Exemple of call to Portfolio Optimizer API, to compute the mean-variance minimum variance frontier

minimum_variance_frontier_appsscript.js

/**
 * Compute the mean-variance minimum variance frontier, as a list of (portfolio volatility, portfolio return) pairs.
 * 
 * @param {Array.<number>} returns, the assets returns, e.g. [0.01, 0.05]
 * @param {Array.<Array.<number>>} covarianceMatrix, the covariance matrix of the assets, e.g. [[1, 0], [0, 1]]
 * @param {number} portfolios, the number of portfolios to compute on the mean-variance minimum variance frontier, e.g. 25
 *
 * @return {Array.<Array.<number>>}, the list of (portfolio volatility, portfolio return) pairs to be inserted into a Google Spreadsheet
 **/
function computeMinimumVarianceFrontier(returns, covarianceMatrix, portfolios) {
  // Define the content of the request, with a JSON payload.
  var data = {
    "assets": covarianceMatrix.length,
    "assetsReturns": returns.map(x => x[0]), // Arrays are provided by Google Sheets as 2 dimensional, so, the last dimension must be removed
    "assetsCovarianceMatrix": covarianceMatrix,
    "portfolios": portfolios
  };
  
  // Request to Portfolio Optimizer
  var response = portfolioOptimizerAPICall("/v1/portfolio/analysis/mean-variance/minimum-variance-frontier", data);
  
  // Decode the response from Portfolio Optimizer
  var out = [];
  for (var i = 0; i < response.portfolios.length; ++i) {
    //
    var portfolio = response.portfolios[i];
    
    //
    var portfolioReturn = portfolio.portfolioReturn;
    var portfolioVolatility = portfolio.portfolioVolatility;
    var assetsWeights = portfolio.assetsWeights;
    
    //
    out.push([portfolioVolatility, portfolioReturn]);
  }
  
  // Return the decoded response to the sheet
  return out;
}