Mean-Variance Efficient Frontier

v1.0.0

Compute the discretized mean-variance efficient frontier associated to a list of assets, optionally subject to:

Minimum and maximum weights constraints
Maximum group weights constraints
Minimum and maximum portfolio exposure constraint

References

Harry M. Markowitz, Portfolio Selection, Efficient Diversification of Investments, Second edition, Blackwell Publishers Inc.

Input

{
  "type": "object",
  "required": [
    "assets",
    "assetsCovarianceMatrix",
    "assetsReturns"
  ],
  "properties": {
    "assets": {
      "type": "integer",
      "description": "The number of assets"
    },
    "assetsCovarianceMatrix": {
      "type": "array",
      "description": "assetsCovarianceMatrix[i][j] is the covariance between the asset i and the asset j",
      "items": {
        "type": "array",
        "items": {
          "type": "number"
        }
      }
    },
    "assetsReturns": {
      "type": "array",
      "description": "assetsReturns[i] is the arithmetic return of asset i",
      "items": {
        "type": "number"
      }
    },
    "constraints": {
      "type": "object",
      "properties": {
        "assetsGroups": {
          "type": "array",
          "items": {
            "type": "array",
            "description": "assetsGroups[k] is the indexes of the assets belonging to the assets group k in the portfolio; exclusive with assetsGroupsMatrix",
            "items": {
              "type": "integer"
            }
          }
        },
        "assetsGroupsMatrix": {
          "type": "array",
          "description": "assetsGroupsMatrix[k][i] is the weight of the asset i in the group of assets k; exclusive with assetsGroups",
          "items": {
            "type": "array",
            "items": {
              "type": "number"
            }
          }
        },
        "maximumAssetsGroupsWeights": {
          "type": "array",
          "description": "maximumAssetsGroupsWeights[k] is the maximum weight of the assets group k in the portfolio, in percentage between 0 and 1 if assetsGroups is provided",
          "items": {
            "type": "number"
          }
        },
        "maximumAssetsWeights": {
          "type": "array",
          "description": "maximumAssetsWeights[i] is the maximum weight of the asset i in the portfolio, in percentage",
          "items": {
            "type": "number"
          }
        },
        "maximumPortfolioExposure": {
          "type": "number",
          "description": "The maximum portfolio exposure; must be higher than or equal to minimumPortfolioExposure"
        },
        "minimumAssetsWeights": {
          "type": "array",
          "description": "minimumAssetsWeights[i] is the minimum weight of the asset i in the portfolio, in percentage",
          "items": {
            "type": "number"
          }
        },
        "minimumPortfolioExposure": {
          "type": "number",
          "description": "The minimum portfolio exposure; must be lower than or equal to maximumPortfolioExposure"
        }
      }
    },
    "portfolios": {
      "type": "integer",
      "description": "The number of portfolios to compute on the mean-variance efficient frontier"
    }
  }
}

Output

{
  "type": "object",
  "required": [
    "portfolios"
  ],
  "properties": {
    "portfolios": {
      "type": "array",
      "items": {
        "type": "object",
        "required": [
          "assetsWeights",
          "portfolioReturn",
          "portfolioVolatility"
        ],
        "properties": {
          "assetsWeights": {
            "type": "array",
            "description": "assetsWeights[i] is the weight of the asset i in the portfolio, in percentage",
            "items": {
              "type": "number"
            }
          },
          "portfolioReturn": {
            "type": "number",
            "description": "The arithmetic return of the portfolio"
          },
          "portfolioVolatility": {
            "type": "number",
            "description": "The volatility of the portfolio"
          }
        }
      }
    }
  }
}