BasicMode • 5/26/2026, 9:23:00 PM
RADUSDT | 4BasicMode.json | 2024-04-24 - 2026-02-25 | +40.77% | 434785 trades | 100% WR
Strategy: BasicMode | Period: 2024-04-24 to 2026-02-25 | Starting Capital: 10,000.00 USDT | Final Value: 14,077.48 USDT | Return: +40.77% | Trades: 434,785 | Win Rate: 100.0% | Best Trade: 0.3159 USDT | Worst Trade: 0.0150 USDT | Total Profit: +20,680.08 USDT | Max Drawdown: -41.51% | Sharpe Ratio: 0.60 | Total Fees: 6,773.02 USDT
Backtest RADUSDT (Mode: 4BasicMode.json) Period: 2024-04-24 00:00:01 to 2026-02-25 23:59:59 Starting balance: 10,000.00 USDT Final value: 14,077.48 USDT P&L: +4,077.48 USDT (+40.77%) Result: PROFIT Completed trades: 434785 Open orders at end: 3120 Win rate: 100.0% Avg. profit/trade: 0.047564 USDT Best trade: 0.315932 USDT Worst trade: 0.014972 USDT Total profit (trades only): 20,680.079085 USDT Max drawdown: -41.51% Profit factor: ∞ (no losing trades) Sharpe ratio: 0.60 Total fees: 6,773.02 USDT Avg hold time: 23.3h TP / SL / TSL: 434785 / 0 / 0 Strategy parameters: Buy trigger: -0.1% from last buy Buy splits: 7 Sell targets: [0.25, 0.35, 0.5, 0.75, 1.0, 2.5, 5.0] Investment per buy: 60.0 USDT Fees: maker 7.5 bps / taker 7.5 bps Elapsed: 7384.6s
The BasicMode configuration produced a 40.77% return on RADUSDT in the tested window. This is a positive single-window result; a like-for-like comparison against buy-and-hold of RADUSDT over the same dates is required to judge whether the strategy added value beyond the underlying price move.
About RADUSDT: RADUSDT 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 434,785 closed trades on RADUSDT is unusually high. Strategies that win this often typically use small take-profits relative to stop-losses, which works until a single large adverse RADUSDT move erases many small wins. This figure covers closed trades only and **excludes 3,120 orders** that were still open at the end of the window.
At roughly 646.0 RADUSDT 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: 0.3159 USDT. Worst: 0.0150 USDT. Average per trade: 0.0476 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 21.10:1. **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 BasicMode strategy: BasicMode is the balanced reference configuration — moderate position sizing, standard take-profit and stop-loss bands. It's the baseline against which other modes are compared.
Configuration analysis: The BasicMode configuration entered on a 0.1% pullback signal across 7 potential buy splits at 60 USDT each. Total deployable notional is therefore 420 USDT — a position-sizing footprint that is defensive at 4% 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 7 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 40.77% is already net of trading costs — no additional fee adjustment is required when comparing to other runs.
Over the configured 673-day window the strategy reported 20680.08 USDT of realised trade profit on a 10000 USDT starting balance, ending at a portfolio value of 14077.48 USDT. Mechanically annualising the 40.77% window return projects to roughly +20.4% 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 RADUSDT 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 BasicMode 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 22.1 months (673 days from `config.from` to `config.to`) of RADUSDT 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: RADUSDT 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 RADUSDT.
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