quantitivecalc/dist/RiskAndVolatilityAnalysis/calculateVolatility.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.calculateVolatility = calculateVolatility;
/**
 * Calculates rolling volatility (standard deviation) of returns over a specified window size.
 *
 * @param data - Array of data objects containing return values.
 * @param returnsColumn - The key in each data object representing the return value.
 * @param resultColumn - The key to store the calculated volatility in each data object.
 * @param windowSize - The number of periods to use for the rolling window (default is 20).
 * @param annualize - Whether to annualize the volatility (default is true, assumes 252 trading days per year).
 * @returns A new array of data objects with the calculated volatility added under `resultColumn`.
 *
 * @remarks
 * - If there are not enough data points to fill the window, the volatility is set to `null`.
 * - Only numeric and non-NaN return values are considered in the calculation.
 */
function calculateVolatility(data, returnsColumn, resultColumn, windowSize = 20, annualize = true) {
    if (!data || data.length === 0) {
        return [];
    }
    const result = data.map(row => ({ ...row }));
    for (let i = 0; i < result.length; i++) {
        if (i < windowSize - 1) {
            result[i][resultColumn] = null;
        }
        else {
            // Get returns for the window
            const windowReturns = [];
            for (let j = i - windowSize + 1; j <= i; j++) {
                const returnValue = result[j][returnsColumn];
                if (typeof returnValue === 'number' && !isNaN(returnValue)) {
                    windowReturns.push(returnValue);
                }
            }
            if (windowReturns.length > 1) {
                // Calculate standard deviation
                const mean = windowReturns.reduce((sum, val) => sum + val, 0) / windowReturns.length;
                const variance = windowReturns.reduce((sum, val) => sum + Math.pow(val - mean, 2), 0) / (windowReturns.length - 1);
                let volatility = Math.sqrt(variance);
                // Annualize if requested (assuming daily data)
                if (annualize) {
                    volatility = volatility * Math.sqrt(252); // 252 trading days per year
                }
                result[i][resultColumn] = volatility;
            }
            else {
                result[i][resultColumn] = null;
            }
        }
    }
    return result;
}