Expand description
§Moving Average Indicators
The moving_average module provides functions for calculating moving averages, a core component of many technical indicators and trading strategies.
A moving average smooths out price data by creating a constantly updated average price, helping to filter out noise and reveal trends.
§When to Use
Use these functions when you want to:
- Smooth raw price data
- Identify trends and trend reversals
- Serve as a basis for other indicators (e.g., MACD, Bollinger Bands)
- Experiment with advanced or custom moving average models
§Structure
- single: Functions that return a single value for a slice of prices.
- bulk: Functions that compute values of a slice of prices over a period and return a vector.
§Included Functions
§Bulk
mcginley_dynamic: McGinley Dynamic Moving Average (adaptive smoothing)moving_average: Configurable moving average (Simple, Smoothed, Exponential, or Personalized)
§Single
mcginley_dynamic: McGinley Dynamic Moving Averagemoving_average: Configurable moving average (Simple, Smoothed, Exponential, or Personalized)
§API Details
- Functions accept slices of
f64prices and a moving average type or relevant parameters. - Supported types include: Simple, Smoothed, Exponential, and Personalized (custom alpha).
- The McGinley Dynamic is an adaptive moving average that adjusts automatically to market speed.
- See function-level docs for formulas, panics, and usage examples.