Calculation

OHLC Volatility Range Map

The OHLC Volatility Range Map is a cutting-edge tool designed to provide deeper insights into market dynamics by incorporating candlestick data analysis with a focus on volatility.

It utilizes two core statistical methods—Mean and Median—to deliver actionable insights into price behavior, especially during periods of heightened market activity.

Leveraging Volatility for Deeper Analysis

Volatility reflects the magnitude and speed of price movements, offering critical insights into market behavior. By combining statistical calculations with volatility principles, this algorithm empowers traders to identify key opportunities and mitigate risks in rapidly changing conditions.

1. Mean Method

The Mean method calculates the average of the Open, High, Low, and Close values for each candlestick. This approach provides a balanced representation of price action, highlighting central tendencies and equilibrium levels. When paired with volatility analysis, the Mean offers a clearer understanding of price movements within a candlestick:

• Bullish Candle: The range between the Open and the Low highlights the price's downward movement, while the range between the Open and the High reflects the upward extension of price action.

• Bearish Candle: The range between the Open and the High indicates the price's upward movement, while the range between the Open and the Low captures the downward price extension.

2. Median Method

The Median method focuses on the middle value of the OHLC dataset, offering a robust measure of price action that minimizes the impact of extreme wicks or spikes—common in volatile markets. When combined with volatility insights:

• The Median pinpoints key price levels less affected by sharp fluctuations.

• It helps traders find potential entry and exit points even in unpredictable market conditions.

3. Kernel Density Estimation

The Kernel Density Estimation (KDE) method focuses on identifying the most probable price levels within the OHLC dataset by estimating the underlying distribution of price action. Unlike simple averages or medians, KDE provides a smoothed view of the data, capturing subtle patterns and price clusters while minimizing the impact of outliers.

By modeling the distribution with a continuous curve, KDE is particularly effective in volatile markets, as it highlights zones of price stability even amidst rapid fluctuations.

When applied in conjunction with manipulation and distribution phases, KDE reveals densely populated price areas, offering reliable zones for potential trade entries or exits.

Volatility-Driven Insights

The OHLC Volatility Range Map Algorithm is more than a tool—it’s a comprehensive framework for navigating volatile markets. By integrating statistical methods with volatility analysis, it enables traders to:

• Identify high and low volatility zones.

• Recognize potential liquidity draws and key price levels.

• Adjust strategies to fast-changing market conditions.

Whether you're analyzing short-term fluctuations or longer-term trends, this algorithm equips you with the tools needed to master price action in any market environment.