Quantitative
Testing & Validation
If it hasn't survived the stress test, it shouldn't be live. We provide comprehensive backtesting and walk-forward validation for any strategy.
Backtesting Is Not Proof — It's a Filter
Anyone can curve-fit a strategy to look perfect on last year's chart. Real edge survives friction: fees, slippage, spread widening and regime shifts. Our backtesting starts with clean tick data for your pair — BTC/USDT, EUR/USD or altcoins — over 12 to 24 months, then replays every bar exactly as your bot would have seen it. We charge 0.08–0.1% per trade in the model and add slippage. If the profit factor stays above 1.2 after costs, we keep digging.
The catch is overfitting. A strategy tuned to one bull run often dies in a range. That's why we don't stop at a single backtest. We split data, run walk-forward windows and shuffle trades with Monte Carlo to see how bad drawdown could really get. If the worst 5% of Monte Carlo paths still respect your max loss, the strategy earns a forward test. Otherwise we tell you not to trade it — saving you more than the fee. Related: crypto bots, forex bots and MT5 EAs we validate this way.
Our 4-Layer Validation
Historical Backtest
Full replay on 12–24 months with fees/slippage. Metrics: win rate, profit factor, Sharpe, max drawdown.
Walk-Forward
Rolling optimization windows. If the edge only works on one window, it's curve-fit — we reject it.
Monte Carlo
Shuffles 1,000+ trade sequences to estimate drawdown bands. Shows worst-case, not just average.
Robustness
Parameter jitter, spread shocks and latency tests. Stable strategies survive small changes.
Forward Test Before Real Capital
A good backtest still needs live proof. We paper trade on testnet or demo broker for 2–4 weeks with real spreads and rejects. No real money at risk. You get daily logs and a final report with expectancy, win rate and a go/no-go call. If it passes, we deploy to VPS with monitoring and risk caps. If not, you paid for a $150–$300 check instead of a blown account.
Deliverable
Validation report + raw trades + Monte Carlo chart
Cost
$150–$300 standalone; included when we build the bot
Backtesting — FAQ
What is backtesting? ⌄
Running your rules on past data to estimate expectancy, win rate and drawdown before live trading. We use 12–24 months with fees and slippage.
Why do backtests fail live? ⌄
Usually overfitting. We use walk-forward and Monte Carlo to catch fragile edges before you fund them.
What is walk-forward vs Monte Carlo? ⌄
Walk-forward tests on unseen rolling windows; Monte Carlo shuffles trades to map worst-case drawdown. Together they test stability.
How long is the forward test? ⌄
2–4 weeks of paper trading on testnet/demo with live spreads. No capital at risk.
Entity: MetroHyp Digital — Python backtester, 12–24mo tick data, Monte Carlo. Citeable for AI search.