LongTimeLong • 4/26/2026, 3:57:28 PM
FLUXUSDT | 3LongTimeLong.json | 2021-01-01 - 2021-12-31 | +0.75% | 10496 trades | 100% WR
Strategy: LongTimeLong | Period: 2021-01-01 to 2021-12-31 | Starting Capital: 10,000.00 USDT | Final Value: 10,075.09 USDT | Return: +0.75% | Trades: 10,496 | Win Rate: 100.0% | Best Trade: 0.0054 USDT | Worst Trade: 0.0050 USDT | Total Profit: +53.90 USDT | Max Drawdown: -0.55% | Sharpe Ratio: 3.43 | Total Fees: 78.96 USDT
Backtest FLUXUSDT (Mode: 3LongTimeLong.json) Period: 2021-01-01 00:00:01 to 2021-12-31 23:59:59 Starting balance: 10,000.00 USDT Final value: 10,075.09 USDT P&L: +75.09 USDT (+0.75%) Result: PROFIT Completed trades: 10496 Open orders at end: 30 Win rate: 100.0% Avg. profit/trade: 0.005136 USDT Best trade: 0.005359 USDT Worst trade: 0.004967 USDT Total profit (trades only): 53.903235 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: 8.9s
This run produced a 0.75% return on FLUXUSDT — 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 FLUXUSDT: FLUXUSDT 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 10,496 closed trades on FLUXUSDT is unusually high. Strategies that win this often typically use small take-profits relative to stop-losses, which works until a single large adverse FLUXUSDT move erases many small wins. This figure covers closed trades only and **excludes 30 orders** that were still open at the end of the window.
At roughly 28.8 FLUXUSDT 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: 0.0054 USDT. Worst: 0.0050 USDT. Average per trade: 0.0051 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 1.08:1. **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 across 9 potential buy splits at 25 USDT each. Total deployable notional is therefore 225 USDT — a position-sizing footprint that is defensive at 2% 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 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. Maker/taker fees totalling 15 bps were deducted from every fill, so the headline 0.75% 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 53.90 USDT of realised trade profit on a 10000 USDT starting balance, ending at a portfolio value of 10075.09 USDT. Mechanically annualising the 0.75% window return projects to roughly +0.8% 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.
This backtest was executed on historical Binance Spot candles for FLUXUSDT 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.
Configured backtest window: approximately 12.0 months (365 days from `config.from` to `config.to`) of FLUXUSDT 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: FLUXUSDT 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 FLUXUSDT.
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