Live Backtest Results
This backtest analyzes the performance of the RSI Mean Reversion strategy on ETH/USDT over the Daily timeframe using historical market data. The results provide insight into how the strategy would have performed under real market conditions, including profitability, risk exposure, and consistency.
ROI
-65.60%
Win Rate
42.11%
Max DD
69.93%
Sharpe
-0.20
Profit Factor
0.35
Total Trades
19
Backtest insights
The RSI Mean Reversion strategy generated a total return of -65.60%, indicating a net loss. The maximum drawdown of 69.93% suggests high volatility and significant risk exposure. With a win rate of 42.11% across 19 trades, the strategy demonstrates a limited sample size.
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 RSI Mean Reversion Strategy Works
What It Is
The RSI Mean Reversion strategy is built on the principle that price tends to revert to its average after stretching to an extreme. It combines two classic indicators: the 14-period Relative Strength Index (RSI) to measure momentum extremes, and Bollinger Bands (a 20-period SMA with bands set 2 standard deviations away) to measure statistical price deviation. When ETH/USDT becomes oversold and trades below its lower band, the strategy anticipates a snap-back toward the mean. The version tested on this page enters long when the 14-period RSI falls below 30 and price closes below the lower Bollinger Band, and exits when price reverts to the 20-period SMA or RSI crosses back above 50.
How Signals Are Generated
In this strategy, trading signals are generated based on predefined mean-reversion conditions. A buy signal occurs when ETH/USDT becomes oversold — the 14-period RSI drops below 30 while price closes below the lower Bollinger Band — indicating price has deviated below its statistical mean and is primed to revert. An exit signal occurs when price reverts back up to the 20-period SMA or the RSI crosses above 50, confirming the reversion has played out. With Daily candles, each signal reflects a broad stretch of market data, making individual signals less frequent but more significant.
When It Works Best
This strategy tends to perform best in range-bound macro regimes where ETH/USDT trades within a broad band and reverts to its mean after extended drawdowns. On the Daily timeframe, it excels during consolidation between major cycles, where deep oversold readings mark durable swing lows that revert toward the longer-term average.
When It Performs Poorly
However, the strategy may underperform during powerful trending or breakdown markets where ETH/USDT keeps making new lows without reverting. Extended directional moves on the Daily timeframe turn oversold conditions into prolonged oversold conditions, so reversion entries get repeatedly stopped or held through deepening drawdowns.
Strengths
Combines momentum (RSI) and statistical deviation (Bollinger Bands) for higher-conviction reversion entries
Buys into weakness at a discount to the mean, offering favorable risk/reward in range-bound markets
Mean-based exit locks in the reversion move without needing to predict the next trend
Limitations
Mean reversion fails in strong trends - oversold can stay oversold, leading to buying into sustained declines
Catching falling knives carries drawdown risk if price keeps deviating from the mean
RSI and band thresholds (30 / 2 std) may need tuning across different ETH volatility regimes
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 RSI Mean Reversion strategy perform on ETH/USDT in the Daily timeframe?
The performance of the RSI Mean Reversion strategy on ETH/USDT in the Daily timeframe depends on market conditions. Based on the backtest results above, it achieved a return of -65.60% with a maximum drawdown of 69.93%. Results may vary depending on volatility and overall market trends.
Is the RSI Mean Reversion strategy reliable for trading ETH/USDT?
The RSI Mean Reversion strategy can be effective when used in the right conditions. For ETH/USDT, it typically performs well during range-bound and consolidating markets but may underperform during strong trends where oversold conditions persist. Backtesting helps evaluate its reliability before applying it in live trading.
Why is backtesting important for trading strategies?
Backtesting allows traders to evaluate how a strategy would have performed using historical data. It helps identify strengths, weaknesses, and risk levels before applying the strategy in real markets, reducing the likelihood of unexpected losses.
How can I test the RSI Mean Reversion strategy on CoinQuant?
You can use CoinQuant to build and backtest the RSI Mean Reversion strategy without coding. Simply type the prompt shown below into the CoinQuant chat box and the platform will parse your natural language instruction, generate the strategy logic, and run the full backtest automatically.
What are the best settings for the RSI Mean Reversion strategy on the Daily timeframe?
The best settings depend on the asset and timeframe. Traders often adjust the RSI threshold (30 is standard, but 25 produces fewer, deeper oversold signals while 35 generates more frequent entries) and the Bollinger Band width (2 standard deviations is standard, but 2.5 demands a larger deviation before entry while 1.5 triggers earlier). Using a backtesting platform like CoinQuant allows you to test different configurations and identify what works best for Daily ETH/USDT trading.
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