BTC
RELATIVE VOLATILITY INDEX
1MO

BTC Relative Volatility Index Strategy 1 Month Backtest Results

See how a BTC/USDT Relative Volatility Index strategy performs over the 1 month timeframe using real CoinQuant backtest data, including returns, drawdown, win rate, Sharpe ratio, profit factor, and trade count.

Performance

Live Backtest Results

This backtest analyzes the BTC Relative Volatility Index strategy over the 1 month timeframe. The tested logic is consistent across the page: A long entry triggers when the 14-period Relative Volatility Index crosses above the 50 level on the selected timeframe. The position exits when the same indicator crosses below 50, keeping the setup centered on volatility direction.

ROI

459.5%

Win Rate

28.6%

Max DD

50.11%

Sharpe

0.67

Profit Factor

5.48

Total Trades

7

Backtest insights

The Relative Volatility Index strategy generated a total return of 459.5% over the 1 month timeframe. With a maximum drawdown of 50.11% and a win rate of 28.6% across 7 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 Relative Volatility Index Strategy Works

What It Is

The Relative Volatility Index measures volatility direction rather than price momentum alone. This test uses the 50 level as a centerline, treating rising volatility pressure above 50 as the long trigger and a cross back below 50 as the exit. The page reports a real CoinQuant backtest on BTC/USDT 1 month data.

How Signals Are Generated

A long entry triggers when the 14-period Relative Volatility Index crosses above the 50 level on the selected timeframe. The position exits when the same indicator crosses below 50, keeping the setup centered on volatility direction. This keeps the strategy auditable and repeatable inside CoinQuant.

When It Works Best

This strategy tends to work best when volatility expansion supports directional continuation after the centerline cross. The 1 month timeframe captures a distinct market rhythm, so the same indicator can behave differently across horizons.

When It Performs Poorly

The strategy struggles when volatility shifts direction without price follow-through. Sideways BTC/USDT periods can create repeated centerline crosses with limited trend development.

Strengths

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Focuses on volatility direction rather than price alone

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Uses a transparent 50-level crossover

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Works across the standard 19 timeframe grid

Limitations

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Volatility can expand in either direction

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Centerline crosses can whipsaw in range-bound markets

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A 14-period setting may not suit 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.

Feature CoinQuant Manual Trading Other Platforms
Backtesting Speed Instant, automated Manual, time-consuming Often slow or limited
Data Accuracy Uses real historical market data Prone to human error Varies by platform
No-Code Strategy Building Fully no-code, beginner-friendly No Often requires coding or complex setup
Strategy Validation Full performance metrics (ROI, drawdown, win rate) Difficult to measure Partial or unclear
Ease of Use Beginner-friendly interface Requires experience Often technical
Learning Curve Low High Medium to high
Scalability Test multiple strategies quickly Not scalable Limited scaling
Automation Fully automated backtesting and execution Manual only Partial automation
Optimization Easy parameter testing and iteration Very difficult Limited tools
Setup Time Minutes, no coding required Hours / Days Moderate to high
Reliability of Results Structured, data-driven backtesting Depends on user accuracy Depends on platform
Time Efficiency Minutes Hours / Days Moderate
Best For Fast, no-code strategy validation and testing Experienced manual traders Mixed use cases

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 Relative Volatility Index strategy perform on BTC/USDT in the 1 month timeframe?

In this backtest the Relative Volatility Index strategy on the 1 month timeframe generated a return of 459.5% with a maximum drawdown of 50.11% and a win rate of 28.6% across 7 trades. These results are based on historical backtest data and actual performance may vary.

What is the Relative Volatility Index indicator?

The Relative Volatility Index measures volatility direction rather than price momentum alone. This test uses the 50 level as a centerline, treating rising volatility pressure above 50 as the long trigger and a cross back below 50 as the exit.

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 Relative Volatility Index strategy on CoinQuant?

Paste the exact strategy prompt from this page into CoinQuant, select BTC/USDT and the 1 month timeframe, and CoinQuant generates a full backtest with performance metrics, no coding required.

What are the best settings for the Relative Volatility Index strategy on the 1 month 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 1 month timeframe.

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