FullBullMarket • 5/26/2026, 9:22:01 PM
AGLDUSDT | 1FullBullMarket.json | 2021-01-01 - 2021-12-31 | -46.58% | 11979 trades | 100% WR
Strategy: FullBullMarket | Period: 2021-01-01 to 2021-12-31 | Starting Capital: 10,000.00 USDT | Final Value: 5,341.57 USDT | Return: -46.58% | Trades: 11,979 | Win Rate: 100.0% | Best Trade: 1.8190 USDT | Worst Trade: 0.0120 USDT | Total Profit: 2,554.44 USDT | Max Drawdown: -59.74% | Sharpe Ratio: -1.23 | Total Fees: 226.24 USDT
Backtest AGLDUSDT (Mode: 1FullBullMarket.json) Period: 2021-01-01 00:00:01 to 2021-12-31 23:59:59 Starting balance: 10,000.00 USDT Final value: 5,341.57 USDT P&L: -4,658.43 USDT (-46.58%) Result: LOSS Completed trades: 11979 Open orders at end: 871 Win rate: 100.0% Avg. profit/trade: 0.213243 USDT Best trade: 1.818954 USDT Worst trade: 0.011978 USDT Total profit (trades only): 2,554.437562 USDT Max drawdown: -59.74% Profit factor: ∞ (no losing trades) Sharpe ratio: -1.23 Total fees: 226.24 USDT Avg hold time: 10.4h TP / SL / TSL: 11979 / 0 / 0 Strategy parameters: Buy trigger: -0.1% from last buy Buy splits: 6 Sell targets: [0.25, 2.5, 5.0, 10.0, 20.0, 30.0] Investment per buy: 60.0 USDT Fees: maker 7.5 bps / taker 7.5 bps Elapsed: 318.8s
This run produced a -46.58% return on AGLDUSDT — a clear loss in the tested window. Useful primarily as a negative datapoint about parameter combinations that did not fit AGLDUSDT market conditions over these dates.
About AGLDUSDT: AGLDUSDT 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 11,979 closed trades on AGLDUSDT is unusually high. Strategies that win this often typically use small take-profits relative to stop-losses, which works until a single large adverse AGLDUSDT move erases many small wins. This figure covers closed trades only and **excludes 871 orders** that were still open at the end of the window.
At roughly 32.8 AGLDUSDT 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: 1.8190 USDT. Worst: 0.0120 USDT. Average per trade: 0.2132 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 +0.02%, giving a best-vs-worst ratio of 151.86:1. **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 FullBullMarket strategy: FullBullMarket is tuned for sustained uptrends — it scales position size into rising markets and gives winners room to run. It tends to underperform in choppy or bear conditions.
Configuration analysis: The FullBullMarket configuration entered on a 0.1% pullback signal across 6 potential buy splits at 60 USDT each. Total deployable notional is therefore 360 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 6 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 -46.58% 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 2554.44 USDT of realised trade profit on a 10000 USDT starting balance, ending at a portfolio value of 5341.57 USDT. Mechanically annualising the -46.58% window return projects to roughly -46.6% 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 AGLDUSDT 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 FullBullMarket 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 AGLDUSDT 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: AGLDUSDT 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 AGLDUSDT.
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