quantitivecalc/dist/PortfolioAnalysis/calculateCorrelationMatrix.js

A TypeScript library providing advanced quantitative finance functions for risk analysis, performance metrics, and technical indicators. (Currently in development)

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.calculateCorrelationMatrix = calculateCorrelationMatrix;
/**
 * Calculates the rolling correlation matrix for a set of assets over a specified window size.
 *
 * @param data - An array of asset return objects, where each object contains asset return values keyed by asset name.
 * @param assetColumns - An array of asset names (keys in each data object) to include in the correlation matrix.
 * @param windowSize - Optional. The number of periods to use for the rolling window. If not provided, uses the entire data length.
 * @returns An array of correlation matrices, each representing the correlations between assets for a window of data.
 *
 * @remarks
 * - If `windowSize` is not specified, the function computes the correlation matrix for the entire dataset.
 * - Each correlation matrix is a nested object where the outer keys are asset names, and the inner keys are asset names with correlation values.
 * - Correlation values are set to `1` for diagonal elements (self-correlation), and `0` if there is insufficient data.
 * - Handles missing or invalid data by skipping those entries in the calculation.
 */
function calculateCorrelationMatrix(data, assetColumns, windowSize) {
    if (!data || data.length === 0 || assetColumns.length === 0) {
        return [];
    }
    const results = [];
    const effectiveWindowSize = windowSize || data.length;
    for (let i = effectiveWindowSize - 1; i < data.length; i++) {
        const windowData = data.slice(i - effectiveWindowSize + 1, i + 1);
        const correlationMatrix = {};
        // Initialize matrix
        assetColumns.forEach(asset1 => {
            correlationMatrix[asset1] = {};
            assetColumns.forEach(asset2 => {
                correlationMatrix[asset1][asset2] = asset1 === asset2 ? 1 : 0;
            });
        });
        // Calculate correlations
        for (let j = 0; j < assetColumns.length; j++) {
            for (let k = j; k < assetColumns.length; k++) {
                const asset1 = assetColumns[j];
                const asset2 = assetColumns[k];
                if (asset1 === asset2) {
                    correlationMatrix[asset1][asset2] = 1;
                    continue;
                }
                // Extract valid data pairs
                const pairs = [];
                windowData.forEach(row => {
                    const val1 = row[asset1];
                    const val2 = row[asset2];
                    if (typeof val1 === 'number' && typeof val2 === 'number' && !isNaN(val1) && !isNaN(val2)) {
                        pairs.push([val1, val2]);
                    }
                });
                if (pairs.length < 2) {
                    correlationMatrix[asset1][asset2] = 0;
                    correlationMatrix[asset2][asset1] = 0;
                    continue;
                }
                // Calculate means
                const mean1 = pairs.reduce((sum, pair) => sum + pair[0], 0) / pairs.length;
                const mean2 = pairs.reduce((sum, pair) => sum + pair[1], 0) / pairs.length;
                // Calculate correlation
                let numerator = 0;
                let sumSq1 = 0;
                let sumSq2 = 0;
                pairs.forEach(([val1, val2]) => {
                    const diff1 = val1 - mean1;
                    const diff2 = val2 - mean2;
                    numerator += diff1 * diff2;
                    sumSq1 += diff1 * diff1;
                    sumSq2 += diff2 * diff2;
                });
                const denominator = Math.sqrt(sumSq1 * sumSq2);
                const correlation = denominator === 0 ? 0 : numerator / denominator;
                correlationMatrix[asset1][asset2] = correlation;
                correlationMatrix[asset2][asset1] = correlation;
            }
        }
        results.push(correlationMatrix);
    }
    return results;
}