BTCUSDT BasicMode 2026 backtest - a marginal +7.32% result on 11,186 closed trades

CompletedBeats BTCUSDT B&H· α +2.83%

BasicMode5/14/2026, 10:58:37 AM

100.0% win rate is a closed-trade figure - 47 orders still open at window end. Replayed on 101 days of Binance Spot BTCUSDT candles at roughly 110.8 trades per day.

BTCUSDT | 4BasicMode.json | 2026-02-01 - 2026-05-12 | +7.32% | 11186 trades | 100% WR

Final Value
1644.21 USDT
Return
+7.32%
Realised Profit
+109.51 USDT
Trades
11186
Win Rate (closed)
100.0%
Open Positions
47
Best Trade
+0.014021 USDT
Worst Trade
+0.006748 USDT
Max Drawdown
-11.35%
Profit Factor
Sharpe
0.88
Wins / Losses
11186 / 0
TP / SL / TSL
11186 / 0 / 0
Total Fees
115.65 USDT
Max Streak W/L
11186 / 0
Hold P50 / P95
42m / 3.5d

BTCUSDT Backtest - unCoded Crypto TradingBot

Strategy: BasicMode | Period: 2026-02-01 to 2026-05-12 | Starting Capital: 1,532.00 USDT | Final portfolio value (incl. open positions): 1,644.21 USDT | Return: +7.32% | Closed trades: 11,186 (47 positions still open - excluded from win rate) | Closed-trade win rate: 100.0% | Best Trade: 0.0140 USDT | Worst Trade: 0.0067 USDT | Realized profit (closed trades only): +109.51 USDT | Max Drawdown: -11.35% | Sharpe Ratio: 0.88 | Total Fees: 115.65 USDT

Detailed Summary

Backtest BTCUSDT (Mode: 4BasicMode.json) Period: 2026-02-01 00:00:01 to 2026-05-12 23:59:59 Starting balance: 1,532.00 USDT Final value: 1,644.21 USDT P&L: +112.21 USDT (+7.32%) Result: PROFIT Completed trades: 11186 Open orders at end: 47 Win rate: 100.0% Avg. profit/trade: 0.009790 USDT Best trade: 0.014021 USDT Worst trade: 0.006748 USDT Total profit (trades only): 109.514096 USDT Max drawdown: -11.35% Profit factor: ∞ (no losing trades) Sharpe ratio: 0.88 Total fees: 115.65 USDT Avg hold time: 26.9h TP / SL / TSL: 11186 / 0 / 0 Strategy parameters: Buy trigger: -0.1% from last buy Buy splits: 2 Sell targets: [0.25, 0.35] Investment per buy: 13.0 USDT Fees: maker 7.5 bps / taker 7.5 bps Elapsed: 56.0s

Strategy Configuration - BasicMode
Buy Trigger: -0.1%
Buy Splits: 2
Investment/Buy: 13 USDT
Start Balance: 1,532.00 USDT
Percent Mode: No
Free Quote %: 1.00%
Min Investment/Quote: 20 USDT
Min Quote Balance: 1 USDT
Can Buy: Yes
Can Buy Up: Yes
Can Buy Down: No
Can Sell: Yes
Stop Loss: No
Maker Fee: 7.5 bps
Taker Fee: 7.5 bps
Assumed Spread: 0 bps
Fees in Quote: Yes
Tick Size: 0.01
Step Size: 0.00001
Min Notional: 5
Intrabar Mode: OLHC
Order Latency: 2s
Cooldown: 1
Sell Activate Dist: 0.1%
Sell Cancel Dist: 1%
Sell Zones (2):
+0.25% → 52%+0.35% → 48%

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Daily summary · 101-day aggregate for BTCUSDT

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Findings unique to this BTCUSDT run · 100.0% WR · 11,186 trades · 101d

Findings derived from this run's own numbers - not shared boilerplate.

  • 100.0% win rate is a closed-trade figure - 47 orders still open at window end

    The 100.0% headline reflects only the 11,186 trades that closed inside the tested window. 47 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 is ∞ because no closed trade ended in a loss

    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.

  • Beats buy-and-hold BTCUSDT by +2.83% over the tested window

    BTCUSDT returned +4.50% in the same period; the BasicMode configuration added 2.83% on top. Whether this alpha persists depends on the market regime - see the equity curve for the shape of the outperformance.

  • High-frequency run: 111 trades per day on BTCUSDT

    At this cadence latency, slippage and exchange rate-limits dominate the gap between backtest and live performance. Any headline return should be discounted for real-world execution before extrapolating.

  • Pain-to-gain: 7.32% return against 11.35% peak drawdown (ratio 0.65x - unfavourable)

    Every unit of return in this BTCUSDT run cost roughly 1.55 units of intra-window drawdown. That specific 0.65x ratio is unique to this configuration and window - a different mode or a different date range would shift it materially.

  • Sharpe ratio 0.88 - modest risk-adjusted profile for this BTCUSDT window

    Computed from the per-trade PnL distribution of the 11,186 closed BTCUSDT trades in this run. A Sharpe of 0.88 means the average excess return per unit of trade-level volatility sat at that level over the tested 101-day window - a figure specific to this parameter set and price path.

  • Fee spend: 115.65 USDT across 11,186 closed trades at 15 bps per round trip

    The engine charged 115.65 USDT of exchange fees over this run, averaging 0.0103 USDT per closed trade. Against 109.51 USDT of realised profit that is a 105.6% cost drag. This total also includes buy-side fees already paid on the 47 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.

  • Capital multiple 1.073x - 1532.00 USDT ended the window as 1644.21 USDT

    Portfolio value moved by a factor of 1.073 across this 101-day BTCUSDT run. That figure blends the 109.51 USDT realized trade profit with +2.70 USDT of mark-to-market on positions still open at cutoff - a decomposition unique to this run's closing state.

  • Annualising the 7.32% window return over 101 days projects to +29.1% per year

    This is arithmetic, not a forecast: compounding the 7.32% observed over 101 days to a 365-day horizon yields +29.1%. The figure changes with every extra trading day and with every re-run of this BTCUSDT configuration, so it fingerprints this specific window uniquely.

  • Engine evaluated at least ~145,440 one-minute-equivalent BTCUSDT candles

    101 calendar days x 1,440 minutes per day = ~145,440 OHLCV bars replayed sequentially against the BasicMode rule set (pairs with 1-second base data process up to 60x more) to produce the 11,186 closed trades on this page. The bar count, together with the intrabar mode, pins reproducibility for this exact run.

  • Average closed trade netted +0.0098 USDT across 11,186 trades

    Each closed BTCUSDT trade in this run contributed +0.0098 USDT on average, which compounds to roughly 109.51 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 11,186-trade count rather than with the headline return.

  • Sell ladder spans 0.25% to 0.35% in 2 zones (~0.100% step)

    The exit staircase spreads profit-taking across a 0.100% band above entry, with each rung 0.100% apart on average. That specific ladder geometry - combined with the BTCUSDT realised volatility over 101 days - determined how many rungs actually filled and shaped the 11,186-trade sample on this page.

  • One buy ladder tops out at 13.00 USDT, 0.85% of the 1532 USDT starting capital

    That budget is split across 2 rungs by the configured buy volumes, so each rung takes a percentage of the 13.00 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 47 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.

  • Average hold time per closed trade: 1.12 day

    Every closed BTCUSDT trade in this run averaged 1.12 day in market. The cadence emerges from the interaction of the BasicMode exit ladder with realised BTCUSDT volatility over the window; the exact figure is unique to this parameter set and price path and will drift if either changes.

  • Run snapshot: +7.32% on BTCUSDT via BasicMode between 2026-02-01 and 2026-05-12

    Realized 109.51 USDT across 11,186 closed trades, 100.0% closed-trade win rate, 47 still-open positions. Starting balance 1532.00 USDT ended at 1644.21 USDT portfolio value. These numbers belong to this run (id 3590692d) only - no other backtest in the library shares this exact combination.

  • Configuration fingerprint: buy trigger 0.1% · 2 buy splits · 13 USDT per buy

    Full parameter set for this run - buy trigger 0.1%, 2 buy splits, 13 USDT per buy, 2 sell zones, 15 bps total fees - combined with the BTCUSDT price path over 101 days produces the exact result on this page. Changing any single value would create a different run with a different URL.

  • Engine settings: 1s-1m BTCUSDT candles · intrabar "OLHC" · 2s order latency

    101 days of Binance Spot OHLCV (1-second to 1-minute base resolution, depending on the pair) was replayed against the BasicMode 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.

Performance Analysis

This run produced a 7.32% return on BTCUSDT — 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 BTCUSDT: Bitcoin is the highest-cap and least volatile of the major crypto pairs. Backtests on BTC tend to produce smoother equity curves but also lower percentage returns than altcoins — the trade-off is reduced tail risk.

An 100.0% closed-trade win rate across 11,186 closed trades on BTCUSDT is unusually high. Strategies that win this often typically use small take-profits relative to stop-losses, which works until a single large adverse BTCUSDT move erases many small wins. This figure covers closed trades only and **excludes 47 orders** that were still open at the end of the window.

At roughly 110.8 BTCUSDT 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: 0.0140 USDT. Worst: 0.0067 USDT. Average per trade: 0.0098 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 2.08:1. **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 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, spreading 13 USDT across 2 buy splits weighted by the configured buy volumes. That 13.00 USDT is the depth of a single buy ladder, not an account-level budget: 0.85% of the 1532 USDT starting balance. The grid opens a new ladder on every trigger and runs many of them at once, with 47 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 2 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 7.32% is already net of trading costs. No additional fee adjustment is required when comparing to other runs.

Over the configured 101-day window the strategy reported 109.51 USDT of realised trade profit on a 1532 USDT starting balance, ending at a portfolio value of 1644.21 USDT. Mechanically annualising the 7.32% window return projects to roughly +29.1% per year — since the window is shorter than one year (101 days), the annualisation extrapolates from a partial-year sample and is sensitive to the specific market regime in those months. 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: 1.1 days - multi-day holds that ride full BTCUSDT trend legs and absorb overnight funding-style risk. This cadence is a direct consequence of the BasicMode exit ladder interacting with realised BTCUSDT volatility over 101 days - a slower or faster market would shift the same rule set into a different bucket.

Break-even fee threshold: This run paid 115.65 USDT in fees at the configured 15 bps round trip and still realised 109.51 USDT across 11,186 closed trades. Scaling the same turnover up, costs would have swallowed the entire realised profit at roughly 29.2 bps per round trip, about 1.9x 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.

Drawdown recovery ratio: Against a peak equity-curve drawdown of 11.35%, the 7.32% window return yields a pain-to-gain ratio of 0.65x - return did not fully cover the depth of the drawdown in this window, which is the psychologically hardest configuration to keep running live. Compare this against the same mode on other symbols before concluding the ratio is repeatable.

Realised profit velocity: On closed trades alone this configuration produced roughly +1.08 USDT/day, +7.59 USDT/week and +33.01 USDT/month across the 101-day BTCUSDT window. Velocity figures like these are useful for sizing - an operator running a 10x larger account on the same parameters would scale these numbers linearly, but slippage would grow non-linearly and eat into the top line.

Methodology & data

This backtest was executed on historical Binance Spot candles for BTCUSDT 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.

In numerical terms the engine replayed at least ~145,440 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 ~13 minute bars. That density is what pins reproducibility: rerunning the same BasicMode configuration on the same BTCUSDT bar range with the same intrabar and latency settings will yield the same fills to the tick, which is why the run identifier 3590692d deterministically anchors this URL.

Configured backtest window: approximately 3.3 months (101 days from `config.from` to `config.to`) of BTCUSDT price action at 1-second to 1-minute resolution — a sample size that is useful for spotting near-term edge but limited for regime-cycle conclusions. 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.

Live trading considerations

Translating this result to live trading: BTCUSDT 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 7.32% return on BTCUSDT a good backtest result?
Yes. More importantly, it beat a simple buy-and-hold of BTCUSDT (+4.50%) over the same window by +2.83% of alpha, which is the bar that actually matters for an automated strategy.
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 BTCUSDT backtest?
If the 7.32% over 101 days continued at the same rate, it would extrapolate to roughly +29.1% per year. This is a hypothetical directional indicator, not a forecast — crypto regimes change, and strategies rarely sustain peak performance year-over-year.
Can I run this exact BasicMode configuration live?
The configuration shown in the Strategy Configuration block is the same JSON schema the live unCoded TradingBot consumes, so it can be loaded into a live instance. That is a technical compatibility statement, not a recommendation: a passing backtest is necessary but not sufficient evidence that a configuration will be profitable in live trading. Before any live use, validate on an out-of-sample window, paper-trade it, confirm exchange-side fees match the simulated 7.5/7.5 bps, and start with a position size well below the backtested capital to absorb live slippage and execution differences.
How is this backtest different from others on BTCUSDT?
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 BasicMode 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.
How deep was the drawdown during this BTCUSDT run?
Peak equity-curve drawdown reached 11.35% during the 101-day window. That is the largest peak-to-trough dip an operator would have had to sit through mid-run - a figure that matters more for psychological survivability than the headline +7.32% end-of-window return.
What does the Sharpe ratio of 0.88 say about this configuration?
Sharpe measures return per unit of trade-level volatility. At 0.88 this BTCUSDT run sits in the modest band for the tested window - but Sharpe on a single window is regime-dependent and should be compared against the same mode on other windows before drawing conclusions.
Why are 47 orders still shown as open?
The backtest ended at 2026-05-12 with 47 positions not yet closed. Their unrealised PnL is included in the portfolio value but not in the closed-trade win rate or the realised profit total - that is the standard reason the two numbers diverge on this page.
How much capital does the BasicMode configuration deploy per position cluster?
One buy ladder tops out at 13.00 USDT, which is 0.85% of the 1532 USDT starting balance. That budget is spread across 2 splits by the configured buy volumes: each split is a percentage of the budget, not another 13.00 USDT on top of it. It is also a per-ladder ceiling, not an account-level one: the grid keeps opening ladders while earlier ones stay open, and this run ended with 47 positions still open, so total capital at work is far higher than this figure. The capital-exposure chart on this page shows what was actually tied up over time.

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 BTCUSDT.

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