Struct SymbolCorrelationMatrix 

pub struct SymbolCorrelationMatrix {
    pub symbols: Vec<String>,
    pub matrix: Vec<Vec<f64>>,
    pub n: usize,
}

Full Pearson correlation matrix for a fixed set of symbols.

Constructed from complete return histories; not updated incrementally. For rolling / streaming use, see RollingCorrelation.

Fields

symbols: Vec<String>

Symbol labels in order.

matrix: Vec<Vec<f64>>

n×n correlation matrix (row-major).

n: usize

Dimension (number of symbols).

Implementations

impl SymbolCorrelationMatrix

pub fn from_returns(symbols: Vec<String>, returns: Vec<Vec<f64>>) -> Self

Build the Pearson correlation matrix from full return series.

symbols and returns must have the same length; all return slices must also have the same length (the minimum across series is used).

pub fn get(&self, i: usize, j: usize) -> f64

Get the correlation between symbols at indices i and j.

pub fn to_table(&self) -> String

Render the correlation matrix as a plain-text ASCII table.

pub fn highly_correlated(&self, threshold: f64) -> Vec<(String, String, f64)>

Returns all symbol pairs where |correlation| > threshold.

Each entry is (symbol_a, symbol_b, correlation) for i < j.

pub fn eigenvalues(&self) -> Vec<f64>

Compute eigenvalues of the correlation matrix using the Jacobi sweep algorithm.

Returns eigenvalues in descending order. The Jacobi method iteratively zeroes off-diagonal elements via plane rotations.

Trait Implementations

impl Clone for SymbolCorrelationMatrix

fn clone(&self) -> Self

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for SymbolCorrelationMatrix

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.