Live Backtest Results
This backtest analyzes the performance of the Kaufman Efficiency Ratio strategy on BTC/USDT over the 15 Minute timeframe using historical market data. The Efficiency Ratio measures how directional (efficient) recent price movement is versus noise, entering only when the trend is clean. The results provide insight into profitability, risk exposure, and consistency.
ROI
-99.99%
Win Rate
34.83%
Max DD
99.99%
Sharpe
-4.27
Profit Factor
0.61
Total Trades
17971
Backtest insights
The Efficiency Ratio strategy generated a total return of -99.99% over the 15 Minute timeframe. With a maximum drawdown of 99.99% and a win rate of 34.83% across 17971 trades, the Efficiency Ratio filter aims to keep the strategy in position only during genuinely trending, low-noise conditions - favoring quality of trend over quantity of signals.
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 Efficiency Ratio Strategy Works
What It Is
The Kaufman Efficiency Ratio (ER) measures the ratio of net directional price change to the total path length over a lookback window. A value near 1.0 means a clean, efficient trend; a value near 0 means noisy, choppy price action. This BTC Efficiency Ratio strategy goes long only when the ER(10) confirms an efficient uptrend on the 15 Minute timeframe.
How Signals Are Generated
A long entry triggers when the Efficiency Ratio(10) rises above 0.30 and BTC/USDT closes above its 10-period SMA on the 15 Minute timeframe, confirming both trend quality and direction. The position exits when the ER(10) falls back below 0.30 (trend loses efficiency) or price closes below the 10-period SMA.
When It Works Best
This strategy performs best during sustained, low-noise trends where the Efficiency Ratio stays elevated. The 15 Minute timeframe captures a specific market rhythm where efficient directional moves tend to persist long enough to be profitable.
When It Performs Poorly
The strategy may underperform in choppy, sideways markets where price oscillates without clear direction, keeping the ER low and generating few or late signals. Sharp reversals can also trigger the SMA exit after a drawdown. Caution is warranted around major news events and low-liquidity sessions.
Strengths
Filters out noisy, choppy conditions - trades only clean trends
Clear, rule-based entry and exit signals reduce emotional trading
Adapts across timeframes with appropriate parameter tuning
Limitations
Can sit in cash for long stretches during ranging markets
SMA exit may lag sharp reversals, giving back some open profit
Fixed 0.30 threshold may not be optimal for every regime
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 Efficiency Ratio strategy perform on BTC/USDT in the 15 Minute timeframe?
In this backtest the Efficiency Ratio strategy on the 15 Minute timeframe generated a return of -99.99% with a maximum drawdown of 99.99% and a win rate of 34.83% across 17971 trades. These results are based on historical backtest data and actual performance may vary.
What is the Kaufman Efficiency Ratio?
The Efficiency Ratio (ER) is a Kaufman indicator that measures how efficient price movement is - the net change divided by the sum of absolute bar-to-bar moves over a lookback. Values near 1 signal a clean trend; values near 0 signal noise. It's used here to trade only when the trend is efficient.
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. Without backtesting, traders are flying blind.
How can I test the Efficiency Ratio strategy on CoinQuant?
Describe the strategy in natural language, select BTC/USDT and the 15 Minute timeframe, and CoinQuant instantly generates a full backtest with all performance metrics - no coding required.
What are the best settings for the Efficiency Ratio strategy on the 15 Minute timeframe?
Optimal settings depend on the ER lookback period, the efficiency threshold, and the SMA length used for direction. CoinQuant lets you test multiple parameter combinations to find the best fit for the 15 Minute timeframe.
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