens of mediocre ones.
We don't compete on biggest single wins. As a hypothetical, a 65% win-rate system compounding ~1% per trade beats 'one 50x trade per month' systems that quietly post -50% loss days. The math is unsexy — small edges, repeated and compounded, similar in spirit to how institutional quant desks operate. Our actual numbers are in the ledger above.
Common questions
Why not 100% win rate?▾
Anyone selling you a 100% win-rate strategy is lying. Markets are probabilistic, the best traders in the world are wrong 30–50% of the time. What matters is that the average win is bigger than the average loss, and that you follow every signal, not just the ones you like.
Why are the per-trade returns so small? Other services advertise 50%+ wins.▾
Per-trade returns of 0.5–2% (spot) are an intentional design choice, not a limitation. High-magnitude returns require high variance, and high variance is what blows accounts up. The systems advertising '100x setup' wins quietly take 50%+ drawdowns on losing weeks; their lifetime expectancy is often negative once you account for the deletes. Our profile is closer to how institutional quant desks actually operate: small per-trade edges, repeated thousands of times, compounded over years. Some traders apply leverage to amplify the moves — be aware that leverage amplifies losses exactly the same way and adds liquidation risk that can trigger before a published stop. If you use it, understand your exchange's margin and liquidation math first, and read the Risk Disclaimer.
What can we learn from this data?▾
The track record tells you two things: how often the engine is right, and what the average win and loss look like. Use it to size your positions, set your expectations, and decide which timeframes match your style. The longer the dataset grows, the more reliable each statistic becomes.
What about drawdown?▾
Every strategy has losing streaks. The simulator above shows the worst drawdown in the backtest, that's the pain you'd have had to sit through. If it scares you, size smaller.
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