CorrelationType.cs

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 * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
 * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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 * Licensed under the Apache License, Version 2.0 (the "License"); 
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*/
 
namespace QuantConnect.Indicators
{
    /// <summary>
    /// Defines the different types of Correlation
    /// </summary>  
    public enum CorrelationType
    {
        /// <summary>
        /// Pearson Correlation (Product-Moment Correlation):
        /// Measures the linear relationship between two datasets. The coefficient ranges from -1 to 1.
        /// A value of 1 indicates a perfect positive linear relationship, -1 indicates a perfect
        /// negative linear relationship, and 0 indicates no linear relationship.
        /// It assumes that both datasets are normally distributed and the relationship is linear.
        /// It is sensitive to outliers which can affect the correlation significantly.
        /// </summary>
        Pearson,
        /// <summary>
        /// Spearman Correlation (Rank Correlation):
        /// Measures the strength and direction of the monotonic relationship between two datasets.
        /// Instead of calculating the coefficient using raw data, it uses the rank of the data points.
        /// This method is non-parametric and does not assume a normal distribution of the datasets.
        /// It's useful when the data is not normally distributed or when the relationship is not linear.
        /// Spearman's correlation is less sensitive to outliers than Pearson's correlation.
        /// The coefficient also ranges from -1 to 1 with similar interpretations for the values,
        /// but it reflects monotonic relationships rather than only linear ones.
        /// </summary>
        Spearman
 
    }
}