LongTimeLong • 4/19/2026, 5:13:49 PM
100.0% win rate is a closed-trade figure - 5 orders still open at window end. Replayed on 365 days of Binance Spot USDPUSDT candles at roughly 0.23 trades per day.
USDPUSDT | 3LongTimeLong.json | 2025-01-01 - 2025-12-31 | +0.00% | 85 trades | 100% WR
Strategy: LongTimeLong | Period: 2025-01-01 to 2025-12-31 | Starting Capital: 10,000.00 USDT | Final portfolio value (incl. open positions): 10,000.41 USDT | Return: +0.00% | Closed trades: 85 (5 positions still open - excluded from win rate) | Closed-trade win rate: 100.0% | Best Trade: 0.0062 USDT | Worst Trade: 0.0054 USDT | Realized profit (closed trades only): +0.49 USDT | Max Drawdown: -0.00% | Sharpe Ratio: 1.62 | Total Fees: 0.71 USDT
Backtest USDPUSDT (Mode: 3LongTimeLong.json) Period: 2025-01-01 00:00:01 to 2025-12-31 23:59:59 Starting balance: 10,000.00 USDT Final value: 10,000.41 USDT P&L: +0.41 USDT (+0.00%) Result: PROFIT Completed trades: 85 Open orders at end: 5 Win rate: 100.0% Avg. profit/trade: 0.005820 USDT Best trade: 0.006160 USDT Worst trade: 0.005420 USDT Total profit (trades only): 0.494723 USDT Strategy parameters: Buy trigger: -0.1% from last buy Buy splits: 9 Sell targets: [0.25, 0.35, 0.5, 0.75, 1.0, 2.5, 5.0, 10.0, 15.0] Investment per buy: 25.0 USDT Fees: maker 7.5 bps / taker 7.5 bps Elapsed: 22.3s
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Findings derived from this run's own numbers - not shared boilerplate.
The 100.0% headline reflects only the 85 trades that closed inside the tested window. 5 positions carried unrealized PnL at the cutoff and are not counted here - a losing close after the window would move this number down.
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.
Computed from the per-trade PnL distribution of the 85 closed USDPUSDT trades in this run. A Sharpe of 1.62 means the average excess return per unit of trade-level volatility sat at that level over the tested 365-day window - a figure specific to this parameter set and price path.
The engine charged 0.71 USDT of exchange fees over this run, averaging 0.0084 USDT per closed trade. Against 0.49 USDT of realised profit that is a 144.4% cost drag. This total also includes buy-side fees already paid on the 5 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 0.00% observed over 365 days to a 365-day horizon yields +0.0%. The figure changes with every extra trading day and with every re-run of this USDPUSDT configuration, so it fingerprints this specific window uniquely.
365 calendar days x 1,440 minutes per day = ~525,600 OHLCV bars replayed sequentially against the LongTimeLong rule set (pairs with 1-second base data process up to 60x more) to produce the 85 closed trades on this page. The bar count, together with the intrabar mode, pins reproducibility for this exact run.
Each closed USDPUSDT trade in this run contributed +0.0058 USDT on average, which compounds to roughly 0.49 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 85-trade count rather than with the headline return.
The exit staircase spreads profit-taking across a 14.750% band above entry, with each rung 1.844% apart on average. That specific ladder geometry - combined with the USDPUSDT realised volatility over 365 days - determined how many rungs actually filled and shaped the 85-trade sample on this page.
That budget is split across 9 rungs by the configured buy volumes, so each rung takes a percentage of the 22.50 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 5 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 USDPUSDT trade in this run averaged 7.83 days in market. The cadence emerges from the interaction of the LongTimeLong exit ladder with realised USDPUSDT volatility over the window; the exact figure is unique to this parameter set and price path and will drift if either changes.
Realized 0.49 USDT across 85 closed trades, 100.0% closed-trade win rate, 5 still-open positions. Starting balance 10000.00 USDT ended at 10000.41 USDT portfolio value. These numbers belong to this run (id df07eb93) only - no other backtest in the library shares this exact combination.
Full parameter set for this run - buy trigger 0.1%, 9 buy splits, 25 USDT per buy, 9 sell zones, 15 bps total fees - combined with the USDPUSDT price path over 365 days produces the exact result on this page. Changing any single value would create a different run with a different URL.
365 days of Binance Spot OHLCV (1-second to 1-minute base resolution, depending on the pair) was replayed against the LongTimeLong 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 0.00% return on USDPUSDT — a small positive result. Outcomes in this range are within the noise band of typical backtest variance and should not be over-interpreted as evidence of edge.
About USDPUSDT: USDPUSDT is a stablecoin-quoted spot pair on Binance. Quote-side liquidity is deep, so slippage assumptions in this backtest map reasonably well to live execution at retail size.
An 100.0% closed-trade win rate across 85 closed trades on USDPUSDT is unusually high. Strategies that win this often typically use small take-profits relative to stop-losses, which works until a single large adverse USDPUSDT move erases many small wins. This figure covers closed trades only and **excludes 5 orders** that were still open at the end of the window.
Trade frequency of about 0.23 USDPUSDT trades per day is conservative — the bot waits for higher-quality setups, trading roughly 30 times a week.
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: 0.0062 USDT. Worst: 0.0054 USDT. Average per trade: 0.0058 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 1.14:1. **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 LongTimeLong strategy: LongTimeLongMoreProfit holds positions longer to capture larger swings. It accepts deeper drawdowns in exchange for higher per-trade payoff.
Configuration analysis: The LongTimeLong configuration entered on a 0.1% pullback signal, spreading 25 USDT across 9 buy splits weighted by the configured buy volumes. That 22.50 USDT is the depth of a single buy ladder, not an account-level budget: 0.22% of the 10000 USDT starting balance. The grid opens a new ladder on every trigger and runs many of them at once, with 5 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 9 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 0.00% is already net of trading costs. No additional fee adjustment is required when comparing to other runs.
Over the configured 365-day window the strategy reported 0.49 USDT of realised trade profit on a 10000 USDT starting balance, ending at a portfolio value of 10000.41 USDT. Mechanically annualising the 0.00% window return projects to roughly +0.0% per year — the window covers roughly one full year, so the annualised figure is closer to the realised pace than to an extrapolation, but a single year still represents a single market regime. 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: 7.8 days - long-horizon holds where broader USDPUSDT regime dwarfs entry-timing precision. This cadence is a direct consequence of the LongTimeLong exit ladder interacting with realised USDPUSDT volatility over 365 days - a slower or faster market would shift the same rule set into a different bucket.
Break-even fee threshold: This run paid 0.71 USDT in fees at the configured 15 bps round trip and still realised 0.49 USDT across 85 closed trades. Scaling the same turnover up, costs would have swallowed the entire realised profit at roughly 25.4 bps per round trip, about 1.7x 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.
This backtest was executed on historical Binance Spot candles for USDPUSDT 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 LongTimeLong 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 ~525,600 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 ~6,184 minute bars. That density is what pins reproducibility: rerunning the same LongTimeLong configuration on the same USDPUSDT bar range with the same intrabar and latency settings will yield the same fills to the tick, which is why the run identifier df07eb93 deterministically anchors this URL.
Configured backtest window: approximately 12.0 months (365 days from `config.from` to `config.to`) of USDPUSDT price action at 1-second to 1-minute resolution — a sample size that is large enough to span multiple short-term regimes. 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: USDPUSDT is a deeply-liquid USDT-quoted pair on Binance, so the simulated fills here translate well to live execution at retail size. Lower trade frequency keeps slippage drag minimal, so live results should track the backtest more closely than a high-frequency configuration would. 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 USDPUSDT.