quantitivecalc/dist/riskAndVolatilityAnalysis.d.ts

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

/**
 * Risk and Volatility Analysis Utilities
 *
 * Functions:
 * - calculateVolatility: Calculates rolling volatility (standard deviation) of returns, with optional annualization.
 * - calculateMaxDrawdown: Calculates the maximum drawdown over time for a value series.
 * - calculateSharpeRatio: Calculates the rolling Sharpe ratio for a series of returns.
 * - calculateVaR: Value at Risk calculation (parametric, historical, Monte Carlo methods)
 * - calculateBeta: Stock's correlation with market benchmark
 *
 * All functions operate on arrays of objects (list of dicts) and allow you to specify source/result columns.
 */
export declare function calculateVolatility(data: Array<Record<string, any>>, returnsColumn: string, resultColumn: string, windowSize?: number, annualize?: boolean): Array<Record<string, any>>;
export declare function calculateMaxDrawdown(data: Array<Record<string, any>>, sourceColumn: string, resultColumn?: string): Array<Record<string, any>>;
export declare function calculateSharpeRatio(data: Array<Record<string, any>>, returnsColumn: string, resultColumn: string, windowSize?: number, // 1 year for daily data
riskFreeRate?: number): Array<Record<string, any>>;
export declare function calculateVaR(data: Array<Record<string, any>>, returnsColumn: string, resultColumn: string, confidenceLevel?: number, // 5% VaR (95% confidence)
windowSize?: number, method?: 'parametric' | 'historical' | 'monteCarlo'): Array<Record<string, any>>;
export declare function calculateBeta(data: Array<Record<string, any>>, assetReturnsColumn: string, benchmarkReturnsColumn: string, resultColumn: string, windowSize?: number): Array<Record<string, any>>;