Covariance Matrices, Portfolio Variance, and Diversification
Install and import#
npm install fintech-algorithmsimport { covarianceMatricesPortfolioVarianceAndDiversification } from "fintech-algorithms/financial-mathematics-statistics-and-data-foundations/financial-risk-and-performance-statistics/covariance-matrices-portfolio-variance-and-diversification";Signature#
covarianceMatricesPortfolioVarianceAndDiversification(input)Worked example#
verified This is the worked example published in the article, replayed by the test suite on every run. The output cannot drift.
Input#
{
"returns": [0.01, -0.02, 0.015, -0.01, 0.03],
"benchmark": [0.008, -0.01, 0.012, -0.006, 0.02],
"frequency": 252,
"target": 0,
"confidence": 0.8,
"riskFree": 0.0001,
"weights": [0.6, 0.4],
"covarianceMatrix": [
[0.04, 0.01],
[0.01, 0.09]
]
}Call#
covarianceMatricesPortfolioVarianceAndDiversification(input)Returns#
object with 2 fields: portfolioVariance, portfolioVolatility
{
"portfolioVariance": 0.033600000000000005,
"portfolioVolatility": 0.18330302779823363
}Diagrams#
How it works#
This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.
References#
- Expected Shortfall — Basel Framework MAR33
- Mutual Fund Performance — William F. Sharpe
- Measures of Scale — NIST/SEMATECH e-Handbook
- Historical-example decision