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  • 1. Mean Method
  • 2. Median Method
  • 3. Kernel Density Estimation
  • Period Options
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  1. Statistics
  2. OHLC Macro Range Map™

Calculation

OHLC Macro Range Map Calculation

The OHLC Macro Range Map is an advanced tool designed to provide deeper insights into market dynamics by analyzing candlestick data using two key statistical methods:

  • Mean

  • Median

  • KDE

These methods, alongside insights into manipulation and distribution phases, empower traders to make more informed decisions based on price action.

1. Mean Method

The Mean method calculates the average of the Open, High, Low, and Close values of a candlestick. This approach offers a balanced representation of price action, helping traders identify central tendencies and equilibrium levels. When combined with manipulation and distribution insights, the Mean provides a clear understanding of price movement within a candlestick, specific to each session.

  • Bullish Candle:

    • Manipulation: Defined by the range between the Open and the Low, representing deceptive price movements aimed at misleading traders before the upward trend.

    • Distribution: Defined by the range between the Open and the High, showing the true extension of price in the bullish direction.

  • Bearish Candle:

    • Manipulation: Defined by the range between the Open and the High, indicating misleading price movements intended to trap traders before the downward trend.

    • Distribution: Defined by the range between the Open and the Low, representing the actual extension of price in the bearish direction.

2. Median Method

The Median method focuses on the middle value within the OHLC dataset, offering a robust measure of price action that minimizes the influence of outliers. By isolating the most central data point, the Median is especially effective in volatile markets, ensuring analysis remains unaffected by extreme wicks or spikes.

When paired with manipulation and distribution phases, the Median highlights stable zones and reliable price levels for potential trade entries or exits.

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.

Period Options

The algorithm includes several customizable period options, allowing traders to adjust statistical calculations to suit different market conditions. These periods determine how data is aggregated and how the Mean and Median are calculated over time for each specific session or "killzone."

  • 5 Candles: Short-term analysis, ideal for intraday traders seeking immediate price action insights.

  • 20 Candles: Medium-term perspective, suitable for swing traders aiming to capture broader trends.

  • 40 Candles: Balanced timeframe for detecting intermediate trends and price levels.

  • 60 Candles: Longer-term view for assessing significant market phases and identifying major support/resistance levels.

  • Custom: Fully customizable period, enabling traders to tailor the algorithm to specific strategies or unique market conditions.

  • Maximum: Includes all available candlesticks, providing a comprehensive view of historical market behavior.

The selected period directly influences the statistical outputs and traders' interpretation of key levels:

  • Short Periods (e.g., 5, 20): Highlight recent market activity, offering high responsiveness to current trends but more sensitivity to noise. Ideal for identifying immediate manipulation and distribution ranges within specific sessions.

  • Long Periods (e.g., 40, 60): Smooth out short-term fluctuations, providing a clearer view of underlying trends and significant liquidity levels within each session.

  • Custom and Maximum Periods: Offer flexibility to capture unique patterns or analyze market behavior over extended durations, enhancing strategy customization.

By combining the Mean, Median and KDE methods with dynamic period options, the OHLC Macro Range Map Algorithm empowers traders to analyze market behavior with precision and flexibility.

Shorter periods cater to fast-moving markets, while longer and customizable options ensure relevance across varying strategies.

Integrated with manipulation and distribution insights, this tool provides a comprehensive framework for understanding and navigating price action effectively across all key market sessions.

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Last updated 15 days ago