Live Backtest Results
This backtest analyzes the BTC Swing Points Detector strategy over the 2 week timeframe. The tested logic is consistent across the page: A long entry triggers when the Swing Points Detector identifies a confirmed swing low on the selected timeframe. The position exits when the indicator identifies a confirmed swing high, turning local pivots into the complete entry and exit rule.
ROI
965.7%
Win Rate
57.1%
Max DD
63.29%
Sharpe
0.73
Profit Factor
2.56
Total Trades
14
Backtest insights
The Swing Points Detector strategy generated a total return of 965.7% over the 2 week timeframe. With a maximum drawdown of 63.29% and a win rate of 57.1% across 14 trades, the result shows how this indicator rule reacted to BTC/USDT trend changes during the tested window. The same entry, exit, and timeframe rules are used across every metric on this page.
Performance may vary depending on market conditions. During trending periods, the strategy may behave differently compared to ranging markets, impacting both returns and drawdowns.
How the BTC Swing Points Detector Strategy Works
What It Is
The Swing Points Detector marks local pivot lows and pivot highs after enough bars confirm the structure. This test buys confirmed swing lows and exits on confirmed swing highs, creating a rule-based reversal framework. The page reports a real CoinQuant backtest on BTC/USDT 2 week data.
How Signals Are Generated
A long entry triggers when the Swing Points Detector identifies a confirmed swing low on the selected timeframe. The position exits when the indicator identifies a confirmed swing high, turning local pivots into the complete entry and exit rule. This keeps the strategy auditable and repeatable inside CoinQuant.
When It Works Best
This strategy tends to work best when confirmed pivot lows are followed by recoveries before the next confirmed pivot high appears. The 2 week timeframe captures a distinct market rhythm, so the same indicator can behave differently across horizons.
When It Performs Poorly
The strategy struggles when pivots are confirmed late or when BTC/USDT trends sharply through local levels. Confirmation delay can reduce responsiveness during fast market moves.
Strengths
Tests explicit local high and low structure
Uses clear pivot-based entries and exits
Helpful for comparing reversal behavior across timeframes
Limitations
Confirmed swing points can lag because right-side bars are required
Sharp trends can make pivot exits late
Choppy markets can create clustered pivots
Why Use CoinQuant Instead of Manual Trading or Other Platforms
Choosing the right way to test and execute trading strategies is critical. Below is a comparison between CoinQuant, manual trading, and other platforms to highlight key differences in speed, accuracy, and usability.
CoinQuant is designed specifically for traders who want to validate strategies quickly and reliably without coding. Unlike manual trading or traditional platforms, it allows you to test multiple scenarios, analyze performance instantly, and iterate faster using real data.
Frequently asked questions
How does the Swing Points Detector strategy perform on BTC/USDT in the 2 week timeframe?
In this backtest the Swing Points Detector strategy on the 2 week timeframe generated a return of 965.7% with a maximum drawdown of 63.29% and a win rate of 57.1% across 14 trades. These results are based on historical backtest data and actual performance may vary.
What is the Swing Points Detector indicator?
The Swing Points Detector marks local pivot lows and pivot highs after enough bars confirm the structure. This test buys confirmed swing lows and exits on confirmed swing highs, creating a rule-based reversal framework.
Why is backtesting important for trading strategies?
Backtesting evaluates how a strategy would have performed on historical data before risking real capital. It reveals metrics like ROI, drawdown, and win rate that show whether a strategy has a genuine edge.
How can I test the Swing Points Detector strategy on CoinQuant?
Paste the exact strategy prompt from this page into CoinQuant, select BTC/USDT and the 2 week timeframe, and CoinQuant generates a full backtest with performance metrics, no coding required.
What are the best settings for the Swing Points Detector strategy on the 2 week timeframe?
Optimal settings depend on the indicator parameters, timeframe, market regime, and trading objective. The default tested here is the exact rule shown in the strategy prompt. CoinQuant lets you test parameter variations to find the best fit for the 2 week timeframe.
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