DGBUSDT

Completed

LongTimeLongMoreProfit4/27/2026, 5:28:22 PM

DGBUSDT | 2LongTimeLongMoreProfit.json | 2021-01-01 - 2021-12-31 | +50.14% | 347600 Trades | 100% WR

Final Value
15,014.24 USDT
Return
+50.14%
Profit
+22,933.06 USDT
Trades
347,600
Win Rate
100.0%
Open Orders
4,807
Best Trade
+0.611091 USDT
Worst Trade
+0.009968 USDT

DGBUSDT Backtest – unCoded Crypto TradingBot

Strategy: LongTimeLongMoreProfit | Period: 2021-01-01 to 2021-12-31 | Starting Capital: 10,000.00 USDT | Final Value: 15,014.24 USDT | Return: +50.14% | Trades: 347,600 | Win Rate: 100.0% | Best Trade: 0.6111 USDT | Worst Trade: 0.0100 USDT | Total Profit: +22,933.06 USDT

Strategy Configuration – LongTimeLongMoreProfit
Buy Trigger: -0.1%
Buy Splits: 8
Investment/Buy: 50 USDT
Start Balance: 10,000.00 USDT
Can Buy Up: Yes
Can Buy Down: No
Stop Loss: No
Maker Fee: 7.5 bps
Taker Fee: 7.5 bps
Sell Zones (8):
+0.25% → 20%+0.5% → 10%+0.75% → 10%+1% → 10%+2.5% → 10%+5% → 25%+10% → 10%+20% → 5%

Performance Analysis

This backtest delivered an exceptional 50.14% return on DGBUSDT -- well above what most automated crypto strategies achieve over a comparable window. Returns of this magnitude on DGBUSDT usually require a directional tailwind, a high win-rate edge, or both working in tandem.

About DGBUSDT: DGBUSDT 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% win rate across 347,600 trades on DGBUSDT is unusually high. Strategies that win this often typically use small take-profits relative to stop-losses, which works until a single large adverse DGBUSDT move erases many small wins.

At roughly 954.9 DGBUSDT 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: 0.6111 USDT. Worst: 0.0100 USDT. Average per trade: 0.0660 USDT.

Risk profile: Per-trade exposure was minimal -- the worst trade only cost 0.00% of starting capital. That low-risk-per-trade footprint is the signature of a tightly-sized configuration; expect smoother equity curves but also slower compounding in strong trend regimes. Best single trade contributed +0.01% to the account, giving a single-trade reward-to-risk ratio of roughly 61.31:1 between the extreme outliers.

About the LongTimeLongMoreProfit strategy: LongTimeLongMoreProfit holds positions longer to capture larger swings. It accepts deeper drawdowns in exchange for higher per-trade payoff.

Configuration analysis: The LongTimeLongMoreProfit configuration entered on a 0.1% pullback signal across 8 potential buy splits at 50 USDT each. Total deployable notional is therefore 400 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 8 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 50.14% is already net of trading costs -- no additional fee adjustment is required when comparing to other runs.

Over the 364-day test window the strategy generated 22933.06 USDT of profit on a 10000 USDT starting balance, growing the account to 15014.24 USDT. Annualised, the 50.14% return over 364 days projects to roughly +50.3% per year -- a pace that would compound at a rate that comfortably outpaces traditional asset classes. Crypto market regimes shift quickly, so this projection should be treated as a directional indicator rather than a forecast.

Methodology & data

This backtest was executed on historical Binance Spot 1-minute candles for DGBUSDT, 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 every minute sequentially, evaluates the LongTimeLongMoreProfit 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.

Test window covers approximately 12.0 months of DGBUSDT 1-minute price action -- a sample size that is large enough to span multiple short-term regimes.

Live trading considerations

Translating this result to live trading: DGBUSDT 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.

Frequently asked questions

Is a 50.14% return on DGBUSDT a good backtest result?
Yes -- this clears the bar most automated crypto strategies fail to reach over a comparable window.
What does the 100.0% win rate mean here?
It means 100.0 out of every 100 closed trades ended profitable. Frequent wins are emotionally easier to operate but say nothing about size -- one large loss can offset many small wins.
What is the annualised return for this DGBUSDT backtest?
Compounding the 50.14% over 364 days projects to +50.3% per year. This is a directional indicator only -- crypto regimes change, and strategies rarely sustain peak performance year-over-year.
Can I run this exact LongTimeLongMoreProfit configuration live?
The configuration shown in the Strategy Configuration block is the same JSON the live unCoded TradingBot consumes, so it is directly deployable. Before going live, validate the run on a paper-trading window, confirm exchange-side fees match the simulated 7.5/7.5 bps, and start with a position size below the backtested capital to absorb live slippage.
How is this backtest different from others on DGBUSDT?
Every run on the platform uses the same intrabar-fill engine and historical Binance Spot data, so the comparison is apples-to-apples. What differs between runs is the LongTimeLongMoreProfit parameter set (buy trigger, sell zones, splits, stop-loss) and the time window -- both are visible above so you can rerun, tune, or fork this configuration.

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 DGBUSDT.

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Trades

0 Trades

0 abgeschlossene Trades – unCoded Crypto TradingBot Backtest
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