MarketMakerTest • 6/4/2026, 12:42:29 PM
BTCUSDT | 1001MarketMakerTest.json | 2023-01-01 - 2023-12-31 | +36.24% | 1194404 trades | 62% WR
Strategy: MarketMakerTest | Period: 2023-01-01 to 2023-12-31 | Starting Capital: 100,000.00 USDT | Final Value: 136,239.87 USDT | Return: +36.24% | Trades: 1,194,404 | Win Rate: 62.0% | Best Trade: 0.0365 USDT | Worst Trade: -0.0104 USDT | Total Profit: +11,721.62 USDT | Max Drawdown: -15.94% | Profit Factor: 5.74 | Sharpe Ratio: 1.20 | Total Fees: 18,174.19 USDT
Backtest BTCUSDT (Mode: 1001MarketMakerTest.json) Period: 2023-01-01 00:00:01 to 2023-12-31 23:59:59 Starting balance: 100,000.00 USDT Final value: 136,239.87 USDT P&L: +36,239.87 USDT (+36.24%) Result: PROFIT Completed trades: 1194404 Open orders at end: 6198 Win rate: 62.0% Avg. profit/trade: 0.009814 USDT Best trade: 0.036485 USDT Worst trade: -0.010438 USDT Total profit (trades only): 11,721.623203 USDT Max drawdown: -15.94% Profit factor: 5.74 Sharpe ratio: 1.20 Total fees: 18,174.19 USDT Avg hold time: 32.2h TP / SL / TSL: 1194404 / 0 / 0 Strategy parameters: Buy trigger: -0.0025% from last buy Buy splits: 10 Sell targets: [0.05, 0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5] Investment per buy: 100.0 USDT Fees: maker 7.5 bps / taker 7.5 bps Elapsed: 4486.1s
The MarketMakerTest configuration produced a 36.24% return on BTCUSDT in the tested window. This is a positive single-window result; a like-for-like comparison against buy-and-hold of BTCUSDT over the same dates is required to judge whether the strategy added value beyond the underlying price move.
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.
The 62.0% closed-trade win rate on 1,194,404 closed BTCUSDT trades sits in the comfortable range — frequent wins keep equity curves smooth and reduce psychological drawdown when running MarketMakerTest live. This figure covers closed trades only and **excludes 6,198 orders** that were still open at the end of the window.
At roughly 3272.3 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: 0.0365 USDT. Worst: -0.0104 USDT. Average per trade: 0.0098 USDT.
Risk profile (closed trades only): Per-trade exposure was minimal — the worst closed 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 +0.00% to the account, giving a best-vs-worst ratio of roughly 3.50:1 between the extreme closed trades. Note: this is a closed-trade statistic — open positions and unrealized PnL are not included.
Configuration analysis: The MarketMakerTest configuration entered on a 0.0025% pullback signal across 10 potential buy splits at 100 USDT each. Total deployable notional is therefore 1000 USDT — a position-sizing footprint that is defensive at 1% 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 10 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 36.24% 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 11721.62 USDT of realised trade profit on a 100000 USDT starting balance, ending at a portfolio value of 136239.87 USDT. Mechanically annualising the 36.24% window return projects to roughly +36.2% 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 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 MarketMakerTest 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 BTCUSDT 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: 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.
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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