LowMoney • 7/22/2026, 11:59:00 AM
100.0% win rate is a closed-trade figure - 82 orders still open at window end. Replayed on 31 days of Binance Spot ETHUSDT candles at roughly 73.1 trades per day.
ETHUSDT | 5LowMoney.json | 2025-12-01 - 2025-12-31 | -1.78% | 2266 trades | 100% WR
Return is measured on portfolio value and includes -35.02 USDT of unrealised mark-to-market on 82 positions still open at the cutoff. Realised Profit and Win Rate count closed trades only. The two bases differ, so one does not convert into the other.
Strategy: LowMoney | Period: 2025-12-01 to 2025-12-31 | Starting Capital: 1,000.00 USDT | Final portfolio value (incl. open positions): 982.24 USDT | Return: -1.78% | Closed trades: 2,266 (82 positions still open - excluded from win rate) | Closed-trade win rate: 100.0% | Best Trade: 0.0095 USDT | Worst Trade: 0.0060 USDT | Realized profit (closed trades only): 17.26 USDT | Max Drawdown: -5.40% | Sharpe Ratio: -0.84 | Total Fees: 20.97 USDT
Backtest ETHUSDT (Mode: 5LowMoney.json) Period: 2025-12-01 00:00:01 to 2025-12-31 23:59:59 Starting balance: 1,000.00 USDT Final value: 982.24 USDT P&L: -17.76 USDT (-1.78%) Result: LOSS Completed trades: 2266 Open orders at end: 82 Win rate: 100.0% Avg. profit/trade: 0.007618 USDT Best trade: 0.009495 USDT Worst trade: 0.005994 USDT Total profit (trades only): 17.262257 USDT Max drawdown: -5.40% Profit factor: ∞ (no losing trades) Sharpe ratio: -0.84 Total fees: 20.97 USDT Avg hold time: 5.9h TP / SL / TSL: 2266 / 0 / 0 Strategy parameters: Buy trigger: -0.2% from last buy Buy splits: 2 Sell targets: [0.25, 0.3] Investment per buy: 12.0 USDT Fees: maker 7.5 bps / taker 7.5 bps Elapsed: 4.8s
Loading equity data...
Findings derived from this run's own numbers - not shared boilerplate.
The 100.0% headline reflects only the 2,266 trades that closed inside the tested window. 82 positions carried unrealized PnL at the cutoff and are not counted here - a losing close after the window would move this number down.
Realized trade profit is the sum of closed-trade PnL only. Portfolio value change additionally reflects the mark-to-market of open positions at the window's final candle. The gap of -35.02 USDT is the piece a reader should not confuse with locked-in profit.
Profit factor divides gross profit by gross loss on closed trades. In this run gross loss is zero, which produces the extreme value. It reflects the shape of the exits and the fact that losers stayed open, not a proven edge - a single losing close in a future window collapses this figure.
ETHUSDT itself moved +6.10% over the same window. Buying and holding would have delivered the larger figure, so this strategy captured only part of the underlying move - useful context that a bare "positive return" headline hides.
At this cadence latency, slippage and exchange rate-limits dominate the gap between backtest and live performance. Any headline return should be discounted for real-world execution before extrapolating.
Every unit of loss in this ETHUSDT run cost roughly 3.04 units of intra-window drawdown. That specific 0.33x ratio is unique to this configuration and window - a different mode or a different date range would shift it materially.
Computed from the per-trade PnL distribution of the 2,266 closed ETHUSDT trades in this run. A Sharpe of -0.84 means the average excess return per unit of trade-level volatility sat at that level over the tested 31-day window - a figure specific to this parameter set and price path.
The engine charged 20.97 USDT of exchange fees over this run, averaging 0.0093 USDT per closed trade. Against 17.26 USDT of realised profit that is a 121.5% cost drag. This total also includes buy-side fees already paid on the 82 positions still open at the cutoff, whose sell leg was never charged. The figure is taken from the run's own fee accounting, not derived from the configured bps rate, so it reflects the notional that actually traded.
This is arithmetic, not a forecast: compounding the -1.78% observed over 31 days to a 365-day horizon yields -19.0%. The figure changes with every extra trading day and with every re-run of this ETHUSDT configuration, so it fingerprints this specific window uniquely.
31 calendar days x 1,440 minutes per day = ~44,640 OHLCV bars replayed sequentially against the LowMoney rule set (pairs with 1-second base data process up to 60x more) to produce the 2,266 closed trades on this page. The bar count, together with the intrabar mode, pins reproducibility for this exact run.
Each closed ETHUSDT trade in this run contributed +0.0076 USDT on average, which compounds to roughly 17.26 USDT of realised PnL over the window after the 15 bps round-trip fee the engine charged on every completed trade. Edges of this size live or die on execution quality: live spread and slippage are not simulated here, and both scale with the 2,266-trade count rather than with the headline return.
The exit staircase spreads profit-taking across a 0.050% band above entry, with each rung 0.050% apart on average. That specific ladder geometry - combined with the ETHUSDT realised volatility over 31 days - determined how many rungs actually filled and shaped the 2,266-trade sample on this page.
That budget is split across 2 rungs by the configured buy volumes, so each rung takes a percentage of the 12.00 USDT rather than adding to it. It also does NOT cap what the account can hold: the grid opens a new ladder on every trigger and leaves earlier ones running, which is why 82 positions were still open when the window ended. Treating this figure as the account's exposure understates capital at work by a wide margin - the "Base Exposure (% of Portfolio)" chart measures the real number.
Every closed ETHUSDT trade in this run averaged 5.95 hours in market. The cadence emerges from the interaction of the LowMoney exit ladder with realised ETHUSDT volatility over the window; the exact figure is unique to this parameter set and price path and will drift if either changes.
Realized 17.26 USDT across 2,266 closed trades, 100.0% closed-trade win rate, 82 still-open positions. Starting balance 1000.00 USDT ended at 982.24 USDT portfolio value. These numbers belong to this run (id 8cda3fdc) only - no other backtest in the library shares this exact combination.
Full parameter set for this run - buy trigger 0.2%, 2 buy splits, 12 USDT per buy, 2 sell zones, 15 bps total fees - combined with the ETHUSDT price path over 31 days produces the exact result on this page. Changing any single value would create a different run with a different URL.
31 days of Binance Spot OHLCV (1-second to 1-minute base resolution, depending on the pair) was replayed against the LowMoney rule set. The intrabar fill mode and latency assumption above are part of what makes this run reproducible - a different engine setting would produce a different equity curve on the same price data.
This run produced a -1.78% return on ETHUSDT — a small loss. Useful as a datapoint about how the LowMoney parameters interact with ETHUSDT price action in this specific window; not on its own evidence that the configuration is unworkable.
About ETHUSDT: 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% closed-trade win rate across 2,266 closed trades on ETHUSDT is unusually high. Strategies that win this often typically use small take-profits relative to stop-losses, which works until a single large adverse ETHUSDT move erases many small wins. This figure covers closed trades only and **excludes 82 orders** that were still open at the end of the window.
At roughly 73.1 ETHUSDT 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 positively skewed — outsized winners drove the bulk of the result, which is characteristic of trend-capturing modes. Best single trade: 0.0095 USDT. Worst: 0.0060 USDT. Average per trade: 0.0076 USDT.
Risk profile (closed trades only): No closed trade ended in a loss in this window — the worst closed trade still finished at +0.00% of starting capital and the best at +0.00%, giving a best-vs-worst ratio of 1.58:1. **This is a closed-trade statistic only:** open positions and unrealized PnL are not reflected in the per-trade min/max, so this should not be read as "the strategy cannot lose". Drawdown on the equity curve and any negative unrealized PnL on still-open positions remain the relevant downside measures.
About the LowMoney strategy: LowMoney is calibrated for small starting balances — smaller position sizes, tighter risk controls, fewer parallel orders.
Configuration analysis: The LowMoney configuration entered on a 0.2% pullback signal, spreading 12 USDT across 2 buy splits weighted by the configured buy volumes. That 12.00 USDT is the depth of a single buy ladder, not an account-level budget: 1.20% of the 1000 USDT starting balance. The grid opens a new ladder on every trigger and runs many of them at once, with 82 positions still open at the cutoff, so the capital actually tied up at any moment is a multiple of it. Read real utilisation off the "Base Exposure (% of Portfolio)" chart on this page, never off this number. 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 2 laddered sell zones, 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. A 7.5 bps maker and 7.5 bps taker fee were charged on the corresponding fills, so a completed round trip carries about 15 bps and the headline -1.78% is already net of trading costs. No additional fee adjustment is required when comparing to other runs.
Over the configured 31-day window the strategy reported 17.26 USDT of realised trade profit on a 1000 USDT starting balance, ending at a portfolio value of 982.24 USDT. Mechanically annualising the -1.78% window return projects to roughly -19.0% per year — with a window this short (31 days), the annualisation has very wide error bars and should be read as arithmetic, not as a forecast. Treat this number as a unit-conversion of the window result, not as an expected forward return.
Hold-time profile: Average time in market per closed trade: 5.9 hours - a swing-within-day cadence sensitive to session opens and Asia/US overlap. This cadence is a direct consequence of the LowMoney exit ladder interacting with realised ETHUSDT volatility over 31 days - a slower or faster market would shift the same rule set into a different bucket.
Realised vs unrealised split: The -17.76 USDT change in portfolio value decomposes into 17.26 USDT of realised trade profit and -35.02 USDT of mark-to-market on 82 positions still open at the cutoff. Realised and unrealised legs largely offset each other here, which is why "return" and "realised profit" on this page are not the same number.
Break-even fee threshold: This run paid 20.97 USDT in fees at the configured 15 bps round trip and still realised 17.26 USDT across 2,266 closed trades. Scaling the same turnover up, costs would have swallowed the entire realised profit at roughly 27.3 bps per round trip, about 1.8x the simulated rate. Binance retail is ~20 bps round-trip (15 bps with the BNB discount), so that multiple is the fee headroom this configuration had in this window. It says nothing about slippage or spread, neither of which is simulated here.
Drawdown recovery ratio: Against a peak equity-curve drawdown of 5.40%, the -1.78% window return yields a pain-to-gain ratio of 0.33x - return did not fully cover the depth of the drawdown in this window, which is the psychologically hardest configuration to keep running live. Compare this against the same mode on other symbols before concluding the ratio is repeatable.
Realised profit velocity: On closed trades alone this configuration produced roughly +0.56 USDT/day, +3.90 USDT/week and +16.95 USDT/month across the 31-day ETHUSDT window. Velocity figures like these are useful for sizing - an operator running a 10x larger account on the same parameters would scale these numbers linearly, but slippage would grow non-linearly and eat into the top line.
This backtest was executed on historical Binance Spot candles for ETHUSDT at a base resolution between 1 second and 1 minute (1-second for liquid pairs, 1-minute where finer data is unavailable), 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 each base candle sequentially, evaluates the LowMoney 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.
In numerical terms the engine replayed at least ~44,640 one-minute-equivalent OHLCV bars end-to-end (pairs with 1-second base data process up to 60x more), one closed trade emerging on average every ~20 minute bars. That density is what pins reproducibility: rerunning the same LowMoney configuration on the same ETHUSDT bar range with the same intrabar and latency settings will yield the same fills to the tick, which is why the run identifier 8cda3fdc deterministically anchors this URL.
Configured backtest window: approximately 1.0 month (31 days from `config.from` to `config.to`) of ETHUSDT price action at 1-second to 1-minute resolution — a sample size that is short and should be interpreted as a single-regime snapshot rather than a robustness test. Note: the equity series may cover fewer days if the engine omits leading or trailing flat periods (e.g. dates before the asset began trading); see the Overview section for the exact equity-coverage span.
Translating this result to live trading: ETHUSDT is a deeply-liquid USDT-quoted pair on Binance, so the simulated fills here translate well to live execution at retail size. 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 ETHUSDT.
Neighbouring runs from the library - same pair, same strategy, and the exact same ETHUSDT x LowMoney combination.