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~/backtests/na-gj-l-003 backtest

$ cd /evidence  ·  evidence archive

Backtest evidence

Bootes

code: NA-FX-015 GBPJPY_Oanda H1 2006-01-01 → 2026-06-19
net $13,655 trades 569 win 47.63%
Verified · OTS443ff57188bb…
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at-a-glance --summaryok

$ stats --glance

headline performance at a glance

net_profit
Total net profit $13,655
gross profit$39,137
gross loss$25,482
win_rate
47.63%WIN
█████░░░░░
Win rate
271W / 298L
profit_factor
1.54PF
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Profit factor
gross P / gross L
cagr
4.40%CAGR
█░░░░░░░░░
CAGR
annualized
max_drawdown
-11.45%MAX DD
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Max drawdown
$1,310
equity_curve --renderok

$ plot --equity

cumulative account equity over the test window

Stored snapshot: 569 points; starts at $10,262.93, ends at $23,654.54; observed range $10,029.13–$23,911.53.

x: time · y: equity (USD)● rendered by na-backtest-charts

$ plot --drawdown

underwater equity (peak-to-trough), in account currency — risk per trade is a fixed dollar amount, so a percent axis would shrink every year as the balance grew

x: time · y: drawdown (USD)● rendered by na-backtest-charts
trade_breakdown --analyzepartial

$ trades --breakdown

win/loss split, averages, and streaks

win_loss_split
47.63%win
Wins271
Losses298
Total569
win_vs_loss_size
Avg win$144.42
Avg loss$85.51
Largest win$280.96
Largest loss-$204.60
key_ratios
Profit factor1.54
Win/Loss ratio0.91
Payout ratio1.69
Expectancy$24.00
Avg trade$24.00
Bars in trade22.55
streaks
Max consec wins8
Max consec losses8
Avg consec wins1.94
Avg consec losses2.13
Long vs short breakdown and per-trade distributions are not in the ingested dataset yet.
full_statistics --allok

$ stats --full

complete metric set, grouped by category

$13,655
Net profit
$39,137
Gross profit
$25,482
Gross loss
4.40%
CAGR
6.50
AHPR
$683
Yearly avg profit
$56
Monthly avg profit
$1.83
Daily avg profit
6.83%
Yearly avg return
3.95%
Exposure
569
Trades
$24.00
Avg trade
run.configok

$ cat run.config

parameters used for this run

instrumentGBPJPY_Oanda
timeframeH1
period start2006-01-01
period end2026-06-19
profit in pips7076.2 ticks
strategyview →
Trading financial instruments carries a high level of risk and may not be suitable for all investors. Past performance — including backtested and simulated results — is not indicative of future results. NeuronAlgo provides research and tooling, not financial advice.
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Generated from stored backtest metrics · NeuronAlgo research desk

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