Inverse Distance Weighted Moving Average

The Inverse Distance Weighted Moving Average indicator provides a trend-following smoothing method that calculates price averages based on the relative distance between data points to emphasize significant price levels. It offers a more adaptive alternative to standard moving averages by weighing price values according to their proximity to other points within a specified lookback period.

Usage

The Inverse Distance Weighted Moving Average (IDWMA) is primarily used to identify trend direction and potential reversal points. Because the weighting mechanism is based on the sum of distances between points, the indicator reacts uniquely to price clusters and volatility.

• Trend Identification: Users can observe the slope and color of the IDWMA to determine the current market bias. A rising line (often colored green) suggests bullish momentum, while a falling line (often colored red) suggests bearish momentum.
• Support and Resistance: Like other moving averages, the IDWMA can act as dynamic support or resistance. Price crossovers (price moving above or below the IDWMA) are frequently used as signals for trend shifts.
• Mean Reversion: Large deviations between the price and the IDWMA may indicate overextended market conditions, suggesting a potential return to the average.

Details

The IDWMA is based on the concept of Inverse Distance Weighting, a deterministic interpolation method. In this specific implementation, the weight for each price point in the lookback window is determined by the sum of absolute differences (distances) between that point and all other points in the window.

The calculation follows these steps:

1. For each point $i$ in the length $n$, calculate the sum of distances between $src[i]$ and all $src[j]$ where $j$ ranges from $0$ to $n-1$.
2. Multiply the price at each point by its calculated weight.
3. Divide the total weighted sum by the sum of all weights to produce the final IDWMA value.

This approach ensures that price levels that are "closer" in value to the rest of the sample exert a different influence than outliers, providing a unique smoothing effect compared to time-weighted averages like the EMA or SMA.

Settings

• Length: The lookback period used for the calculation. Higher values result in a smoother line with more lag, while lower values make the indicator more responsive to recent price changes.
• Highlight Movements: A toggle to enable or disable color changes based on the directional slope of the moving average.
• Source: The price data point used for the calculation (e.g., Close, Open, High, Low, HL2).

FAQ

What makes IDWMA different from a Simple Moving Average? Unlike a Simple Moving Average which assigns equal weight to every data point, the IDWMA assigns weights based on the statistical "distance" between price points in the lookback period, making it more sensitive to price distribution.

How can I use this for trade signals? Common strategies include trading price crossovers (when price closes above or below the line) or using the color-coded slope changes to confirm trend direction.

How do I get access to the Inverse Distance Weighted Moving Average? You can get access on the LuxAlgo Library for charting platforms like TradingView, MetaTrader (MT4/MT5), and NinjaTrader for free.