MinimalMoney • 5/4/2026, 6:13:10 AM
ETHFDUSD | 6MinimalMoney.json | 2026-01-01 - 2026-04-25 | -3.05% | 12764 trades | 100% WR
Strategy: MinimalMoney | Period: 2026-01-01 to 2026-04-25 | Starting Capital: 10,000.00 USDT | Final Value: 9,694.99 USDT | Return: -3.05% | Trades: 12,764 | Win Rate: 100.0% | Best Trade: 0.0067 USDT | Worst Trade: 0.0064 USDT | Total Profit: 83.78 USDT | Max Drawdown: -9.31% | Sharpe Ratio: -0.50 | Total Fees: 251.29 USDT
The -3.05% result on ETHFDUSD is underwhelming -- the strategy lost a small portion of capital. This typically happens when the MinimalMoney mode's assumptions (volatility regime, trend direction, grid spacing) don't match the actual ETHFDUSD market conditions during the test period.
About ETHFDUSD: Ethereum sits one tier below Bitcoin in market cap and slightly above it in realised volatility. ETH pairs typically reward strategies that can hold through brief drawdowns to capture larger trend moves.
An 100.0% win rate across 12,764 trades on ETHFDUSD is unusually high. Strategies that win this often typically use small take-profits relative to stop-losses, which works until a single large adverse ETHFDUSD move erases many small wins.
At roughly 112.0 ETHFDUSD trades per day this is a high-frequency configuration -- fee drag and slippage assumptions become critical when extrapolating to live trading on Binance Spot.
The trade payoff distribution is fairly symmetric -- wins and losses are similar in magnitude, suggesting the strategy is reading market structure consistently in both directions. Best single trade: 0.0067 USDT. Worst: 0.0064 USDT. Average per trade: 0.0066 USDT.
Risk profile: Per-trade exposure was minimal -- the worst trade only cost 0.00% of starting capital. That low-risk-per-trade footprint is the signature of a tightly-sized configuration; expect smoother equity curves but also slower compounding in strong trend regimes. Best single trade contributed +0.00% to the account, giving a single-trade reward-to-risk ratio of roughly 1.05:1 between the extreme outliers.
Configuration analysis: The MinimalMoney configuration entered on a 0.1% pullback signal across 1 potential buy splits at 13 USDT each. Total deployable notional is therefore 13 USDT -- a position-sizing footprint that is defensive at 0% of starting capital -- most of the account stays in stablecoins as buffer. No hard stop-loss is configured -- the strategy relies on take-profit zones and trailing logic instead, which trades smoother behaviour for higher tail-risk in sustained downtrends. Profit is taken in 1 laddered sell zone, which scales out gradually rather than betting on a single exit price -- a structure that smooths returns at the cost of capping the very best winners. Maker/taker fees totalling 15 bps were deducted from every fill, so the headline -3.05% is already net of trading costs -- no additional fee adjustment is required when comparing to other runs.
Over the 114-day test window the strategy generated 83.78 USDT of profit on a 10000 USDT starting balance, growing the account to 9694.99 USDT. Annualised, the -3.05% return over 114 days projects to roughly -9.4% per year -- a pace that would erode capital over time if extrapolated. Crypto market regimes shift quickly, so this projection should be treated as a directional indicator rather than a forecast.
This backtest was executed on historical Binance Spot 1-minute candles for ETHFDUSD, with intrabar fill simulation in "OLHC" mode and a synthetic order latency of 2s applied to each fill to approximate real-world routing delay. The simulator processes every minute sequentially, evaluates the MinimalMoney rule set, and books fills against the next available bar -- a standard event-driven backtesting approach that avoids look-ahead bias. Equity is marked-to-market on every closed trade and aggregated into the equity curve shown above.
Test window covers approximately 3.7 months of ETHFDUSD 1-minute price action -- a sample size that is useful for spotting near-term edge but limited for regime-cycle conclusions.
Translating this result to live trading: ETHFDUSD liquidity should be checked separately -- fill assumptions can drift if the order book is thin during volatile windows. The high trade frequency means cumulative slippage and exchange-side latency will erode a few percent of the headline return over a full year -- budget for that gap. Without a hard stop-loss, the live system depends on the take-profit ladder firing during recovery legs; a prolonged downtrend without recovery will hold positions open longer than backtest aggregates suggest. Additionally, exchange downtime, API rate limits, and funding-rate changes (on perp variants) are not modelled here and should be accounted for in production deployment.
This interpretation is generated deterministically from this run's own metrics. Past performance is not indicative of future results -- a profitable backtest is necessary but not sufficient evidence that a strategy will work in live trading on ETHFDUSD.
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